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Process Modelling for Control concentrates on the modelling steps underlying a successful control design, answering questions like: How should I carry out the identification of my process to obtain a good model? How can I assess the quality of a model before to using it in control design? How can I ensure that a controller will stabilise a real process well enough before implementation? What is the most efficient method of order reduction to simplify the implementation of high-order controllers? System identification, model/controller validation and order reduction are studied in a common framework. Detailed worked examples, representative of various industrial applications, are given. This monograph uses mathematics convenient to researchers interested in real applications and to practising engineers interested in control theory. It enables control engineers to improve their methods and provides academics and graduate students with an all-round view of recent results in modelling for control.
Deadlock problems in flexible manufacturing systems (FMS) have received more and more attention in the last two decades. Petri nets are one of the more promising mathematical tools for tackling deadlocks in various resource allocation systems. In a system modeled with Petri nets, siphons are tied to the occurrence of deadlock states as a structural object. The book systematically introduces the novel theory of siphons, traps, and elementary siphons of Petri nets as well as the deadlock control strategies for FMS developed from it. Deadlock prevention methods are examined comparatively. The many FMS examples presented to demonstrate the concepts and results of this book range from the simple to the complex. Importantly, to inspire and motive the reader’s interest in further research, a number of interesting and open problems in this area are proposed at the end of each chapter.
This book focuses on those functionalities that can provide significant improvements in Proportional–integral–derivative (PID) performance in combination with parameter tuning. In particular, the choice of filter to make the controller proper, the use of a feedforward action and the selection of an anti-windup strategy are addressed. The book gives the reader new methods for improving the performance of the most widely applied form of control in industry.
Modelling and Control of Mini-Flying Machines is an exposition of models developed to assist in the motion control of various types of mini-aircraft: • Planar Vertical Take-off and Landing aircraft; • helicopters; • quadrotor mini-rotorcraft; • other fixed-wing aircraft; • blimps. For each of these it propounds: • detailed models derived from Euler-Lagrange methods; • appropriate nonlinear control strategies and convergence properties; • real-time experimental comparisons of the performance of control algorithms; • review of the principal sensors, on-board electronics, real-time architecture and communications systems for mini-flying machine control, including discussion of their performance; • detailed explanation of the use of the Kalman filter to flying machine localization. To researchers and students in nonlinear control and its applications Modelling and Control of Mini-Flying Machines provides valuable insights to the application of real-time nonlinear techniques in an always challenging area.
Passivity and associated stability conditions form one of the cornerstones in control theory and have begun to be applied in process control. In this book, passivity-based developments in all areas of control theory are addressed systematically for the first time. The emphasis is placed on real results that add insight. Case studies illustrate applications in all the main chapters. MATLAB® routines and a library of functions that implement the methods developed in the book can be downloaded from springer.com.
Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.
Control of Integral Processes with Dead Time provides a unified and coherent review of the various approaches devised for the control of integral processes, addressing the problem from different standpoints. In particular, the book treats the following topics: How to tune a PID controller and assess its performance; How to design a two-degree-of-freedom control scheme in order to deal with both the set-point following and load disturbance rejection tasks; How to modify the basic Smith predictor control scheme in order to cope with the presence of an integrator in the process; and how to address the presence of large process dead times. The methods are presented sequentially, highlighting the evolution of their rationale and implementation and thus clearly characterising them from both academic and industrial perspectives.
Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.
This book introduces a formalism for modeling complex and large-scale systems that merges Petri nets, differential equation systems, and object-oriented methods. It describes a method that starts from the requirements of a supervisory system and results in a proposal for such a system. The book also presents a validation procedure that allows verification of the formal properties of the hybrid model.
A recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of LMI-based convex optimization methods. Within this theoretical framework, control parameter determination can be designed and stability and robustness of closed-loop systems can be analyzed. This book describes the new framework of SDC system design and provides a comprehensive description of the modelling of controller design tools and their real-time implementation. It starts with a review of current research on SDC and moves on to some basic techniques for modelling and controller design of SDC systems. This is followed by a description of controller design for fixed-control-structure SDC systems, PDF control for general input- and output-represented systems, filtering designs, and fault detection and diagnosis (FDD) for SDC systems. Many new LMI techniques being developed for SDC systems are shown to have independent theoretical significance for robust control and FDD problems.