This document provides an overview of a course on advanced process control fundamentals. The course aims to understand concepts of advanced industrial process control. Topics covered include process dynamics and control, process modeling, solution of differential equations, advanced control configurations, nonlinear compensation, multivariable control, and distributed control systems. Prerequisites for the course are several introductory control systems courses. The first lecture provides an introduction to process dynamics and control, including modeling a process, process control objectives, and the first order dynamics of processes. Process modeling involves formulating material and energy balances, developing constitutive equations, and ensuring the appropriate degrees of freedom.
In a split range control loop, the output of a controller is split and sent to two or more control valves to control a process. The controller output is sequenced such that one valve controls when the output is 0-50% and the other valve controls when the output is 50-100%. An example is given of controlling hotwell level using a split range strategy with a recirculation valve controlling when the level is below 50% and a deaerator valve controlling when it is above 50%. The strategy allows effective control of a process using multiple final control elements with a single controller output.
This document describes the closed loop control system used for boiler drum level control. It uses a three element control approach with drum level, feedwater flow, and main steam flow as process variables. During startup, a single 30% capacity feedwater control valve (FCV-101) is used to maintain drum level setpoint. At 30% load, control switches to two 100% capacity main feedwater valves (FCV-102) controlled via a three element algorithm. Drum level is measured by three level transmitters and averaged for input to the level controller (LIC-101). The controller output is summed with steam flow and used to set the remote setpoint for FIC-101, which controls FCV-102 position
The document discusses process control systems. It defines a process as a sequence of interdependent steps that transforms inputs into outputs. Control refers to regulating all aspects of a process. There are three main types of processes: continuous, batch, and discrete. A process control system uses sensors, controllers and actuators to monitor and regulate variables like pressure, temperature and flow to maintain efficiency and safety. Common applications include manufacturing plants and wastewater treatment. Advanced process control techniques like model predictive control use dynamic models and optimization to control multiple variables simultaneously.
This paper outlines fundamental topics related to classical control theory. It moves from modeling simple mechanical systems to designing controllers to manage said system.
This slide show contains a detailed explanation of the following topics from Control System:
1. Open loop & Closed loop
2. Mathematical modeling
3. f-v and f-i analogy
4. Block diagram reduction technique
5. Signal flow graph
Cascade control uses two or more interconnected control loops to control a process variable. In a basic cascade control scheme, the output of the primary controller determines the set point of the secondary controller. The secondary controller then adjusts the control variable. This allows the secondary controller to respond quickly to disturbances while the primary controller responds more slowly.
An example is given of using cascade control to maintain the temperature of a fluid heated by steam. A secondary flow controller loop would respond quickly to changes in steam flow, while the primary temperature controller loop would adjust more slowly to variations in fluid temperature. Cascade control in this case allows compensation for disturbances in both steam and fluid flow rates to better maintain the desired fluid temperature.
Mr. C.S.Satheesh, M.E.,
Basic elements in control systems
System
Types of Control Systems
Open Loop Control Systems
Closed Loop Control Systems
Difference Between Open loop & Closed loop Control Systems
The document discusses how work is done in a turbine. It explains that:
1) The heat energy in steam is converted to kinetic energy as it enters the turbine through nozzles, and then to mechanical work as it impacts the rotating blades.
2) Further work is done as the steam reacts with fixed blades, redirecting it to more rotating blades.
3) As the steam travels through the machine, it continually expands, giving up energy at each set of blades.
4) The tapering shape of the turbine allows the steam to enter at smaller blades and exit at larger blades.
In a split range control loop, the output of a controller is split and sent to two or more control valves to control a process. The controller output is sequenced such that one valve controls when the output is 0-50% and the other valve controls when the output is 50-100%. An example is given of controlling hotwell level using a split range strategy with a recirculation valve controlling when the level is below 50% and a deaerator valve controlling when it is above 50%. The strategy allows effective control of a process using multiple final control elements with a single controller output.
This document describes the closed loop control system used for boiler drum level control. It uses a three element control approach with drum level, feedwater flow, and main steam flow as process variables. During startup, a single 30% capacity feedwater control valve (FCV-101) is used to maintain drum level setpoint. At 30% load, control switches to two 100% capacity main feedwater valves (FCV-102) controlled via a three element algorithm. Drum level is measured by three level transmitters and averaged for input to the level controller (LIC-101). The controller output is summed with steam flow and used to set the remote setpoint for FIC-101, which controls FCV-102 position
The document discusses process control systems. It defines a process as a sequence of interdependent steps that transforms inputs into outputs. Control refers to regulating all aspects of a process. There are three main types of processes: continuous, batch, and discrete. A process control system uses sensors, controllers and actuators to monitor and regulate variables like pressure, temperature and flow to maintain efficiency and safety. Common applications include manufacturing plants and wastewater treatment. Advanced process control techniques like model predictive control use dynamic models and optimization to control multiple variables simultaneously.
This paper outlines fundamental topics related to classical control theory. It moves from modeling simple mechanical systems to designing controllers to manage said system.
This slide show contains a detailed explanation of the following topics from Control System:
1. Open loop & Closed loop
2. Mathematical modeling
3. f-v and f-i analogy
4. Block diagram reduction technique
5. Signal flow graph
Cascade control uses two or more interconnected control loops to control a process variable. In a basic cascade control scheme, the output of the primary controller determines the set point of the secondary controller. The secondary controller then adjusts the control variable. This allows the secondary controller to respond quickly to disturbances while the primary controller responds more slowly.
An example is given of using cascade control to maintain the temperature of a fluid heated by steam. A secondary flow controller loop would respond quickly to changes in steam flow, while the primary temperature controller loop would adjust more slowly to variations in fluid temperature. Cascade control in this case allows compensation for disturbances in both steam and fluid flow rates to better maintain the desired fluid temperature.
Mr. C.S.Satheesh, M.E.,
Basic elements in control systems
System
Types of Control Systems
Open Loop Control Systems
Closed Loop Control Systems
Difference Between Open loop & Closed loop Control Systems
The document discusses how work is done in a turbine. It explains that:
1) The heat energy in steam is converted to kinetic energy as it enters the turbine through nozzles, and then to mechanical work as it impacts the rotating blades.
2) Further work is done as the steam reacts with fixed blades, redirecting it to more rotating blades.
3) As the steam travels through the machine, it continually expands, giving up energy at each set of blades.
4) The tapering shape of the turbine allows the steam to enter at smaller blades and exit at larger blades.
This document discusses elements of process control systems including sensors, controllers, and control elements. It provides definitions of these elements and describes how they relate and interact in a process control loop based on a block diagram approach. The key elements are the process being controlled, sensors that measure process variables, a controller that determines necessary control actions, and control elements that implement adjustments to the process. The document also discusses criteria for evaluating how well a control system is performing including stability, steady-state regulation, and transient response.
This document discusses different types of control systems. It describes open loop and closed loop control systems. Open loop systems do not use feedback, so they are less accurate than closed loop systems which use feedback to reduce errors. Examples of open loop systems include a TV remote, microwave oven, and alarm system. Closed loop systems are found in applications like dryers, heating systems, elevators, and traffic collision avoidance. The document also covers requirements for good control systems and differences between tracking and control systems.
Heat can be transferred between two systems in three modes: conduction, convection, and radiation. In a heat exchanger, heat is transferred when two fluids at different temperatures flow through the exchanger. The rate of heat transfer depends on the overall heat transfer coefficient, which takes into account the resistances to heat transfer through the solid wall and boundary layers of each fluid. Common types of heat exchangers include shell-and-tube, plate, compact, regenerative, and cross-flow exchangers. The selection of a heat exchanger depends on factors like the fluids used, temperatures, pressures, and space requirements.
ENVEA designs and produces a complete range of state of the art CEMS gas and dust analyzers, sampling systems, data acquisition systems and software for the continuous measurement & reporting of stack pollutants.
With the global focus on emissions, the Group helps its clients quickly achieve environmental compliance in the most cost-effective manner.
Industrial emissions monitoring regulations vary from country to country, and the measurement technology must be assessed for suitability and in accordance with local requirements and standards.
Our solutions are fully compliant with the latest European and International regulations & standards.
Distributed Control System (Presentation)Thunder Bolt
A distributed control system (DCS) is a control system where control elements are distributed throughout a plant or process. Honeywell and Yokogawa introduced commercial DCS systems in 1975. A DCS includes field devices, controllers, HMIs, historians, and redundancy. It provides a single database, easier redundancy, and mitigation of processor failures, though complex failure diagnosis and cost are limitations. Major DCS vendors include ABB, Emerson, Honeywell, Siemens, and GE.
Ratio control is a feed-forward control scheme that measures and maintains a constant ratio between two disturbances (loads), usually flow rates. It is commonly used to control the ratio of reactants entering a reactor, the reflux ratio in distillation columns, and the fuel/air ratio in burners. Ratio control allows linking two streams to produce and maintain a defined ratio simply without needing a complex model. However, it assumes the correct ratio is maintained by controlling only one measured flow rate.
Control system basics, block diagram and signal flow graphSHARMA NAVEEN
This document discusses control systems and provides definitions and classifications of control systems. It defines a control system as an arrangement of physical elements connected to regulate, direct or command itself. Control systems are classified as natural or man-made, manual or automatic, open-loop or closed-loop, linear or non-linear. The key difference between open-loop and closed-loop systems is that closed-loop systems have feedback which makes them more accurate, reliable and less sensitive to parameter changes compared to open-loop systems. Examples of both open-loop and closed-loop systems are provided. The document also discusses transfer functions, Laplace transforms, block diagram reduction rules, and signal flow graphs.
This document is from Arasu Engineering College and discusses control systems and electrical circuits. It provides examples of obtaining transfer functions from RLC circuits using Kirchhoff's laws. It also discusses the transfer function of an armature controlled DC motor. The motor transfer function is derived by writing the differential equations for the electrical and mechanical systems and relating the armature current to torque, back emf to speed, and equating the electrical and mechanical equations. The final transfer function is obtained by substituting the equations and simplifying.
This document discusses optimal controller settings for a 604 process control. It describes how an optimizing control strategy can identify when a plant needs to change operating points to reduce costs. The strategy calculates new set point values for controllers to bring the plant to the new optimal operating conditions. Implementing digital computers allows supervisory control, where the computer calculates new set points and communicates them to control loops. The document also discusses performance criteria for controller tuning like decay ratio and time integral criteria.
This document describes a ratio control system. It begins with an introduction that explains a ratio controller holds the ratio of flow rates between two streams at a set point by controlling one stream. A block diagram then shows the ratio controller receiving inputs from flow transmitters on the two process lines. The description explains that one line is the "wild stream" while the other is controlled to maintain the desired ratio. Advantages are that the system can link streams to produce a defined ratio simply. Disadvantages are one flow may not be directly measured and the ratio relationship must exist between the variables.
Transfer function of Mechanical translational system KALPANA K
This document discusses transfer functions and mechanical translational systems. It contains the following key points:
1) The transfer function is defined as the ratio of the Laplace transform of the output variable to the Laplace transform of the input variable, assuming zero initial conditions.
2) Mechanical translational systems can be modeled using mass, spring, and dashpot elements. Forces acting on these elements are modeled using Newton's second law.
3) Examples are provided to illustrate how to write the differential equations for a mechanical system, take the Laplace transform to obtain algebraic equations, and determine the transfer function as the ratio of the output to input variable.
Chapter 1 introduction to control systemLenchoDuguma
This chapter introduces control systems and covers the following topics:
1. It defines open-loop and closed-loop control systems, with open-loop systems having no feedback and closed-loop systems using feedback to reduce errors between the output and desired input.
2. It discusses the history of control systems from the 18th century to present day, including developments in areas like stability analysis, frequency response methods, and state-space methods.
3. It compares classical and modern control theory, noting that modern control theory can handle more complex multi-input, multi-output systems through time-domain analysis of differential equations.
This document discusses different types of displays used in distributed control systems (DCS). It describes trend, group, schematic, detail, standard, alarm, loop, continuous process, graphic, batch, and overview displays. Trend displays are used for analyzing plant conditions over time. Group displays show operating parameters of control loops. Schematic displays provide a pictorial view of the plant. Detail displays show all parameters for a specific process point. Standard displays are block diagrams created by technicians. Alarm displays indicate emergency situations. Loop displays show closed-loop process control. Advantages of DCS include quality control, reduced installation costs, and operating efficiencies, while disadvantages include requiring skilled operators and potential for whole system failure if one component fails.
The document discusses instrumentation and controls used in boiler systems. It describes the key objectives of instrumentation including measurement, control, quality control and safety. It then provides details on various control loops used in boiler instrumentation including drum level control, steam temperature control, combustion control, furnace pressure control, deaerator pressure and level control, and soot blower pressure control. It stresses the importance of good maintenance management for instrumentation and controls.
This document discusses ratio control and split range control strategies. It describes ratio control as using one uncontrolled stream to adjust the flow of a second stream to maintain a desired ratio between the two streams. Split range control involves splitting a controller's output between two or more control valves to sequence their operation over different ranges of the controller's output. Examples are given of using split range control to manage pressure in a separator by opening a flare valve or closing a fuel gas valve depending on the pressure level.
The document discusses control systems and distributed control systems (DCS). It defines a control system as using feedback to maintain or alter quantities according to a desired state. A DCS uses distributed controllers and communication networks to control large, complex industrial processes. Key components of a DCS include field devices, input/output modules, controllers, human-machine interfaces, and control engineering software. DCS are suitable for large chemical plants, refineries, and other industrial applications where centralized control is not feasible.
This document provides an introduction to process control. It discusses control objectives like safety, production specifications, and economics. It defines control as maintaining desired conditions in a system by adjusting variables. Examples of control systems include maintaining temperature in a heated tank and steering a car. Feedback and feedforward control are described. The document outlines the major steps in control system development and provides an example of controlling temperature and level in a heated tank. Key points covered include measurements, control elements, structures, and calculations.
The document discusses process control and control systems. It defines control as maintaining desired conditions in a system by adjusting variables. Control is necessary to maintain variables when disturbances occur and to respond to changes in desired values. For control to be possible, the process must be designed so it responds well dynamically. Control systems use measurements from sensors to calculate adjustments to manipulated variables via controllers and final control elements. The document outlines various control strategies and characteristics of effective control systems.
This document discusses elements of process control systems including sensors, controllers, and control elements. It provides definitions of these elements and describes how they relate and interact in a process control loop based on a block diagram approach. The key elements are the process being controlled, sensors that measure process variables, a controller that determines necessary control actions, and control elements that implement adjustments to the process. The document also discusses criteria for evaluating how well a control system is performing including stability, steady-state regulation, and transient response.
This document discusses different types of control systems. It describes open loop and closed loop control systems. Open loop systems do not use feedback, so they are less accurate than closed loop systems which use feedback to reduce errors. Examples of open loop systems include a TV remote, microwave oven, and alarm system. Closed loop systems are found in applications like dryers, heating systems, elevators, and traffic collision avoidance. The document also covers requirements for good control systems and differences between tracking and control systems.
Heat can be transferred between two systems in three modes: conduction, convection, and radiation. In a heat exchanger, heat is transferred when two fluids at different temperatures flow through the exchanger. The rate of heat transfer depends on the overall heat transfer coefficient, which takes into account the resistances to heat transfer through the solid wall and boundary layers of each fluid. Common types of heat exchangers include shell-and-tube, plate, compact, regenerative, and cross-flow exchangers. The selection of a heat exchanger depends on factors like the fluids used, temperatures, pressures, and space requirements.
ENVEA designs and produces a complete range of state of the art CEMS gas and dust analyzers, sampling systems, data acquisition systems and software for the continuous measurement & reporting of stack pollutants.
With the global focus on emissions, the Group helps its clients quickly achieve environmental compliance in the most cost-effective manner.
Industrial emissions monitoring regulations vary from country to country, and the measurement technology must be assessed for suitability and in accordance with local requirements and standards.
Our solutions are fully compliant with the latest European and International regulations & standards.
Distributed Control System (Presentation)Thunder Bolt
A distributed control system (DCS) is a control system where control elements are distributed throughout a plant or process. Honeywell and Yokogawa introduced commercial DCS systems in 1975. A DCS includes field devices, controllers, HMIs, historians, and redundancy. It provides a single database, easier redundancy, and mitigation of processor failures, though complex failure diagnosis and cost are limitations. Major DCS vendors include ABB, Emerson, Honeywell, Siemens, and GE.
Ratio control is a feed-forward control scheme that measures and maintains a constant ratio between two disturbances (loads), usually flow rates. It is commonly used to control the ratio of reactants entering a reactor, the reflux ratio in distillation columns, and the fuel/air ratio in burners. Ratio control allows linking two streams to produce and maintain a defined ratio simply without needing a complex model. However, it assumes the correct ratio is maintained by controlling only one measured flow rate.
Control system basics, block diagram and signal flow graphSHARMA NAVEEN
This document discusses control systems and provides definitions and classifications of control systems. It defines a control system as an arrangement of physical elements connected to regulate, direct or command itself. Control systems are classified as natural or man-made, manual or automatic, open-loop or closed-loop, linear or non-linear. The key difference between open-loop and closed-loop systems is that closed-loop systems have feedback which makes them more accurate, reliable and less sensitive to parameter changes compared to open-loop systems. Examples of both open-loop and closed-loop systems are provided. The document also discusses transfer functions, Laplace transforms, block diagram reduction rules, and signal flow graphs.
This document is from Arasu Engineering College and discusses control systems and electrical circuits. It provides examples of obtaining transfer functions from RLC circuits using Kirchhoff's laws. It also discusses the transfer function of an armature controlled DC motor. The motor transfer function is derived by writing the differential equations for the electrical and mechanical systems and relating the armature current to torque, back emf to speed, and equating the electrical and mechanical equations. The final transfer function is obtained by substituting the equations and simplifying.
This document discusses optimal controller settings for a 604 process control. It describes how an optimizing control strategy can identify when a plant needs to change operating points to reduce costs. The strategy calculates new set point values for controllers to bring the plant to the new optimal operating conditions. Implementing digital computers allows supervisory control, where the computer calculates new set points and communicates them to control loops. The document also discusses performance criteria for controller tuning like decay ratio and time integral criteria.
This document describes a ratio control system. It begins with an introduction that explains a ratio controller holds the ratio of flow rates between two streams at a set point by controlling one stream. A block diagram then shows the ratio controller receiving inputs from flow transmitters on the two process lines. The description explains that one line is the "wild stream" while the other is controlled to maintain the desired ratio. Advantages are that the system can link streams to produce a defined ratio simply. Disadvantages are one flow may not be directly measured and the ratio relationship must exist between the variables.
Transfer function of Mechanical translational system KALPANA K
This document discusses transfer functions and mechanical translational systems. It contains the following key points:
1) The transfer function is defined as the ratio of the Laplace transform of the output variable to the Laplace transform of the input variable, assuming zero initial conditions.
2) Mechanical translational systems can be modeled using mass, spring, and dashpot elements. Forces acting on these elements are modeled using Newton's second law.
3) Examples are provided to illustrate how to write the differential equations for a mechanical system, take the Laplace transform to obtain algebraic equations, and determine the transfer function as the ratio of the output to input variable.
Chapter 1 introduction to control systemLenchoDuguma
This chapter introduces control systems and covers the following topics:
1. It defines open-loop and closed-loop control systems, with open-loop systems having no feedback and closed-loop systems using feedback to reduce errors between the output and desired input.
2. It discusses the history of control systems from the 18th century to present day, including developments in areas like stability analysis, frequency response methods, and state-space methods.
3. It compares classical and modern control theory, noting that modern control theory can handle more complex multi-input, multi-output systems through time-domain analysis of differential equations.
This document discusses different types of displays used in distributed control systems (DCS). It describes trend, group, schematic, detail, standard, alarm, loop, continuous process, graphic, batch, and overview displays. Trend displays are used for analyzing plant conditions over time. Group displays show operating parameters of control loops. Schematic displays provide a pictorial view of the plant. Detail displays show all parameters for a specific process point. Standard displays are block diagrams created by technicians. Alarm displays indicate emergency situations. Loop displays show closed-loop process control. Advantages of DCS include quality control, reduced installation costs, and operating efficiencies, while disadvantages include requiring skilled operators and potential for whole system failure if one component fails.
The document discusses instrumentation and controls used in boiler systems. It describes the key objectives of instrumentation including measurement, control, quality control and safety. It then provides details on various control loops used in boiler instrumentation including drum level control, steam temperature control, combustion control, furnace pressure control, deaerator pressure and level control, and soot blower pressure control. It stresses the importance of good maintenance management for instrumentation and controls.
This document discusses ratio control and split range control strategies. It describes ratio control as using one uncontrolled stream to adjust the flow of a second stream to maintain a desired ratio between the two streams. Split range control involves splitting a controller's output between two or more control valves to sequence their operation over different ranges of the controller's output. Examples are given of using split range control to manage pressure in a separator by opening a flare valve or closing a fuel gas valve depending on the pressure level.
The document discusses control systems and distributed control systems (DCS). It defines a control system as using feedback to maintain or alter quantities according to a desired state. A DCS uses distributed controllers and communication networks to control large, complex industrial processes. Key components of a DCS include field devices, input/output modules, controllers, human-machine interfaces, and control engineering software. DCS are suitable for large chemical plants, refineries, and other industrial applications where centralized control is not feasible.
This document provides an introduction to process control. It discusses control objectives like safety, production specifications, and economics. It defines control as maintaining desired conditions in a system by adjusting variables. Examples of control systems include maintaining temperature in a heated tank and steering a car. Feedback and feedforward control are described. The document outlines the major steps in control system development and provides an example of controlling temperature and level in a heated tank. Key points covered include measurements, control elements, structures, and calculations.
The document discusses process control and control systems. It defines control as maintaining desired conditions in a system by adjusting variables. Control is necessary to maintain variables when disturbances occur and to respond to changes in desired values. For control to be possible, the process must be designed so it responds well dynamically. Control systems use measurements from sensors to calculate adjustments to manipulated variables via controllers and final control elements. The document outlines various control strategies and characteristics of effective control systems.
This document provides an introduction to process dynamics and control. It discusses key topics including:
- The objectives of process control which are safety, production specifications, environmental regulations, operational constraints, and economics.
- The basic elements of a control system which are the process, sensor, controller, final control element, manipulated variable, process variable, and set point.
- An example of controlling temperature and liquid level in a stirred tank heater using feedback control and how this control system addresses disturbances.
- The importance of process control for reducing variability, ensuring safe and efficient operations, meeting regulations, and optimizing economics. Process control is needed to maintain processes within specified limits despite changing conditions.
This document provides an introduction to process control. It discusses the importance of process control for reducing variability, increasing efficiency, and ensuring safety. Precise control of process variables like temperature, pressure, and flow is important for process industries. The document outlines the basic components of a control loop, including sensors, controllers, and final control elements. It also describes different types of controllers and their algorithms, including proportional, integral, and derivative control modes. Controller tuning aims to determine the magnitude, duration, and speed of corrective actions.
This document compares control systems in process industries versus discrete manufacturing industries. It discusses that process industries deal with continuous materials and focus on continuous variables like temperature, while discrete manufacturing deals with discrete parts and focuses more on discrete variables like binary signals. It also summarizes different types of control strategies used in each industry, including regulatory control, feedforward control, steady-state optimization, adaptive control, and discrete control systems.
What is Controller, types of controllers How to Select the Right Controller ?Shahnawaz Merchant
A controller is a crucial part of an industrial automation system that manages and regulates the behavior of other devices or systems. It can be compared to the brain of a system, as it receives input, processes information, and sends commands to other parts of the system to achieve a desired outcome.
The document provides an introduction to process control. It defines process control and explains its importance in process industries. It discusses different types of processes like continuous, batch, and their characteristics. It also explains different process control elements like feedback, feedforward, manual and automatic control systems. It distinguishes between feedback and feedforward control schemes. It discusses different process variables involved in control like controlled, manipulated and disturbance variables. Finally, it explains concepts of process dynamics including different dynamic elements like resistance, capacitance, time constant, dead time, and their effect on process response.
This document provides an introduction to a course on Process Instrumentation and Control. It defines process control as dealing with mechanisms, architectures, and algorithms for controlling processes. Examples of controlled processes include controlling temperature with steam addition and maintaining fluid levels in tanks. The objectives of control are to maintain operational conditions, transition between conditions, and define key terminology like manipulated and disturbance inputs, control and output variables, and common control structures like SISO, MIMO, and PID controllers.
The document provides an overview of advanced process control (APC), including its definition, applications, advantages, and limitations. It discusses how APC builds on basic process control techniques by using process models and optimization to enhance plant operation and profitability. Examples are given of APC applications in petrochemical plants and semiconductor manufacturing. The benefits of APC include improved yield, quality, energy efficiency, and responsiveness. However, APC implementations are also complex, time-consuming, and require specialized expertise and resources.
Comparison of different controller strategies for Temperature controlIRJET Journal
This document compares different controller strategies (feedback, feedback with feedforward, and internal model control) for controlling temperature in a heat exchanger system. It describes a heat exchanger system with cold water input and temperature sensor output. The strategies are assessed based on transient response criteria like overshoot and settling time, and error-based criteria like integral of absolute and square errors. The study finds that internal model control outperforms the other strategies for a second-order plus dead time system.
This document provides an introduction to process control instrumentation and techniques. It is split into multiple units covering key topics like pressure, level, temperature, and flow measurements. The objectives are to understand the four main process variables that are measured and controlled, know what a process instrument is and how it functions, and gain an understanding of different instrument types and their applications in process control systems. Basic definitions of instrumentation terms are also provided to establish a common vocabulary.
Process control examples and applications Amr Seif
Process control involves maintaining the output of a process within a desired range through mechanisms and algorithms. For example, controlling the temperature of a chemical reactor to maintain consistent product output. There are different types of process control including regulatory control to maintain performance at a certain level, feedforward control which anticipates disturbances to compensate before they affect the process, and adaptive control where the controller modifies its own parameters based on dynamic process conditions. Discrete control systems make event-driven or time-driven changes to processes.
This document provides an overview of a chemical process control course. It includes:
- A list of course policies including exams, assignments, and grading.
- An outline of topics to be covered in the course ranging from process modeling to controller design.
- An introduction to process control concepts including different types of processes (continuous, batch, semibatch), control variables, and strategies for controlling processes like a blending operation.
The document provides details on the structure, content, and objectives of the chemical process control course.
This document provides an overview of process control tuning and PID control. It discusses the goals of controller tuning which are fast response and good stability, but these cannot be achieved simultaneously. PID control is then introduced which uses proportional, integral and derivative modes to achieve an acceptable compromise between stability and response speed. The key performance aspects of each control mode are explained. For proportional control, steady-state error is its main limitation. Integral control is used to eliminate this error over time by summing all past errors. Examples are also provided to demonstrate offset calculations for different control modes applied to a three-tank mixing process.
This document provides an overview of process control applications in chemical industries. It discusses what process control is, why it is needed, common control techniques like feedback control, and examples of control systems for units like chemical reactors and boilers. Process control is used to maximize safety, quality and efficiency in chemical processes. It allows preserving product quality while optimizing production. The document also reviews various software and instruments used for process control and highlights its importance across many industrial sectors.
This document discusses automation in the pharmaceutical industry. It defines automation and describes its advantages such as improved quality, reduced costs, and increased safety. Automation can occur at various stages of manufacturing like material handling, production processes, and quality control. The document also discusses process control and variables like temperature, pressure, and flow that are important to measure. It provides examples of automation in tablet manufacturing that can improve material handling and specific unit operations.
This document compares the performance of PID, PI, and MPC controllers for controlling water level in a tank process. It describes modeling the first-order plus dead time process in MATLAB and tuning the PID controller using Ziegler-Nichols method. Simulation results show that the MPC controller achieved better performance than the PID and PI controllers in terms of rise time, settling time, and overshoot. Specifically, the MPC controller had the shortest rise time and settling time, as well as the lowest overshoot of the three controllers evaluated.
This document provides an overview of different approaches for tuning PID controllers. It first introduces PID controllers and their proportional, integral and derivative terms. It then describes several common methods for tuning PID controllers, including manual tuning on-site, Ziegler-Nichols reaction curve method, Ziegler-Nichols oscillation method, and Cohen-Coon method. These tuning methods are compared based on their performance and applicability to different process control systems.
This document provides an overview of process control concepts including:
1. Process control refers to methods used to control process variables when manufacturing a product. Modeling the process is important for understanding how to control it.
2. The basic elements of a process control loop include a measurement, controller, actuator, and process. Common signals are the process variable and manipulated variable.
3. Common types of controllers are on-off, proportional, integral, derivative, and PID. On-off is simple but ineffective. Proportional reduces offset but has steady state error. Integral eliminates offset but can oscillate. Derivative reduces oscillations. PID combines all three for optimal control.
4. Cascade control uses
Comparative Analysis of Pso-Pid and Hu-PidIJERA Editor
PID control is an important ingredient of a distributed control system. The controllers are also embedded in many special purpose control systems. PID control is often combined with logic, sequential functions, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturing. Many sophisticated control strategies, such as model predictive control, are also organized hierarchically. PID control is used at the lowest level; the multivariable controller gives the set points to the controllers at the lower level. The PID controller can thus be said to be the “bread and butter‟ of power system engineering. It is an important component in every control engineer‟s tool box. PID controllers have survived many changes in technology, from mechanics and pneumatics to microprocessors via electronic tubes, transistors, integrated circuits. The microprocessor has had a dramatic influence on the PID controller
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
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our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
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The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
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2. Course Description
Aim:
To understand the concepts of advanced industrial
process control
Description:
A Review of Fundamental Process Control; Cascade
Control; Ratio Control; Dead Time Control;
Feedforward Control; Nonlinear Compensation and
Adaptive Control; Multivariable Control; Fuzzy
Logic and Process Control Tuning; Distributed
Control Systems.
3. General Content
Process Dynamics and Control
Process modeling
Solution of ODE
Process Control Tuning
Advanced Control Configurations
Nonlinear Compensation and Adaptive Control
Multivariable Control
Distributed Control System In Process Control
4. Reference Books
1. P.W. Murrill, ―Fundamentals of Process Control
Theory‖, 3rd Edition, 2000
2. K.T. Erikson, ―Plant –Wide Process Control‖, 1st
ed., Wiley Inter-science, 1999
5. Prerequisites
The prerequisite knowledge required to successfully
attend this course is:
• Introduction to measurement and Instrumentation
(EL-3312)
• Control Systems (EP-3111)
• Modern Control Systems (EP-4211)
• Digital Control Systems (EP-5511)
5
6. Lecture One
A Review of Fundamental Process
Control
• Introduction to process dynamics and
control
• Process modeling
7. What does a control system do?
Why is control necessary?
Why is control possible?
How is control done?
Where is control implemented?
What does control engineering ―Engineer‖?
How is Process Control Documented?
7
Introduction to Process Dynamics
and Control
8. Introduction to process …
Control engineering is an engineering science that is
used in many engineering disciplines:
• Chemical, Electrical, Mechanical, Biological
engineering, …
It is applied to a wide range of physical systems from
electrical circuits to guided missiles to robots.
The field of process control encompasses the basic
principles of physicochemical systems, such as
chemical reactors, heat exchangers, and mass
transfer equipment.
8
9. The task of engineers is to design, construct, and
operate a physical system to behave in a desired
manner, and an essential element of this activity is
sustained maintenance of the system at the desired
conditions—which is process control engineering.
Control in process industries refers to the regulation
of all aspects of the process.
Precise control of level, temperature, pressure and
flow is important in many process applications.
9
Introduction to process …
11. Introduction to process …
Variations in proportions, temperature, flow,
turbulence, and many other factors must be carefully
and consistently controlled to produce the desired end
product with a minimum of raw materials and
energy.
Process control technology is the tool that enables
manufacturers to keep their operations running within
specified limits and to set more precise limits to
maximize profitability, ensure quality and safety.
11
12. Importance of Process Control
1. Safety
2. Environmental protection
3. Equipment protection
4. Smooth plant operation and production rate
5. Product quality
6. Profit optimization
7. Monitoring and diagnosis
12
Introduction to process …
13. Introduction to process …
Process is the methods of changing or refining raw
materials to create end products.
The raw materials, either pass through or remain in a
liquid, gaseous, or slurry state during the process, are
transferred, measured, mixed, heated or cooled,
filtered, stored, or handled in some other way to
produce the end product.
13
14. Introduction to process …
Process industries include:
the chemical industry,
the oil and gas industry,
the food and beverage industry,
the pharmaceutical industry,
the water treatment industry, and
the power industry.
Process control refers to the methods that are used to
control process variables when manufacturing a
product.
14
15. Introduction to process …
Manufacturers control the production process for
three reasons:
Reduce variability
Increase efficiency
Ensure safety
Process control can reduce variability in the end
product, which ensures a consistently high-quality
product. Manufacturers can also save money by
reducing variability.
15
16. Introduction to process …
With accurate, dependable process control, the set
point can be moved
closer to the actual
product specification
and thus save the
manufacturer money.
Some processes need to be maintained at a specific
point to maximize efficiency.
For example, a control point might be the
temperature at which a chemical reaction takes place.
16
17. Introduction to process …
Accurate control of temperature ensures process
efficiency. Manufacturers save money by minimizing
the resources required to produce the end product.
Precise process control may also be required to
ensure safety.
For example, maintaining proper boiler pressure by
controlling the inflow of air used in combustion and
the outflow of exhaust gases is crucial in preventing
boiler implosions that can clearly threaten the safety
of workers.
17
18. Introduction to process …
Process Control Laws
First Law: The best control system is the simplest one
that will do the job.
Second Law: You must understand the process before
you can control it.
Third Law: The control is never possible if the
mathematical model can not be developed.
18
19. Introduction to process …
The dynamics of a Shower
What are the controlled or manipulated inputs?
( What part of the system can be directly changed?)
What are the set points?
( What end result is desired?)
What are the uncontrolled inputs?
(What disturbances can happen outside of the shower stall?)
Why might the set points change?
(The same way morning/night, summer/winter, …?)
What are the benefits of controlling this process?
19
21. Introduction to process …
Design aspects of Process control systems
Manipulated Variables: Variables - adjusted by the
operator or controller
Controlled Variables: The process value that is being
manipulated by a system, (T0, P, flow rate, level, etc)
Disturbances: Uncontrolled changes, such as weather
or feed composition
Measured Variables: values-can be directly measured
Final control element: The part of a control system
that has direct influence on the process and brings it
to the set-point condition.
21
22. Introduction to process …
Process control objectives
Operational objectives:
Stability of process
Suppress influence of disturbance
Optimize performance of plant
What variable should be measured & manipulated?
What is the best control configuration?
How should measurements be used to adjust the
manipulated variable?
22
23. Introduction to process …
Process Dynamics
First Order
Higher order
Dead time
23
dy
y kx
dt
1
k
s
x y
2
2
2
2
d y dy
y kx
dt dt
2 2
2 1
k
s s
x y
( ) x( )y t t
s
e x y
t0 t0
θ
24. Introduction to process …
Process Control
• Open-Loop Control: utilize a controller or control
actuator to obtain the desired response.
• Closed-Loop Control: utilizes feedback to compare
the actual output to the desired output response.
24
25. Process Modeling
Why a model is needed?
To make quantitative predictions about system
behaviour
To backup financial or other decisions
To optimize a new or existing process
To operate efficiently and safely an existing
process
For illustration / teaching
25
26. Process Modeling …
Modeling is a goal-oriented task, so the proper model
depends on its application.
Modeling is a task that requires creativity and
problem-solving skills.
The models used in process control are developed to
relate each input variable (cause) to the output
variable (effect).
The modeling approach enables us to reach this goal by
(1) developing the fundamental model and
(2) deriving the linearized models for each input output
dynamic response. 26
27. Process Modeling …
The procedure of process modeling provides a road
map for developing, solving, and interpreting
mathematical models based on fundamental
principles.
In addition to predicting specific behavior, these
models provide considerable insight into the
relationship between the process equipment and
operating conditions and dynamic behavior.
A thorough analysis of results is recommended in all
cases so that the sensitivity of the solution to
assumptions and data can be evaluated.
27
28. Process Modeling…
A process model is a set of equations that allows us
to predict the behavior of a chemical process system.
Process model is developed either:
by first principle or from empirical data
The control system engineer has three options:
1. Simulate the nonlinear system and numerically compute
its solution
2. Develop a linear system model that approximates the
dynamic behavior of the system in the neighborhood of
a specified operating point
3. Transform the nonlinear in to a linear system by an
approximate transformation of variables.
28
29. Process Modeling
The second option involves the following steps:
1. Formulate the system differential equations based
on the first principle (conservation balance)
2. Linearize the differential equations about the
operating point
3. Laplace transform these equations
4. Express as a transfer function
29
30. Process Modeling …
Process models are characterized as lumped
parameter system or distributed parameter systems.
A lumped parameter system assumes that a variable
changes only with one independent variable
Mathematically modeled by Ordinary
differential equations.
A distributed parameter system has more than one
independent variables.
Mathematically modeled by Partial differential
equations.
30
31. Process Modeling …
A Modeling Procedure
1. Define goals
2. Prepare information
3. Formulate model
4. Determine solution
31
• What decisions?
• What variable?
• Location
• Sketch process • State assumptions
• Collect data • Define system
• Conservation balances
• Constitutive equations
• Check degrees of freedom
• Dimensionless form
• Analytical
• Numerical
32. Process Modeling …
5. Analyze results
6. Validate model
32
• Check results for correctness
- sign and shape as expected
- obeys assumptions
• Plot results
• Evaluate sensitivity & accuracy
• Compare with empirical data
33. Process Modeling …
Conservation balance
Overall Material Balance
{Accumulation of mass} = {mass in} - {mass out}
Component Material Balance
{Accumulation of component mass}= {component mass in} -
. {component mass out} + {generation of component mass}
Energy Balance
{Accumulation of U + PE + KE} = {H + PE + KE in due to
. convection} - {H + PE + KE out due to convection}+ Q-Ws
H= U + pv = enthalpy
33
34. Process Modeling …
Guidelines in selecting the proper balances:
If the variable is total liquid mass in a tank or
pressure in an enclosed gas-filled vessel, a material
balance is appropriate.
If the variable is concentration (mole/m3 or weight
fraction, etc.) of a specific component, a component
material balance is appropriate.
If the variable is temperature, an energy balance is
appropriate.
34
35. Process Modeling …
Constitutive equations, e.g.
Heat transfer: Q = hA(AT)
Chemical reaction rate: rA = k0e-E/RT
CA
Equation of state: PV = nRT
How many equations do we need?
Degrees of freedom = NV - NE = 0
35
Not
fundamental,
based on
empirical data
36. Process Modeling …
Summary of degrees-of-freedom analysis
DOF = 0 The system is exactly specified, and the
solution of the model can proceed.
DOF < 0 The system is over specified, and in general,
no solution to the model exists. This is a
symptom of an error in the formulation.
DOF > 0 The system is underspecified, & an infinite
number of solutions to the model exists.
The model must be corrected to achieve
zero degrees of freedom.
36
37. Process Modeling …
Example 1: The mixing tank (CST) in the figure has
been operating for a long time with a feed
concentration of 0.925 kg-mole/m3. The feed
composition experiences a step to 1.85 kg-mole/m3.
All other variables are constant. Determine the
dynamic response. (90% composition)
Information: The system is the
liquid in the tank. the concentration
should be uniform in the liquid.
37
38. Process Modeling …
Assumptions:
1. Well-mixed vessel
2. Density the same for solute and solvent
3. Constant flow in (constant level)
Data:
F0 = 0.085 m3/min; V = 2.1 m3; CAinit = 0.925 mole/m3;
ΔCA0 = 0.925 mole/m3; thus, CA0 = 1.85 mole/m3 after
the step
The system is initially at steady state (CA0 = CA = CAinit)
38
39. Process Modeling …
Formulation: Since this problem involves
concentrations, overall and component material
balances will be prepared.
The overall material balance
{Accumulation of mass} = {mass in} - {mass out}
for constant V
(1)
39
0 1
dV
F F
dt
0 1
0 1
0,
dV
F F
dt
F F F
40. Process Modeling …
Component Material Balance
(2)
= τ time constant of mixer
40
Accumulation of component component generation
component A A in A out of A
0
0
0
( )
( )
1 1
A
A A A A
A
A A
A
A A
dC
MW V MW F C C
dt
dC F
C C
dt V
dC
C C
dt
V
F
41. Process Modeling …
Variables: CA and F1
External variables: F0 and CA0
DOF = NV-NE = 2-2 = 0
Solution
Multiplying both sides of (2) by the integrating factor,
(3)
Integrating both sides
41
/1
exp( ) t
IF dt e
/
/
0
( ) 1t
tA
A
d e C
C e
dt
/ /
0
/
0
1t t
A A
t
A A
C e C e I
C C Ie
(4)
42. Process Modeling …
The integration constant, I
At t=0, CAinit=CA0 – I I =CAinit – CA0
Two important aspects of the dynamic behavior:
Speed of the dynamic response, which is
characterized by the time constant, τ.
the steady-state gain, which is defined as
42
/
0 0
/
0 0
( )
(1 )
t
A A Ainit A
t
A Ainit A A init
C C C C e
C C C C e
(5)
0
1A
p
A
Coutput
k
input C
43. Process Modeling …
Results Analysis
43
Time
from step
Percent of final steady-
state change in output
0 0
T 63.2
2T 86.2
3T 95
4T 98.2
The goal statement
involves determining
the time until 90 % of
the change in outlet
concentration has
occurred.
This time can be calculated by setting
CA = CAinit + 0.9(CA0 - CAinit) in eqn. (5) and solving
Ainit A0
Ainit A0
0.1[ ]
ln (24.7)( 2.3) 56.8min
C C
t
C C
45. Process Modeling …
Validation
The mixing tank was built, the experiment was performed, and
samples of the outlet material were analyzed.
45
The data points are plotted
along with the model
prediction.
By visual evaluation and
considering the accuracy of
each data point, one would
accept the model as "valid"
for most engineering
applications.
Comparison of empirical
data (squares) & model
(line)