LMM in the State of Space The used variables are: x 1 , the rod position; x 2 , the rod velocity; x 3 , the rod acceleration; x 4 , the spool position; and x 5 , the spool velocity. (33.16) Thus the MM of the axis in state-space form becomes (33.17) where (33.18) Controller Design The characteristic polynomial is obtained from det[sI − (A C − b C r T )] = 0, where A C and b C are the controllable forms of the matrices A and b. If A ≠ A C , the use of transformation matrix T is advisable, in order to obtain A C and b C . Thus A C = TAT −1 , and b C = Tb. The matrix F = A C − b C r T has the form (33.19) The characteristic polynomial of the matrix F is (33.20) The poles chosen for the closed-loop determine the polynomial (33.21) The polynomials (33.20) and (33.21) are identical; therefore, the coefficients of matrix are If A = Ac, r T = x ˙ 1 x 2 t(), x ˙ 2 x 3 t(), x ˙ 4 x 5 t()=== x ˙ 3 w Z 2 x 2 t()– 2D Z w Z x 3 t() k Z w Z 2 x 4 t()+–= x ˙ 5 w V 2 x 4 t()– 2D V w V x 5 t() k V w V 2 ut()+–= x ˙ t() Ax t() bu t()+= y t() c T x t()= A 01 0 0 0 00 1 0 0 0 w Z 2 – 2D Z w Z – k Z 0 00 0 0 1 00 0 w V 2 – 2D V w V – , b 0 0 0 0 k V , c T 10000()=== F 0 0 . 0 −a 0 r 1 – 1 0 . 0 −a 1 r 2 – 0 0 . 1 −a n−1 r n – = s n a n−1 r n +()s n−1 … a 1 r 2 +()sa 0 r 1 +()++++ s n p n−1 s n−1 p n−2 s n−2 … p 1 sp 0 +++++ r R T r v p v−1 a v−1 , v– 1, … , n== r R T 0066_frame_Ch33.fm Page 11 Wednesday, January 9, 2002 8:00 PM ©2002 CRC Press LLC 34 Design Optimization of Mechatronic Systems 34.1 Introduction 34.2 Optimization Methods Principles of Optimization • Parametric Optimization • General Aspects of the Optimization Process • Types of Optimization Methods • Selection of a Suitable Optimization Method 34.3 Optimum Design of Induction Motor (IM) IM Design Introduction • Classical IM Design Evaluation • Description of a Solved Problem • Achieved Results 34.4 The Use of a Neuron Network for the Identification of the Parameters of a Mechanical Dynamic System Practical Application 34.1 Introduction Electromechanical systems form an integral part of mechanical and mechatronic systems. Their optimi- zation is a necessary condition for a product to be competitive. In engineering practice, a large number of optimization and identification problems exist that could not be solved without the use of computers [5]. The present level of technological development is characterized by increasing the performance of machines with the production costs kept at a satisfactory level. The demands on the reliability and safety of operation of the designed machines are also considerable. From practical experience we know that the dynamic properties of electromechanical systems have a considerable influence on their reliability and safety. On the other hand, the tendency to push the price of a machine down often leads to unfavorable dynamic properties that result in increased vibrations and noise during operation. Also, electrical properties dramatically deteriorate as the amount of active materials in a machine is reduced. The increased load leads to, among other things, excessive heat formation, which, in turn, has a negative effect on insulation, shortening the service life of a machine. 34.2 Optimization Methods Principles of Optimization The properties of electromechanical systems can be described mathematically using physical quantities. The degree of these properties is then described using mathematically formulated objective (preference) functions. Structural parameters ranging between limit values given as satisfying secondary conditions are the independent variables of these functions. The particular form of the functions depends on the type of machine and its mathematical description. The solutions of a mathematically formulated optimization Tomas Brezina Technical University of Brno Ctirad Kratochvil Technical University of Brno Cestmir Ondrusek Technical University of Brno ©2002 CRC Press LLC V Computers and Logic Systems 35 Introduction to Computers and Logic Systems Kevin Craig and Fred Stolfi Introduction: The Mechatronic Use of Computers • Mechatronics and Computer Modeling and Simulation • Mechatronics, Computers, and Measurement Systems • Mechatronics and the Real-Time Use of Computers • The Synergy of Mechatronics 36 Digital Logic Concepts and Combinational Logic Design George I. Cohn Introduction • Digital Information Representation • Number Systems • Number Representation • Arithmetic • Number Conversion from One Base to Another • Complements • Codes • Boolean Algebra • Boolean Functions • Switching Circuits • Expansion Forms • Realization • Timing Diagrams • Hazards • K -Map Formats • K -Maps and Minimization • Minimization with K -Maps • Quine–McCluskey Tabular Minimization 37 System Interfaces M.J. Tordon and J. Katupitiya Background • TIA/EIA Serial Interface Standards • IEEE 488—The General Purpose Interface Bus (GPIB) 38 Communications and Computer Networks Mohammad Ilyas A Brief History • Introduction • Computer Networks • Resource Allocation Techniques • Challenges and Issues • Summary and Conclusions 39 Fault Analysis in Mechatronic Systems Leila Notash and Thomas N. Moore Introduction • Tools Used for Failure/Reliability Analysis • Failure Analysis of Mechatronic Systems • Intelligent Fault Detection Techniques • Problems in Intelligent Fault Detection • Example Mechatronic System: Parallel Manipulators/Machine Tools • Concluding Remarks 40 Logic System Design M. K. Ramasubramanian Introduction to Digital Logic • Semiconductor Devices • Logic Gates • Logic Design • Logic Gate Technologies • Logic Gate Integrated Circuits • Programmable Logic Devices (PLD) • Mechatronics Application Example 41 Synchronous and Asynchronous Sequential Systems Sami A. Al-Arian Overview and Definitions • Synchronous Sequential System Synthesis • Asynchronous Sequential System Synthesis • Design of Controllers’ Circuits and Datapaths • Concluding Remarks ©2002 CRC Press LLC 35 Introduction to Computers and Logic Systems 35.1 Introduction: The Mechatronic Use of Computers 35.2 Mechatronics and Computer Modeling and Simulation 35.3 Mechatronics, Computers, and Measurement Systems 35.4 Mechatronics and the Real-Time Use of Computers 35.5 The Synergy of Mechatronics 35.1 Introduction: The Mechatronic Use of Computers Mechatronics is the synergistic combination of mechanical engineering, electronics, control systems, and computers. The key element in mechatronics is the integration of these areas through the design process. Synergism and integration in design set a mechatronic system apart from a traditional, multidisciplinary system. In a mechatronic system, computer, electronic, and control technology allow changes in design philosophy, which lead to better performance at lower cost: accuracy and speed from controls, efficiency and reliability from electronics, and functionality and flexibility from computers. Automotive engine- control systems are a good example. Here a multitude of sensors measure various temperatures, pressures, flow rates, rotary speeds, and chemical composition and send this information to a microcomputer. The computer integrates all this data with preprogrammed engine models and control laws and sends com- mands to various valves, actuators, fuel injectors, and ignition systems so as to manage the engine’s operation for an optimum combination of acceleration, fuel economy, and pollution emissions. In mechatronics, balance is paramount. The essential characteristic of a mechatronics engineer and the key to success in mechatronics design is a balance between two sets of skills: • Modeling (physical and mathematical), analysis (closed-form and numerical simulation), and control design (analog and digital) of dynamic physical systems • Experimental validation of models and analysis and understanding the key issues in hardware implementation of designs In mechatronic systems, computers play a variety of roles. First, computers are used to model, analyze, and simulate mechatronic systems and mechatronic system components and, as such, are useful for control design. Second, computers, as part of measurement systems, are used to measure the performance Kevin Craig Rennselear Polytechnic Institute Fred Stolfi Rennselear Polytechnic Institute ©2002 CRC Press LLC 36 Digital Logic Concepts and Combinational Logic Design 36.1 Introduction 36.2 Digital Information Representation 36.3 Number Systems 36.4 Number Representation 36.5 Arithmetic 36.6 Number Conversion from One Base to Another 36.7 Complements 36.8 Codes 36.9 Boolean Algebra 36.10 Boolean Functions 36.11 Switching Circuits 36.12 Expansion Forms 36.13 Realization 36.14 Timing Diagrams 36.15 Hazards 36.16 K -Map Formats 36.17 K -Maps and Minimization 36.18 Minimization with K -Maps 36.19 Quine–McCluskey Tabular Minimization 36.1 Introduction Digital logic deals with the representation, transmission, manipulation, and storage of digital information. A digital quantity has only certain discrete values in contrast with an analog quantity, which can have any value in an allowed continuum. The enormous advantage digital has over analog is its immunity to degradation by noise, if that noise does not exceed a tolerance threshold. 36.2 Digital Information Representation Information can be characterized as qualitative or quantitative. Quantitative information requires a number system for its representation. Qualitative does not. In either case, however, digitalized informa- tion is represented by a finite set of different characters. Each character is a discrete quanta of information. The set of characters used constitutes the alphabet. George I. Cohn California State University, Fullerton ©2002 CRC Press LLC 37 System Interfaces 37.1 Background Terminology and Definitions • Serial vs. Parallel • Bit Rate vs. Baud Rate • Synchronous vs. Asynchronous • Data Flow-Control • Handshaking • Communication Protocol • Error Handling • Simplex, Half-Duplex, Full-Duplex • Unbalanced vs. Balanced Transmission • Point-to-Point vs. Multi-Point • Serial Asynchronous Communications • The Universal Asynchronous Receiver Transmitter (UART) 37.2 TIA/EIA Serial Interface Standards RS-232 Serial Interface • Functional Description of Selected Interchange Circuits • RS-422 and RS-485 Interfaces 37.3 IEEE 488—The General Purpose Interface Bus (GPIB) Introduction • GPIB Hardware • Controllers, Talkers, and Listeners • Interface Management Lines • Handshake Lines • Data Lines DIO1-DIO8 (8 lines) • Addressing of GPIB Devices This chapter deals with asynchronous serial interfaces described by interface standards RS-232, RS-422, and RS-485 and with the general-purpose parallel interface bus described by IEEE-488 standard. The chapter also provides background information, terminology and parameters, which are important in the design of system interfaces for mechatronic systems. 37.1 Background Modern mechatronic systems comprise a number of subsystems, which rely heavily on digital data commu- nications. Different levels of complexity of these systems means that the requirement for data communications range from a simple communication between two devices to systems with a large number of subsystems, where each subsystem communicates directly or indirectly with other subsystems using a communication network. Depending on the proximity of subsystems, different requirements are placed on data communi- cation channels, the physical implementation of channels, and interfaces between these devices. Figure 37.1 shows a schematic diagram of a simple data communication system connecting two devices. A data source creates the data to be transmitted to the destination system and may convert the data into a specific form. The originating system usually does not create the data in a form suitable for transmission over transmission lines. This is left to the transmitter, which transforms the data into a signal suitable for transmission over a specific type of transmission line. The transmission line is generally implemented using electrical wiring but can involve a variety of physical medium including radio frequency, infrared, and sound signals. A transmission line provides a physical medium connecting the two systems. A receiver accepts the M.J. Tordon The University of New South Wales J. Katupitiya The University of New South Wales ©2002 CRC Press LLC . conditions are the independent variables of these functions. The particular form of the functions depends on the type of machine and its mathematical description. The solutions of a mathematically. the State of Space The used variables are: x 1 , the rod position; x 2 , the rod velocity; x 3 , the rod acceleration; x 4 , the spool position; and x 5 , the spool velocity. (33.16) Thus the. = A C − b C r T has the form (33.19) The characteristic polynomial of the matrix F is (33.20) The poles chosen for the closed-loop determine the polynomial (33.21) The polynomials (33.20)