Chapter 1Elements of Mechatronic Systems1.1 IntroductionThe word mechatronics is composed of “mecha” from mechanism and th...
4                                                      1 Elements of Mechatronic SystemsFig. 1.1 Various elements of      ...
1.4 Input Signal Conditioning and Interfacing                                       51.4 Input Signal Conditioning and Int...
6                                                    1 Elements of Mechatronic Systems1.6 Output Signal Conditioning and I...
1.10 Autonomous Supervisory Control                                                  7                                    ...
8                                                     1 Elements of Mechatronic Systemsability to synthesize discrete piec...
1.12 Knowledgebase                                                                   9to frequently asked questions. Typic...
10                                                      1 Elements of Mechatronic Systems   The knowledgebase consists of ...
1.16 Fault Tolerance                                                                 111.16 Fault ToleranceFault-tolerant ...
12                                                     1 Elements of Mechatronic Systems1. User places an original in a lo...
1.18 Why Mechatronics System Simulation?                                              131.18 Why Mechatronics System Simul...
14                                                        1 Elements of Mechatronic Systemsphysical product can be optimiz...
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Intelligent mechatronic systems

  1. 1. Chapter 1Elements of Mechatronic Systems1.1 IntroductionThe word mechatronics is composed of “mecha” from mechanism and the “tron-ics” from electronics. It is the synergistic integration of mechanical engineering,with electronics and intelligent computer control in the design and manufacturing ofindustrial products and processes. Mechatronics involves:• Implementing electronics control in a mechanical system.• Enhancing existing mechanical design with intelligent control.• Replacing mechanical component with an electronic solution. The growth of mechatronic systems has been fuelled by the growth in the con-stituent areas. Advancements in traditional disciplines has also fuelled the growthof mechatronics systems by providing technologies. For example, the invention ofthe microprocessor had effected a lot on the redesign of mechanical systems anddesign of new mechatronics systems. We can recall the spring-driven table clocks.These have been replaced by microprocessor-based table clocks. There are manyexamples of intelligent systems in all walks of life, including smart home appliancessuch as dishwashers, vacuum cleaners, microwaves, and wireless network-enableddevices. However it is the automobile market which has been the motivation forthe development of mechatronic systems. Before we move further let us see theprincipal mechatronic components. The mechatronic components essentially consistof actuators, sensors, input signal conditioning and interfacing unit, digital controlarchitecture, output signal conditioning and interfacing, and displays. The signalflows among these elements is shown in Fig. 1.1. In the following sections, wediscuss about some of these mechatronic components and the issues involved inmechatronic system design and implementation.R. Merzouki et al., Intelligent Mechatronic Systems, 3DOI: 10.1007/978-1-4471-4628-5_1, © Springer-Verlag London 2013
  2. 2. 4 1 Elements of Mechatronic SystemsFig. 1.1 Various elements of Input signala mechatronic system Actuators Sensors conditioning and interfacing Output signal conditioning and Digital control interfacing architecture Displays1.2 ActuatorsActuators are mechanical devices for moving or controlling something. These areresponsible for transformation of output of a microprocessor into a controlling actionon machine or device. For example electrical outputs of controller transforms intolinear motion of a load or say electrical output of controller transforms into an actionwhich controls the amount of liquid passing along a pipe. The actuators can beclassified as• Electric Motors and Drives: These actuators transform electrical energy into mechanical energy. There are various types of electric actuators, such as – DC Motors – AC Motors – Linear Motors – Stepper Motors• Hydraulic Drives• Pneumatic Drives• Internal Combustion hybrids• Actuators of the future.1.3 SensorsSensors are elements of a mechatronic system which produce signals relating to thequantities being measured. Let us take an example of electrical resistance thermome-ter. The quantity being measured here is temperature. The sensor transforms it intochange of resistance of the sensor material. Examples of sensors include switches,potentiometers, thermocouples, strain gauges, digital encoders, and accelerometersand micro-electromechanical systems. A transducer is an element that when subjected to some physical change experi-ences a related change. Thus we can say that sensors are transducers.
  3. 3. 1.4 Input Signal Conditioning and Interfacing 51.4 Input Signal Conditioning and InterfacingAn important question is why do we require signal conditioning? The simple answeris because we want to feed the sensor data to a microprocessor. The signal condi-tioning process provides protection; it ensures that we get the signal to be of righttype and of right level. The signal conditioning process also eliminates or reducesthe noise. Sometimes we require signal manipulation for making it linear functionof some variable. Interfacing is needed because we want to connect peripheral devices such assensors, keyboards, actuators, etc., to microprocessor. Due to different signal formsand levels they cannot be directly connected. We can list some basic interface requirements as1. Electrical buffering/isolation—when peripherals operate at a different current or voltage than the microprocessor bus system or ground references are different.2. Timing control—when the data transfer rates of the peripheral and the micro- processor are different, i.e., interfacing a microprocessor to a slower peripheral. This can be achieved by using special lines between the microprocessor and the peripheral to control the transfer of data. Such lines are called handshake lines and the process is called handshaking.3. Code conversion—when codes used by peripherals are different to that used by microprocessor.4. Changing the number of lines—when microprocessor uses different bits such as 4, 8, or 16 bits. This determines the number of lines in microprocessor data bus. Note that peripherals may have different number of lines.5. Serial to parallel and vice versa data transfer—a 8 bit microprocessor manipulates 8 bits of data at same time. This can be done by parallel data transfer where all data are send simultaneously whereas in serial data transfer signals are sent one by one.6. Conversion from analog to digital and vice versa—when both are used together. The examples of input signal conditioning and interfacing are discrete circuits,analog to digital converters, digital to analog converters, filters, and amplifiers.1.5 Digital Control ArchitectureMicroprocessor system has three parts (i) Central Processing Unit (CPU), (ii) Inputand Output interfaces, and (iii) Memory. Microprocessor having memory, input and output arrangements all on same chipare microcontrollers. Digital control architecture may include components such asdifferent logic circuits, microcontrollers, control algorithms, program logic con-trollers, etc.
  4. 4. 6 1 Elements of Mechatronic Systems1.6 Output Signal Conditioning and InterfacingThe components of this system may include digital to analog, analog to digital con-verter, amplifiers, power transistors, power op amps, pulse width modulation, etc.1.7 DisplaysA display provides visual feedbacks to user based on which he/she can take somedecisions. The examples of displays include LED’s, digital display, cathode ray tubes,liquid crystal displays, etc.1.8 Intelligent SystemWe can define an intelligent system as a system that learns during its existence. Orwe can say that the system senses its environment with the help of sensors; it learns,what action for each situation it should take so that it achieves its objectives. Thus,an intelligent system can be defined only if the system exists along with surrounding,with which it interacts. The system must be able to receive communications fromthe surrounding. This communication is for transmitting information. An intelligentsystem must have an objective and should have ability to check whether the lastaction which it performed has been able to move it closer to its objective or not.1.9 Reconfigurable SystemsA process may continue to operate as long as all of its critical faults can be detectedand it remains observable and controllable. A reconfigurable system is one which canaccommodate the faults using the redundancies present in the system. The redundan-cies are usually in the form of additional actuators and sensors present in the systemthan the minimum required. The fault indicators, fault signature analysis and the fault isolation (root causeanalysis) schemes must be modified every time a system is reconfigured. The func-tional services offered by the components are organized into coherent subsets calledOperating Modes (OM), where each OM is associated to a functional model. Automa-tion specifies the conditions to change from one OM to another. Theoretically, aprocess can operate normally, as long as at least one device is available for eachbasic function. When a device fails, the branch associated with it is removed and thesystem is reconfigured using the next device, according to a defined hierarchy.
  5. 5. 1.10 Autonomous Supervisory Control 7 Signal Digital control conditioning Actuators architecture and interfacing Operator Plant Signal Displays conditioning Sensors and interfacingFig. 1.2 Schematic representation of supervisory control Signal Digital control conditioning Actuators architecture and interfacing Operator Plant Signal Displays conditioning Sensors and interfacingFig. 1.3 Schematic representation of autonomous supervisory control1.10 Autonomous Supervisory ControlThe supervisory control is derived from the supervisor’s control of the subordinatestaff in a manufacturing plant. The supervisory control in mechatronic system meansthat provision for human operator intervention in a control process exists. The inter-vention may be in the form of person programming intermittently and receiving datafrom a computer which is connected through various sensors in a controlled process. The controlled process can be the trajectory following action to be carried by tipof a manipulator. In case of autonomous supervisory control, human intervention isnot present. The schematic representation of supervisory control and autonomoussupervisory control are shown in Figs. 1.2 and 1.3, respectively.1.11 Artificial IntelligenceHumans demonstrate intelligence by communicating effectively and by learning.Artificial intelligence (AI) is the field of study for simulation of human behavior andcognitive process on a computer. It is the study of the nature of the whole space ofintelligent minds. AI takes help of computational techniques for performing job thatrequires intelligence when performed by humans. The issue of AI involves knowl-edge representation, search, perception, and inference. An intelligent machine hasbuilt-in capability to reason. They perform functions that require intelligence whenperformed by people. Intelligent system can be constructed from explicit, declarativeknowledgebases, operated by general, formal reasoning mechanism. They have the
  6. 6. 8 1 Elements of Mechatronic Systemsability to synthesize discrete pieces of information in creating a new understandingof any problem and its possible solution. Some important AI terminologies are• Perception: It is the collection of information using sensors by the intelligent system and organization of gathered information so that decisions can be taken.• Reasoning: It is the process of going from what is known to what is unknown. The reasoning can be either deterministic or nondeterministic. Deterministic reasoning uses if-then rules whereas nondeterministic reasoning makes predictions based on probability.• Learning: It is the adoption of the environment based on experience by the intel- ligent system. Important AI systems are (i) Expert system (ii) Fuzzy system (iii) Artificial neural network (iv) Genetic algorithm (v) Evolutionary programming (vi) Ant colony intelligent system(vii) Particle swam intelligent system.1.12 KnowledgebaseA knowledgebase is a special kind of database for knowledge management [1],providing the means for the computerized collection, organization, and retrieval ofknowledge. It aims to provide right information at right moment. Knowledgebasesare categorized into two major types: Machine-readable knowledgebases store knowledge in a computer-readable form,usually for the purpose of having automated deductive reasoning applied to them.They contain a set of data, often in the form of rules that describe the knowledge ina logically consistent manner. An ontology can define the structure of stored data—what types of entities are recorded and what their relationships are. Logical operators,such as And (conjunction), Or (disjunction), material implication, and negation maybe used to build it up from simpler pieces of information. Consequently, classicaldeduction can be used to reason about the knowledge in the knowledgebase. Somemachine-readable knowledgebases are used with artificial intelligence, for exampleas part of an expert system that focuses on a domain-like prescription drugs orcustoms law. Human-readable knowledgebases are designed to allow people to retrieve and usethe knowledge they contain. They are commonly used to complement a help deskor for sharing information among employees within an organization. They mightstore troubleshooting information, articles, white papers, user manuals, or answers
  7. 7. 1.12 Knowledgebase 9to frequently asked questions. Typically, a search engine is used to locate informationin the system, or users may browse through a classification scheme. Any smart control system includes a knowledgebase [3]. Information on themechatronic systems that include the equipment being controlled, as well as thecontrollable process, may contain errors and inconsistencies and may be incom-plete. In other words, knowledge regarding mechatronic systems is characterizedby indeterminacy. In constructing a knowledgebase, the main criterion is minimiza-tion of the following components of the indeterminacy: incompleteness, inadequacy(errors), and inconsistency. Another goal is to minimize the redundancy of the data inthe knowledgebase. Accordingly, a method of formalized representation of knowl-edge regarding the mechatronic system must not only include representation of therelevant knowledge but also determination and modeling of the indeterminacies inthe knowledge. Thus, mechatronic system modeling may help in enriching the exist-ing knowledgebase of the mechatronic system. Information from the knowledgebasemay be used in the synthesis, control, prediction, and diagnostic systems for mecha-tronic systems. It also helps in creating systems to support design and technologicaldecision making, and in the operation of mechatronic systems. The integration of mechatronic systems can be performed by the components [2](hardware-integration) and by information processing (software-integration). Theinformation processing consists of low-level and high-level feedback control, super-vision and diagnosis, and general process management. Special signal processing,model-based, and adaptive methods are applied. With the aid of a knowledgebaseand inference mechanisms mechatronic systems with increasing intelligence will bedeveloped. The integration by information processing (software integration) is mostly basedon advanced control functions. Besides a basic feedforward and feedback controlan additional influence may take place through the process knowledge and corre-sponding online information processing. This means a processing of available sig-nals in higher levels. This includes the solution of tasks such as supervision withfault diagnosis, optimization and general process management. The respective prob-lem solutions result in real-time algorithms which must be adapted to the mechani-cal process properties, for example expressed by mathematical models in the formof static characteristics, differential equations, etc. Therefore, a knowledgebase isrequired for organizing the methods for design and information gaining, processmodels, and performance criteria. By this way the mechanical parts are governed invarious ways through higher level information processing with intelligent properties,possibly including learning, thus forming an integration by process adapted software. The knowledgebase contains quantitative and qualitative knowledge. The quan-titative part operates with analytic (mathematical) process models, parameter andstate estimation methods, analytic design methods (e.g., for control and fault detec-tion), and quantitative optimization methods. Similar modules hold for the qualitativeknowledge, e.g., in form of rules (fuzzy and soft computing). Further knowledge isthe past history in the memory and the possibility to predict the behavior. Finally,tasks or schedules may be included.
  8. 8. 10 1 Elements of Mechatronic Systems The knowledgebase consists of mathematical process models, parameter estima-tion, and controller design methods and control performance criteria. The feedbackcontrol is organized in lower level and higher level controllers, a reference valuegeneration module and controller parameter adaptation. With this structure the maincontrol functions of mechatronic systems can be organized.1.13 Decision Support SystemA decision support system (DSS) for a mechatronic system is a computer-basedinformation system that supports organizational decision-making activities. DSSsmay serve the operations, and planning levels of a microprocessor and help to makedecisions, which may be rapidly changing and not easily specified in advance. DSSsinclude knowledgebased systems. A properly designed DSS for a mechatronic systemmay be software-based system intended to help compile useful information from acombination of raw data, or system models to identify and solve problems and makedecisions. Let us take an example. Say a walking robot is moving in a straight linebut if some obstruction comes in path of the walking robot then decision supportsystem must be able to gather the data from sensor such as infrared and accordinglyactuate the motors so that the path of the robot is changed and obstruction is notencountered.1.14 DiagnosisDiagnosis in a mechatronic system refers to identification of nature and cause forfailures of mechatronic components, say actuators, sensors, and microcontrollers.1.15 Fault, Failure, and SafetyModern technological systems rely on sophisticated control systems to meet increasedperformance and safety requirements. Over the last three decades, the growingdemand for identification of fault, resulting failure and safety concerns from suchfailure has attracted lot of research in the area. Apart from safety, reliability, maintain-ability, and survivability in technical systems has drawn significant research in FaultDetection and Diagnosis (FDD). Such efforts have led to the development of manyFDD techniques. On the other hand, research on reconfigurable fault-tolerant con-trol systems has increased progressively since the initial research on restructurablecontrol and self-repairing flight control systems began in the early 1980s.
  9. 9. 1.16 Fault Tolerance 111.16 Fault ToleranceFault-tolerant control has proved to be a powerful tool for improving the safety inmechatronic system. Modern technological systems rely on sophisticated controlsystems to meet increased performance and safety requirements. A conventionalfeedback control design for a complex system may result in an unsatisfactory per-formance, or even instability, in the event of malfunctions in actuators, sensors orother system components. To overcome such weaknesses, new approaches to con-trol system design have been developed in order to tolerate component malfunctionswhile maintaining desirable stability and performance properties. This is particu-larly important for safety-critical systems, such as aircraft, spacecraft, nuclear powerplants, and specially automobile and mechatronics systems. In such systems, the con-sequences of a minor fault in a system component can be catastrophic. Therefore,the demand on reliability, safety and fault tolerance is generally high. It is necessaryto design control systems which are capable of tolerating potential faults in thesesystems in order to improve the reliability and availability while providing a desir-able performance. These types of control systems are often known as fault-tolerantcontrol systems (FTCS). More precisely, FTCS are control systems which possessthe ability to accommodate component failures automatically. They are capable ofmaintaining overall system stability and acceptable performance in the event of suchfailures. Fault-Tolerant Control (FTC) relates to recovery from fault such that the systemis controlled under actual constraints without replacing part(s) of the faulty system.FTC approaches can be classified into two categories: passive approach (e.g., robustcontrol) and active approach (e.g., adaptive control). In active FTC, plant faultsare diagnosed and estimated and subsequently the controller is redesigned for faultaccommodation. Historically, from the point of view of practical application, a signif-icant amount of research on fault-tolerant control systems was motivated by aircraftflight control system designs. The goal was to provide “self-repairing” capability inorder to ensure a safe landing in the event of severe faults in the aircraft. Increasedair traffic has necessitated the need for fault-tolerant flight control systems. Faulttolerance is no longer limited to high-end systems, and consumer products, such asautomobiles. It is increasingly dependent on microelectronic/mechatronic systems,on-board communication networks, and software, thus requiring new techniques forachieving fault tolerance.1.17 Examples of Mechatronic Systems1.17.1 A Copy MachineIt is an excellent example of mechatronic system. It has analog and digital circuits,sensors, actuators, and microprocessors. The working of copy machine can be statedas follows:
  10. 10. 12 1 Elements of Mechatronic Systems1. User places an original in a loading bin and pushes a button to start the process.2. The original is transported to the platen glass.3. A high-intensity light source scans the original and transfers the corresponding image as a charge distribution to a drum.4. Blank piece of paper is retrieved from loading cartridge, and image is transferred onto the paper with an electrostatic deposition of ink toner powder that is heated to bond to the paper.5. A sorting mechanism then delivers the copy to an appropriate bin. Now, let us see the mechatronic components in copy machine.1. Actuators: In a copy machine servomotor or stepper motor is used as actuator. The principal job of actuator here is to load and transport the paper, turn the drum, and index the drum.2. Sensors: Optical sensors and microswitches detect the presence or absence of paper, its proper positioning, and check whether or not door and latches are in proper position. Encoders are used to track motor rotation.3. Control: Analog circuits control the lamp, heater, and other power circuit. Digital circuit controls digital display, indicator lights, buttons, and switches, forming the user interface. Other digital circuits used include logic circuit and microprocessor that coordinates all the functions of the machine.1.17.2 Walking RobotA walking robot is another good example of mechatronic system. It has followingmechatronic components:1. Actuators: Servo motors or direct current (DC) motor or stepper motor can be used as an actuator to propel the legs and body.2. Sensors: A walking robot may have many sensors depending upon the level of intelligence required in it. Some of the sensors can be • Infrared (IR) sensor for obstruction detection. • Bumper sensor for obstruction detection. • Compass for orientation detection. • Accelerometer for tilt detection. • Ultrasonic sensor for range detection.3. Micro Controller: One can use any microcontroller such as PIC, ATMega for coordinating the activity of actuators and sensors.
  11. 11. 1.18 Why Mechatronics System Simulation? 131.18 Why Mechatronics System Simulation?Mechatronic system designs are complex by nature, and are becoming more complexday by day. As the number of system’s peripheral components grow to accommodateever increasing demands for functionality and performance from consumers, thesystem design must integrate analog and digital hardware, as well as the software thatcontrols them. As mechatronic system integrates different components its behavioris determined by interdependencies between different components. Therefore, anintegrated and interdisciplinary engineering approach is necessary. So, engineersmust be assisted by tools which allow a systems analysis with respect to capabilities,capacities, and behavior without really constructing the system. This necessitates anappropriate modeling and simulation tool for mechatronic systems. A mechatronic system design requires an integrated modeling and simulationapproach where the whole system needs to be designed together to meet the desiredperformance specifications. The first level of modeling is called a conceptual model.The concept of a new product needs to be validated before additional resources areallocated to design and fabricate that product. Simulation is great tool for conceptvalidation. Once the conceptual model has been validated, the system level designgoes a step further where one determines the constraints on integration of componentsof the system. These constraints relate to the specifications for various componentssuch as the power requirements in the actuators (called actuator sizing) and sensorlimits. The next step in the design of an autonomous mechatronic system involves inte-gration of the control system model with the system model. Besides the selectionof control laws, the control system parameters have to be tuned in this stage so thatthe performance specifications are met with desired accuracy. The controller designalso involves selection and placement of sensors and actuators in the system. Notethat the actuator specifications cannot be determined if the system is not modelledwith its control laws; the actuator must be able to deliver the desired output dictatedby the controller. Moreover, if the sensor response time and feedback delay etc. arenot accounted for in the model then one might get a wrong design. Thus, the systemmodel needs integration of all components of the mechatronic system so that theactuator, sensor and system dynamics are all accounted for during the design stage. The detailed design of components is done after the system-level design and con-trol integration has been validated through simulation. Note that initial system leveldesign uses gross or approximate parameter values. The detailed design accountsfor further constraints such as the mechanical strength of components (load limit,fatigue life, etc.), geometric or assembly compatibilities, logistical issues (electricalor hydraulic power delivery lines) and packaging of electronic components (cool-ing system, heat exchangers, etc.). The detailed design gives more accurate estima-tion of system parameter values which have to be again used in the system levelmodel. An iterative process then converges to the final system design which will beused to fabricate the mechatronic system. The computerized modeling and simula-tion to evolve a product design called virtual prototyping. Like manufacturing of a
  12. 12. 14 1 Elements of Mechatronic Systemsphysical product can be optimized through rapid prototyping tools, the virtual pro-totyping through modeling and simulation offers a solution to quick, maintainable,optimized, and evolving product design. With availability of a virtual prototype of aproduct, it becomes easier to perform product redesign or enhancement.1.19 Future of MechatronicsWe can expect continued advancements in cost-effective actuators, sensors, micro-processors and microcontrollers development enabled by advancements inapplications of microelectromechanical systems (MEMS), adaptive control method-ologies, real-time programming methods, networking and wireless technologies, andsoftware tools for advanced system modeling, virtual prototyping, and testing. TheInternet when utilized in combination with wireless technology, may also lead to newmechatronic products. While developments in automobile technology provide vividexamples of mechatronics development, there are numerous examples of intelligentsystems in all walks of life. In area of medical science we can expect advances inrobot-assisted surgery, in vivo robots and implantable sensors and actuators. Otherareas that will benefit from mechatronic advances may include robotics, manufac-turing, space technology, underwater exploration, and transportation.References 1. Accessed 03 July 2012 2. R. Isermann, Mechatronic systems—a challenge for control engineering. in Proceedings of the American Control Conference, pp. 2617–2632, Albuquerque, New Mexico, June 1997 3. V.Ts. Zoriktuev, S.G. Goncharova, I.F. Mesyagutov, Representation and derivation of knowl- edge in the control systems of mechatronic machine-tool systems. Russ. Eng. Res. 28, 177–181 (2008)