In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Model reduction of unstable systems based on balanced truncation algorithm IJECEIAES
Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Model reduction of unstable systems based on balanced truncation algorithm IJECEIAES
Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms.
It is rather surprising that in software engineering, standard measurement units have yet to be
widely accepted and used. Every other engineering discipline has their own. By and large, effort
is the most commonly used parameter for measuring software initiatives. The problem of
course is that effort is not an independent variable – it depends on who is doing the work and
how it is done. This presentation looks at an approach that has been used to convert the large
amount of effort data usually collected in an organization into something that can meaningfully
be used for estimation and comparison purposes.
Advance Control System MatLab & Simulink codes with outputsSurajKumarHS1
Table of Contents
1. Matrix Operations
2. Transient Response
3. Transfer Function to State Model
4. Time Response of a Dynamic System
5. Controllability and Observability
6. State Feedback Controller
7. Observer - Controller Design and it’s Transfer Function 8. Linear and Non-Linear Systems
9. Describing Function
10. Sylvester Theorem
11. Lyapunov Function
Justification of Montgomery Modular Reductionacijjournal
one of the most known and widely used methods in Cryptography is the method suggested by Peter
Montgomery; this method is based on the changing of the original reduction modulo by some other
convenient modulo, the original Montgomery paper gives the algorithm without any considerations
leading to that algorithm.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
It is rather surprising that in software engineering, standard measurement units have yet to be
widely accepted and used. Every other engineering discipline has their own. By and large, effort
is the most commonly used parameter for measuring software initiatives. The problem of
course is that effort is not an independent variable – it depends on who is doing the work and
how it is done. This presentation looks at an approach that has been used to convert the large
amount of effort data usually collected in an organization into something that can meaningfully
be used for estimation and comparison purposes.
Advance Control System MatLab & Simulink codes with outputsSurajKumarHS1
Table of Contents
1. Matrix Operations
2. Transient Response
3. Transfer Function to State Model
4. Time Response of a Dynamic System
5. Controllability and Observability
6. State Feedback Controller
7. Observer - Controller Design and it’s Transfer Function 8. Linear and Non-Linear Systems
9. Describing Function
10. Sylvester Theorem
11. Lyapunov Function
Justification of Montgomery Modular Reductionacijjournal
one of the most known and widely used methods in Cryptography is the method suggested by Peter
Montgomery; this method is based on the changing of the original reduction modulo by some other
convenient modulo, the original Montgomery paper gives the algorithm without any considerations
leading to that algorithm.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
PRIVACY ENHANCEMENT OF NODE IN OPPORTUNISTIC NETWORK BY USING VIRTUAL-IDijsc
An entrepreneurial system is one of the sort of remote system. Delay resistance system is correspondence
organizing proposition which empowers the correspondence in such a situation where end to end way
might never be exist. Message is forward on the premise of chance. Time interim to convey a message is
long we can't evaluate or anticipate the time until we get the message. There is a security issue in these
sorts of system. In this paper we will proposed another procedure which will expand the protection of the
system and build execution of the system.
PERFUSION SYSTEM CONTROLLER STRATEGIES DURING AN ECMO SUPPORTijsc
In this work modelling and control of Perfusion system is presented. The Perfusion system simultaneously
controls the partial pressures during Extra Corporeal Membrane Oxygenation (ECMO) support. The
main Problem in ECMO system is exchange of Blood Gases in the Artificial Lung (Oxygenator).It is a
highly Nonlinear Process comprising time-varying parameters, and varying time delays, it is currently
being controlled manually by trained Perfusionist. The new control strategy implemented here has a
feedback linearization routine with time-delay compensation for the Partial pressuresof Oxygen and
Carbon dioxide. The controllers were tuned robustly and tested in simulations with a detailed artificial
Lung (Oxygenator) model in Cardiopulmonary bypass conditions. This Automatic control strategy is
proposed to improve the patient’s safety by fast control reference tracking and good disturbance rejection
under varying conditions.
Broad phoneme classification using signal based featuresijsc
Speech is the most efficient and popular means of human communication Speech is produced as a sequence
of phonemes. Phoneme recognition is the first step performed by automatic speech recognition system. The
state-of-the-art recognizers use mel-frequency cepstral coefficients (MFCC) features derived through short
time analysis, for which the recognition accuracy is limited. Instead of this, here broad phoneme
classification is achieved using features derived directly from the speech at the signal level itself. Broad
phoneme classes include vowels, nasals, fricatives, stops, approximants and silence. The features identified
useful for broad phoneme classification are voiced/unvoiced decision, zero crossing rate (ZCR), short time
energy, most dominant frequency, energy in most dominant frequency, spectral flatness measure and first
three formants. Features derived from short time frames of training speech are used to train a multilayer
feedforward neural network based classifier with manually marked class label as output and classification
accuracy is then tested. Later this broad phoneme classifier is used for broad syllable structure prediction
which is useful for applications such as automatic speech recognition and automatic language
identification.
An artificial neural network model for classification of epileptic seizures u...ijsc
Epilepsy is one of the most common neurological disorders characterized by transient and unexpected
electrical disturbance in the brain. In This paper
the EEG signals are decomposed into a finite set of
bandlimited signals termed as Intrinsic mode functions.
The Hilbert transom is applied on these IMF’s to
calculate instantaneous frequencies. The 2nd,3rd an
d 4th IMF's are used to extract features of epilepticsignal. A neural network using back propagation alg
orithm is implemented for classification of epilepsy.An overall accuracy of 99.8% is achieved in classification..
Solving the associated weakness of biogeography based optimization algorithmijsc
Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and is based on an old theory of island biogeography that explains the geographical distribution of biological organisms. BBO was introduced in 2008 and then a lot of modifications and hybridizations were employed to enhance its performance. The researchers found that the original version of BBO has some weakness on its exploration. This paper tries to solve the root problems itself instead of solving its effect by using different techniques. It proposes two modifications; firstly, modifying the probabilistic selection process of the migration and mutation stages to give a fairly randomized selection for all the features of the islands. Secondly, the clear duplication process, which is located after the mutation stage, is sized to avoid any corruption on the suitability index variables of the non-mutated islands. The proposed modifications are extensively tested on 120 test functions with different dimensions and complexities. The results proved that the BBO performance can be enhanced effectively without embedding any additional sub-algorithm, and without using any complicated form of the immigration and emigration rates. In addition, the new BBO algorithm requires less CPU time and becomes even faster than the original simplified partial migration-based BBO. These essential modifications have to be considered as an initial step for any other modifications.
METAHEURISTIC OPTIMIZATION ALGORITHM FOR THE SYNCHRONIZATION OF CHAOTIC MOBIL...ijsc
We provide a scheme for the synchronization of two chaotic mobile robots when a mismatch between the
parameter values of the systems to be synchronized is present. We have shown how meta-heuristic
optimization can be used to adapt the parameters in two coupled systems such that the two systems are
synchronized, although their behavior is chaotic and they have started with different initial conditions and
parameter settings. The controlled system synchronizes its dynamics with the control signal in the periodic
as well as chaotic regimes. The method can be seen also as another way of controlling the chaotic
behavior of a coupled system. In the case of coupled chaotic systems, under the interaction between them,
their chaotic dynamics can be cooperatively self-organized. A synergistic approach to meta-heuristic
optimization search algorithm is developed. To avoid being trapped into local optimum and to enrich the
searching behavior, chaotic dynamics is incorporated into the proposed search algorithm. A chaotic Levy
flight is firstly incorporated in the proposed search algorithm for efficiently generating new solutions. And
secondly, chaotic sequence and a psychology factor of emotion are introduced for move acceptance in the
search algorithm. We illustrate the application of the algorithm by estimating the complete parameter
vector of a chaotic mobile robot.
Integrating vague association mining with markov modelijsc
The increasing demand of World Wide Web raises the need of predicting the user’s web page request. The
most widely used approach to predict the web pages is the pattern discovery process of Web usage mining.
This process involves inevitability of many techniques like Markov model, association rules and clustering.
Fuzzy theory with different techniques has been introduced for the better results. Our focus is on Markov
models. This paper is introducing the vague Rules with Markov models for more accuracy using the vague
set theory.
Methodological study of opinion mining and sentiment analysis techniquesijsc
Decision making both on individual and organizational level is always accompanied by the search of
other’s opinion on the same. With tremendous establishment of opinion rich resources like, reviews, forum
discussions, blogs, micro-blogs, Twitter etc provide a rich anthology of sentiments. This user generated
content can serve as a benefaction to market if the semantic orientations are deliberated. Opinion mining
and sentiment analysis are the formalization for studying and construing opinions and sentiments. The
digital ecosystem has itself paved way for use of huge volume of opinionated data recorded. This paper is
an attempt to review and evaluate the various techniques used for opinion and sentiment analysis.
A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a
simple method for gait identification which is based on moments. Moment values are extracted on different
number of frames of Gray Scale and Silhouette images of CASIA database. These moment values are
considered as feature values. Fuzzy logic and Nearest Neighbor Classifier are used for classification. Both
achieved higher recognition.
An Artificial Neural Network Model for Classification of Epileptic Seizures U...ijsc
Epilepsy is one of the most common neurological disorders characterized by transient and unexpected
electrical disturbance in the brain. In This paper the EEG signals are decomposed into a finite set of band
limited signals termed as Intrinsic mode functions. The Hilbert transom is applied on these IMF’s to
calculate instantaneous frequencies. The 2nd,3rd and 4th IMF's are used to extract features of epileptic
signal. A neural network using back propagation algorithm is implemented for classification of epilepsy.
An overall accuracy of 99.8% is achieved in classification..
In order to cope with real-world problems more effectively, we tend to design a decision support system for tuberculosis bacterium class identification. In this paper, we are concerned to propose a fuzzy diagnosability approach, which takes value between {0, 1} and based on observability of events, we
formalized the construction of diagnoses that are used to perform diagnosis. In particular, we present a
framework of the fuzzy expert system; discuss the suitability of artificial intelligence as a novel soft paradigm and reviews work from the literature for the development of a medical diagnostic system. The newly proposed approach allows us to deal with problems of diagnosability for both crisp and fuzzy value of input data. Accuracy analysis of designed decision support system based on demographic data was done
by comparing expert knowledge and system generated response. This basic emblematic approach using
fuzzy inference system is presented that describes a technique to forecast the existence of bacterium and
provides support platform to pulmonary researchers in identifying the ailment effectively.
EXPLORING SOUND SIGNATURE FOR VEHICLE DETECTION AND CLASSIFICATION USING ANNijsc
This paper attempts to explore the possibility of using sound signatures for vehicle detection and
classification purposes. Sound emitted by vehicles are captured for a two lane undivided road carrying
moderate traffic. Simultaneous arrival of different types vehicles, overtaking at the study location, sound of
horns, random but identifiable back ground noises, continuous high energy noises on the back ground are
the different challenges encountered in the data collection. Different features were explored out of which
smoothed log energy was found to be useful for automatic vehicle detection by locating peaks. Melfrequency
ceptral coefficients extracted from fixed regions around the detected peaks along with the
manual vehicle labels are utilised to train an Artificial Neural Network (ANN). The classifier for four
broad classes heavy, medium, light and horns was trained. The ANN classifier developed was able to
predict categories well.
A new design reuse approach for voip implementation into fpsocs and asicsijsc
The aim of this paper is to present a new design reuse approach for automatic generation of Voice over Internet protocol (VOIP) hardware description and implementation into FPSOCs and ASICs. Our motivation behind this work is justified by the following arguments: first, VOIP based System on chip (SOC) implementation is an emerging research and development area, where innovative applications can be implemented. Second, these systems are very complex and due to time to market pressure, there is a need to built platforms that help the designer to explore with different architectural possibilities and choose the circuit that best correspond to the specifications. Third, we aim to develop in hardware, design, methods and tools that are used in software like the MATLAB tool for VOIP implementation. To achieve our goal, the proposed design approach is based on a modular design of the VOIP architecture. The originality of our approach is the application of the design for reuse (DFR) and the design with reuse (DWR) concepts. To validate the approach, a case study of a SOC based on the OR1K processor is studied. We demonstrate that the proposed SoC architecture is reconfigurable, scalable and the final RTL code can be reused for any FPSOC or ASIC technology. As an example, Performances measures, in the VIRTEX-5 FPGA device family, and ASIC 65nm technology are shown through this paper.
Recently, many studies are carried out with inspirations from ecological phenomena for developing
optimization techniques. The new algorithm that is motivated by a common phenomenon in agriculture is
colonization of invasive weeds. In this paper, a modified invasive weed optimization (IWO) algorithm is
presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs) with the
criteria to minimize the maximum completion time (makespan), the total workload of machines and the
workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour
of weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solve
continuous optimization problems that’s why the heuristic rule the Smallest Position Value (SPV) is used to
convert the continuous position values to the discrete job sequences. The computational experiments show
that the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it is
able to find the optimal and best-known solutions on the instances studied.
Soft computing is likely to play aprogressively important role in many applications including image enhancement. The paradigm for soft computing is the human mind. The soft computing critique has been particularly strong with fuzzy logic. The fuzzy logic is facts representationas a
rule for management of uncertainty. Inthis paperthe Multi-Dimensional optimized problem is addressed by discussing the optimal thresholding usingfuzzyentropyfor Image enhancement. This technique is compared with bi-level and multi-level thresholding and obtained optimal
thresholding values for different levels of speckle noisy and low contrasted images. The fuzzy entropy method has produced better results compared to bi-level and multi-level thresholding techniques.
Classical methods for classification of pixels in multispectral images include supervised classifiers such as
the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector
machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a
method that generates many classifiers and aggregates their results. Breiman proposed Random Forestin
2001 for classification and clustering. Random Forest grows many decision trees for classification. To
classify a new object, the input vector is run through each decision tree in the forest. Each tree gives a
classification. The forest chooses the classification having the most votes. Random Forest provides a robust
algorithm for classifying large datasets. The potential of Random Forest is not been explored in analyzing
multispectral satellite images. To evaluate the performance of Random Forest, we classified multispectral
images using various classifiers such as the maximum likelihood classifier, neural network, support vector
machine (SVM), and Random Forest and compare their results.
Fault diagnosis of a high voltage transmission line using waveform matching a...ijsc
This paper is based on the problem of accurate fault diagnosis by incorporating a waveform matching technique. Fault isolation and detection of a double circuit high voltage power transmission line is of immense importance from point of view of Energy Management services. Power System Fault types namely single line to ground faults, line to line faults, double line to ground faults etc. are responsible for transients in current and voltage waveforms in Power Systems. Waveform matching deals with the approximate superimposition of such waveforms in discretized versions obtained from recording devices and Software respectively. The analogy derived from these waveforms is obtained as an error function of voltage and current, from the considered metering devices. This assists in modelling the fault identification as an optimization problem of minimizing the error between these sets of waveforms. In other words, it utilizes the benefit of software discrepancies between these two waveforms. Analysis has been done using the Bare Bones Particle Swarm Optimizer on an IEEE 2 bus, 6 bus and 14 bus system. The performance of the algorithm has been compared with an analogous meta-heuristic algorithm called BAT optimization on a 2 bus level. The primary focus of this paper is to demonstrate the efficiency of such methods and state the common peculiarities in measurements, and the possible remedies for such distortions.
Design of Multiloop Controller for Three Tank Process Using CDM Techniques ijsc
In this study the controller for three tank multi loop system is designed using coefficient Diagram method. Coefficient Diagram Method is one of the polynomial methods in control design. The controller designed by using CDM technique is based on the coefficients of the characteristics polynomial of the closed loop system according to the convenient performance such as equivalent time constant, stability indices and stability limit. Controller is designed for the three tank process by using CDM Techniques; the simulation results show that the proposed control strategies have good set point tracking and better response capability.
COMPARATIVE ANALYSIS OF CONVENTIONAL PID CONTROLLER AND FUZZY CONTROLLER WIT...IJITCA Journal
All the real systems exhibits non-linear nature,conventional controllers are not always able to provide good and accurate results. Fuzzy Logic Control is used to obtain better response. A model for simulation is designed and all the assumptions are made before the development of the model. An attempt has been made to analyze the efficiency of a fuzzy controller over a conventional PID controller for a three tank level control system using fuzzification & defuzzification methods and their responses are compared. Analysis is done through computer simulation using Matlab/Simulink toolbox. This study shows that the application of Fuzzy Logic Controller (FLC) gives the best response with triangular membership function and centroid defuzzification method.
EHR ATTRIBUTE-BASED ACCESS CONTROL (ABAC) FOR FOG COMPUTING ENVIRONMENTcsandit
Liquid level tanks are employed in many industrial and chemical areas. Their level must be keep
a defined point or between maximum-minimum points depending on changing of inlet and outlet
liquid quantities. In order to overcome the problem, many level control methods have been
developed. In the paper, it was aimed that obtain a mathematical model of an installed liquid
level tank system. Then, the mathematical model was derived from the installed system
depending on the sizes of the liquid level tank. According to some proportional-integralderivative
(PID) parameters, the model was simulated by using MATLAB/Simulink program.
After that, data of the liquid level tank were taken into a computer by employing data
acquisition cards (DAQs). Lastly, the computer-controlled liquid level control was successfully
practiced through a written computer program embedded into a PID algorithm used the PID
parameters obtained from the simulations into Advantech VisiDAQ software
Controller Tuning for Integrator Plus Delay Processes.theijes
A design method for PID controllers based on internal model control (IMC) principles, direct synthesis method (DS), stability analysis (SA) method for pure integrating process with time delay is proposed. Analytical expressions for PID controllers are derived for several common types of process models, including first order and second-order plus time delay models and an integrator plus time delay model. Here in this paper, a simple controller design rule and tuning procedure for unstable processes with delay time is discussed. Simulation examples are included to show the effectiveness of the proposed method
Design of a new PID controller using predictive functional control optimizati...ISA Interchange
An improved proportional integral derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers.
Comparison Analysis of Model Predictive Controller with Classical PID Control...ijeei-iaes
pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC) is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT) model controlled by Proportional Integral Derivative (PID) and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.
Robust design of a 2 dof gmv controller a direct self-tuning and fuzzy schedu...ISA Interchange
This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure–or simply GMV2DOF–within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina.
Dynamic Matrix Control (DMC) on jacket tank heater - Rishikesh BagweRishikesh Bagwe
The Dynamic Matrix Control (DMC) method of Model Predictive Control was simulated in MATLAB on Jacketed Tank Heater. The characteristics of the liquid being controlled are height and temperature
Mathematical Modeling and Fuzzy Adaptive PID Control of Erection MechanismTELKOMNIKA JOURNAL
This paper describes an application of fuzzy adaptive PID controller to erection mechanism.
Mathematical model of erection mechanism was derived. Erection mechanism is driven by electrohydraulic
actuator system which is difficult to control due to its nonlinearity and complexity. Therefore fuzzy
adaptive PID controller was applied to control the system. Simulation was performed in Simulink software
and experiment was accomplished on laboratory equipment. Simulation and experiment results of erection
angle controlled by fuzzy logic, PID and fuzzy adaptive PID controllers were respectively obtained. The
results show that fuzzy adaptive PID controller can effectively achieve the best performance for erection
mechanism in comparison with fuzzy logic and PID controllers.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
Metamodel-based Optimization of a PID Controller Parameters for a Coupled-tan...TELKOMNIKA JOURNAL
Liquid flow and level control are essential requirements in various industries, such as paper
manufacturing, petrochemical industries, waste management, and others. Controlling the liquids flow and
levels in such industries is challenging due to the existence of nonlinearity and modeling uncertainties of
the plants. This paper presents a method to control the liquid level in a second tank of a coupled-tank plant
through variable manipulation of a water pump in the first tank. The optimum controller parameters of this
plant are calculated using radial basis function neural network metamodel. A time-varying nonlinear
dynamic model is developed and the corresponding linearized perturbation models are derived from the
nonlinear model. The performance of the developed optimized controller using metamodeling is compared
with the original large space design. In addition, linearized perturbation models are derived from the
nonlinear dynamic model with time-varying parameters.
FRACTIONAL ORDER PID CONTROLLER TUNING BASED ON IMC IJITCA Journal
In this work, a class of fractional order controller (FOPID) is tuned based on internal model control
(IMC). This tuning rule has been obtained without any approximation of time delay. Moreover to show
usefulness of fractional order controller in comparison with classical integer order controllers, an
industrial PID controller tuned in a similar way, is compared with FOPID and then robust stability of both
controllers is investigated. Robust stability analysis has been done to find maximum delayed time
uncertainty interval which results in a stable closed loop control system. For a typical system, robust
stability has been done to find maximum time constant uncertainty interval of system. Two clarify the
proposed control system design procedure, three examples have been given.
Similar to Design of multiloop controller for (20)
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Design of multiloop controller for
1. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
DOI: 10.5121/ijsc.2014.5202 11
DESIGN OF MULTILOOP CONTROLLER FOR
THREE TANK PROCESS USING CDM TECHNIQUES
N. Kanagasabai1
and N. Jaya2
1,2
Department of Instrumentation Engineering,Annamalai University,
Annamalainagar, 608002, India
ABSTRACT
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
KEYWORDS
Coefficient diagram method, three tank, multiloop, CDM-PI
1. INTRODUCTION
Most of the processes industry in power plants, refinery process, aircrafts and chemical industries
are multivariable or multi-input multi-output (MIMO) and control of these MIMO processes are
more complicated than SISO processes. The strategies are used to design a controller for the Single
input and single output (SISO) process cannot be applied for Multi input and multi output (MIMO)
process because of the more interaction between the two loops. The different methods have been
presented in the literature for control [1] of MIMO process. Proportional-integral-derivative (PID)
or Proportional-Integral (PI) based controllers are used very commonly to control three tank
systems. Generalized synthesis method used to tuning the controller parameters. Generally the two
types of control schemes are available to control the MIMO processes. The first control scheme or
multiloop control scheme, where single loop controller are used to in the form of diagonal matrix is
one.. The second scheme is a [3] multivariable controller known as the centralized controller.
Matrix is not a diagonal one.
In this paper, the Coefficient Diagram Method (CDM) can be used to design a controller for MIMO
process. Now the CDM is well established approach to design a controller, which provides an
outstanding time domain characteristics of closed loop systems. Basically the CDM is based on
pole assignment, which can locate of the closed-loop system are used to obtained the predetermined
values. Although it has been used to demonstrate the design based on CDM. It has some robustness
and is possible to see that of the smooth response without oscillation in change in the model of the
process exists.
2. COEFFICIENT DIAGRAM METHOD
The CDM design procedure is quiet easily understandable, efficient and useful. Therefore, the
coefficients of the CDM controller polynomials which can be determined more easily than the PID
2. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
12
controller strategies. The CDM design procedure efficient design method (CDM) is possible to
design very good controllers with less effort and easy when compared with the other method, under
the conditions of stability, time domain performance and robustness. The transfer function of the
numerator and denominator of the system are obtained independently according to stability and
response requirements.. Generally the order of the controller designed by CDM is lower than the
order of the plant. when using the PI controller for the first order plant, the order of the controller is
equal to the order of the plant, and for the second order plant, the order of the controller is lower
than the order of the plant equal to one .The parameters are stability index γi equivalent time
constant and stability limit γi
*
which represent the desired performance. The basic block diagram
of the CDM design for a single-input-single-output system is shown in Fig. 1.Where y is the output
signal, r is the reference signal, u is the controller signal and d is the external disturbance signal.
N(s) and D(s) are to be numerator and Denominator of the plant transfer function. A(s) is the
denominator polynomial of the controller transfer function, F(s) and B(s) are called the reference
numerator and the feedback numerator polynomials of the controller transfer function. The CDM
controller structure they are similar to each other. It has Two Degree of Freedom (2DOF) control
structure because of two numerators in controller transfer function. The system output is given by
d
P(s)
A(s)N(s)
r
P(s)
(s)N(s)F
(s)y += (1)
P(s) =A(s) D(s) +B(s) N(s) = ∑=
n
0i
i
i sa (2)
Where P(s) is the characteristics polynomial of the closed loop system. The CDM design
parameters with respect to the characteristic polynomial coefficient which are equivalent time
constant τ, stability index γi and stability limit γi are defined as
0a
1a
τ = (3a)
1i,
1ia
1ia
2
ia
i
γ =
−+
= ~(n-1), nγ0γ = (3b)
γi
*
= + (3c)
From equation (3a - 3c), the coefficients ai and the target characteristic polynomial Ptarget(s) is given
by
ai = 0aiZ0a
1i
1j
j
jiγ
iτ
=
∏ −
= −
(4)
Ptarget(s) =a0 (5)
++∑ = ∏ −
=
−
1τsn
2i
iτs)(1i
1j
ji
jγ
1
3. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
13
Fig.1: Basic block diagram of CDM
3 .CONTROLLER DESIGN USING CDM
Many of the processes in industry are described as First order process with time delay (FOPTD)
Gp (s) =
sθ
e
1spτ
Kp −
+
(6)
Where kp is process gain is time constant and is time delay. Since the transfer function of the
process is of two polynomials, one is numerator polynomial N(s) of degree m and other is the
denominator polynomial D(s) of degree n where m≤ n, the CDM controller polynomial A(s) and
B(s) of structure shown in Fig 1are represented by
A (s) = iq
0i i
p
0i
i
i SkB(s)andsl ∑∑ ==
= (7)
The controller to be realized for the condition p ≥q must be satisfied. For a better performance the
degree of controller polynomial chosen is important. The controller polynomial for FOPTD process
with numerator Taylor’s approximation is chosen as
A(s) = s (8a)
B(s) = k1s +k0 (8b)
The determination of the coefficient of the controller polynomial in CDM pole-placement method
is used. The feedback controller is chosen by pole-placement technique then a feed forward
controller is determined so as to match the closed loop system steady-state gain . Hence, a
polynomial depending on the parameters ki and li is obtained. Then, a target characteristic
polynomial Ptarget(s) is obtained by placing the design parameters into Eqn 5. Equating these two
polynomials is obtained, which is known to be Diophantine equation.
A(s) D(s) + B(s) N(s) = Ptarget(s) (9)
Solve these equations the controller coefficient for polynomial A(s) and B(s) is found .The
numerator polynomial F(s) which is defined as pre-filter is chosen to be
F(s) = P(s)/N(s) |S=0 = P (0)/N (0) (10)
4. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
14
This way, the value of the error that may occur in the steady-state response of the closed loop
system is reduced to zero. Thus, F(s) is computed by
F(s) = P(s)/N(s) | S=0 = 1/kp (11)
4. CDM-PI CONTROLLER
The transfer function model of conventional PI controller is
Gc(s) = kc (1+ ) (12)
The controller gain kc and integral time Ti are relevant with polynomial coefficient as k1=kc and
k0=kc/Ti . By applying the CDM, the values of k1 and K0 can be calculated as follows:
1) To find the equivalent time constant
2) The stability index γ1 = 3, γ2 = 4.5 are used.
3) From the Eqn.(2), derive the characteristic polynomial with the PI controller stated in Eqn (12)
and equates to the characteristic polynomial obtained from Eqn(14). Then the parameters k1and K0
of the PI controller are obtained.
4) Chose the pre-filter B(s) = K0 and Gf(s) is feed forward controller
Gf (s) =
1siT
1
1s1k
0k
B(s)
F(s)
+
=
+
= (13)
Fig.2: Equivalent block diagram of CDM
5. THREE TANK PROCESS
The three-tank process taken for study [6] is shown in Fig 2. The controlled variables are the level
of the tank1 (h1) and level of the tank3 (h3)and Manipulated variables are in flow of tank1 (fin1)
and in flow of tank3 (fin3). The steady state operating data of the Three-tank system is given in
Table1. The material balance equation for the above three-tank system is given by
h2)2g(h1
s1
Az1
s1
fin1
dt
dh1
−−= (14)
h3)2g(h2
s2
Az3
h2)2g(h1
s2
AZ1
dt
dh2
−−+= (15)
5. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
15
2gh3
s3
Az2
h3)2g(h2
s3
Az3
s3
fin3
dt
dh3
+−+= (16)
Fig.3: Schematic diagram of three tank process
6. SIMULATION RESULTS AND DISCUSSION
In this work, the coefficient diagram method based control system is considered for the three tank
system under nominal operating conditions. The main objective of this process is to control the
level of Tank1 and Tank3. The coefficient diagram method is designed based on the thorough
knowledge of the three tank process. Also the PI controller parameters for the interacting three tank
process are obtained by utilizing direct synthesis method. The controller parameters of three tank
system are obtained by using direct synthesis method for the closed loop system. The controller
settings for loop1 Kc1=1.24137, Ti1=1336.5 and for loop2 Kc2=1.4589, Ti2=1315.5.The multi
loop CDMPI controller is obtained with time constant =10 and found to be Kc1=2.1720,
Ti1=0.111and timeconstantτ=15 Kc2=4.1284 Ti2=0.1113 for loop 1 and loop2 respectively.
The open loop response of the process is shown in Fig.4.The closed loop response of the three tank
process for a set point change in tank1 from its operating value of 0.7m to 1m is shown in Fig.5 and
its corresponding effect of interaction in tank3 .Fig. 6 shows the closed loop response of tank3 for
a set point change of 0.3 m to1.0 from its operating value and its corresponding effect of interaction
in tank1 and their values are tabulated in Table 2. With same operating conditions, a simulations
runs are carried out for direct synthesis based three tank processes for comparative study. The
simulated servo responses are stored in Fig .7 and Fig 8. The performance indices are calculated in
terms of settling time, Integral Square Error (ISE) and Integral Absolute Error (IAE) and values are
Table.1 Steady state operating parameters of three tank process
h1, h2, h3 in m 0.7,0.5,0.3
fin1 and fin3 in ml/sec 100
Outflow coefficient
(Az1, Az2, Az3)
2.251e-5,3.057e-5
,2.307e-5
Area of tank (S1-S3)in m2
0.0154
Acceleration due to gravity in
m/sec2 9.81
6. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
16
charted in Table 2. From the table it is observed that intelligent fuzzy control system gives
satisfactory performance than the PI controller. The servo and regulatory responses are plotted in
Fig .9 to 12.The servo tracking and regulatory responses are plotted in Fig. 13 to 16. The
performances of these controllers are evaluated and tabulated in Table 6. From the table, it is
clearly indicates that the control augmented the control system is considerably reduced the effect of
load disturbance in the process variable compared to the PI controller.
Fig 4. Open loop Response of the three tank process
Fig5. Closed loop response of three tank process with set Point change
in Tank-1(Conventional PI-Controller)
Fig6. Closed loop response of three tank process With set point change
inTank-3(Conventional PI-Controller)
7. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
17
Fig7.Closed loop response of three tank process with set point change
in Tank-1(CDM-PI) Controller
Fig8. Closed loop response of three tank process With set point change
in tank-3(CDM-PI) Controller
Fig9. Servo tracking response of three tank process
in Tank-1(Conventional PI-Controller)
Fig10.Servo tracking response of three tank process
in Tank-3(Conventional PI-Controller)
8. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
18
Fig11. Servo tracking response of three tank process
in Tank-1(CDM-PI) Controller
Fig12 .Servo tracking response of three tank process
in Tank-3(CDM-PI) Controller
Fig13. Servo tracking and Regulatory response of three tank process
in Tank-1Conventional PI-Controller
Fig14. Servo tracking and Regulatory response of three tank process
inTank-3Conventional PI-Controller)
9. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
19
Fig15. Servo tracking and Regulatory response of three tank process in
Tank1 (CDM-PI) Controller
Fig16. Servo tracking and Regulatory response of three tank process in
Tank-3(CDM-PI) Controller
Table.2 Performance and evaluation of the controllers
Controller
scheme
Controller Parameters
LOOP-1 LOOP-2
ts ISE IAE ts ISE IAE
PI
Controller
2.5 0.01813 0.084 3 0.005283 0.0548
2.25 0.01961 0.108 3.3 0.007632 0.1822
2.75 0.1454 0.204 3.5 0.18759 0.439
2.70 1.4576 0.555 3.0 2.466 0.675
CDM-PI
Controller
0.9 0.001683 0.009099 0.7 0.0001612 0.0001627
0.8 0.002002 0.01281 0.65 0.0003276 0.004079
0.75 0.003767 0.03467 0.8 0.003426 0.004567
0.95 0.7890 0.05678 0.9 0.98675 0.06326
10. International Journal on Soft Computing (IJSC) Vol. 5, No. 2, May 2014
20
7. CONCLUSION
In this work the Multiloop CDM-PI controller is designed for three tank process and compared with
the conventional –PI controller designed by Synthesis tuning method through simulation. The ts,
ISE and IAE are taken as performance indices. The superiority of the CDM-PI control is analyzed
and clearly shows that more potential advantages of using CDM-PI control for a three tank process.
The control technique has a good set point tracking without any offset with better settling time. The
comparison of these above two controllers clearly shows that CDM-PI controller is superior
resulting in smoother controller output without oscillations which would like increase the actuator
life.
8. REFERENCES
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