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FRONTIERS IN ADVANCED CONTROL SYSTEMS Edited by Ginalber Luiz de Oliveira Serra Frontiers in Advanced Control Systems Edited by Ginalber Luiz de Oliveira Serra Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Sandra Bakic Technical Editor Teodora Smiljanic Cover Designer InTech Design Team First published July, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from [email protected] Frontiers in Advanced Control Systems, Edited by Ginalber Luiz de Oliveira Serra p. cm. ISBN 978-953-51-0677-7 Contents Preface IX Chapter 1 Highlighted Aspects from Black Box Fuzzy Modeling for Advanced Control Systems Design 1 Ginalber Luiz de Oliveira Serra Chapter 2 Online Adaptive Learning Solution of Multi-Agent Differential Graphical Games 29 Kyriakos G. Vamvoudakis and Frank L. Lewis Chapter 3 Neural and Genetic Control Approaches in Process Engineering 59 Javier Fernandez de Canete, Pablo del Saz-Orozco, Alfonso Garcia-Cerezo and Inmaculada Garcia-Moral Chapter 4 New Techniques for Optimizing the Norm of Robust Controllers of Polytopic Uncertain Linear Systems 75 L. F. S. Buzachero, E. Assunção, M. C. M. Teixeira and E. R. P. da Silva Chapter 5 On Control Design of Switched Affine Systems with Application to DC-DC Converters 101 E. I. Mainardi Júnior, M. C. M. Teixeira, R. Cardim, M. R. Moreira, E. Assunção and Victor L. Yoshimura Chapter 6 PID Controller Tuning Based on the Classification of Stable, Integrating and Unstable Processes in a Parameter Plane 117 Tomislav B. Šekara and Miroslav R. Mataušek Chapter 7 A Comparative Study Using Bio-Inspired Optimization Methods Applied to Controllers Tuning 143 Davi Leonardo de Souza, Fran Sérgio Lobato and Rubens Gedraite Chapter 8 Adaptive Coordinated Cooperative Control of Multi-Mobile Manipulators 163 Víctor H. Andaluz, Paulo Leica, Flavio Roberti, Marcos Toiberoand Ricardo Carelli VI Contents Chapter 9 Iterative Learning - MPC: An Alternative Strategy 191 Eduardo J. Adam and Alejandro H. González Chapter 10 FPGA Implementation of PID Controller for the Stabilization of a DC-DC “Buck” Converter 215 Eric William Zurita-Bustamante, Jesús Linares-Flores, Enrique Guzmán-Ramírez and Hebertt Sira-Ramírez Chapter 11 Model Predictive Control Relevant Identification 231 Rodrigo Alvite Romano, Alain Segundo Potts and Claudio Garcia Chapter 12 System Identification Using Orthonormal Basis Filter 253 Lemma D. Tufa and M. Ramasamy Preface The current control problems present natural trend of increasing its complexity due to performance criteria that is becoming more sophisticated. The necessity of practicers and engineers in dealing with complex dynamic systems has motivated the design of controllers, whose structures are based on multiobjective constraints, knowledge from expert, uncertainties, nonlinearities, parameters that vary with time, time delay conditions, multivariable systems, and others. The classic and modern control theories, characterized by input-output representation and state-space representation, respectively, have contributed for proposal of several control methodologies, taking into account the complexity of the dynamic system. Nowadays, the explosion of new technologies made the use of computational intelligence in the controller structure possible, considering the impacts of Neural Networks, Genetic Algorithms, Fuzzy systems, and others tools inspired in the human intelligence or evolutive behavior. The fusion of classical and modern control theories and the computational intelligence has also promoted new discoveries and important insights for proposal of new advanced control techniques in the context of robust control, adaptive control, optimal control, predictive control and intelligent control. These techniques have contributed to a successful implementations of controllers and obtained great attention from industry and academy to propose new theories and applications on advanced control systems. In recent years, the control theory has received significant attention from the academy and industry so that researchers still carry on making contribution to this emerging area. In this regard, there is a need to publish a book covering this technology. Although there have been many journal and conference articles in the literature, they often look fragmental and messy, and thus are not easy to follow up. In particular, a rookie who plans to do research in this field can not immediately keep pace to the evolution of these related research issues. This book, Frontiers in Advanced Control Systems, pretends to bring the state-of-art research results on advanced control from both the theoretical and practical perspectives. The fundamental and advanced research results as well as the contributions in terms of the technical evolution of control theory are of particular interest. Chapter one highlights some aspects on fuzzy model based advanced control systems. The interest in this brief discussion is motivated due to applicability of fuzzy systems X Preface to represent dynamic systems with complex characteristics such as nonlinearity, uncertainty, time delay, etc., so that controllers, designed based on such models, can ensure stability and robustness of the control system. Finally, experimental results of a case study on adaptive fuzzy model based control of a multivariable nonlinear pH process, commonly found in industrial environment, are presented. Chapter two brings together cooperative control, reinforcement learning, and game theory to solve multi-player differential games on communication graph topologies. The coupled Riccati equations are developed and stability and solution for Nash equilibrium are proven. A policy iteration algorithm for the solution of graphical games is proposed and its convergence is proven. A simulation example illustrates the effectiveness of the proposed algorithms in learning in real-time, and the solutions of graphical games. Chapter three presents an application of adaptive neural networks to the estimation of the product compositions in a binary methanol-water continuous distillation column from available temperature measurements. A software sensor is applied to train a neural network model so that a GA performs the search for the optimal dual control law applied to the distillation column. Experimental results of the proposed methodology show the performance of the designed neural network based control system for both set point tracking and disturbance rejection cases. Chapter four proposes new methods for optimizing the controller’s norm, considering different criteria of stability, as well as the inclusion of a decay rate in LMIs formulation. The 3-DOF helicopter practical application shows the advantage of the proposed method regarding implementation cost and required effort on the motors. These characteristics of optimality and robustness make the design methodology attractive from the standpoint of practical applications for systems subject to structural failure, guaranteeing robust stability and small oscillations in the occurrence of faults. Chapter five presents a study about the stability and control design for switched affine systems. A new theorem for designing switching affine control systems, is proposed. Finally, simulation results involving four types of converters namely Buck, Boost, Buck-Boost and Sepic illustrate the simplicity, quality and usefulness of the proposed methodology. Chapter six proposes a new method of model based PID controller tuning for a large class of processes (stable processes, processes having oscillatory dynamics, integrating and unstable processes), in a classification plane, to guarantee the desired performance/robustness tradeoff according to parameter plane. Experimental results show the advantage and efficiency of the proposed methodology for the PID control of a real thermal plant by using a look-up table of parameters. In chapter seven, Bio-inspired Optimization Methods (BiOM) are used for controllers tuning in chemical engineering problems. For this finality, three problems are studied, Preface XI with emphasis on a realistic application: the control design of heat exchangers on pilot scale. Experimental results show a comparative analysis with classical methods, in the sense of illustrating that the proposed methodology represents an interesting alternative for this purpose. In chapter eight, a novel method for centralized-decentralized coordinated cooperative control of multiple wheeled mobile manipulators, is proposed. In this strategy, the desired motions are specified as a function of cluster attributes, such as position, orientation, and geometry. These attributes guide the selection of a set of independent system state variables suitable for specification, control, and monitoring. The control is based on a virtual 3-dimensional structure, where the position control (or tracking control) is carried out considering the centroid of the upper side of a geometric structure (shaped as a prism) corresponding to a three-mobile manipulators formation. Simulation results show the good performance of proposed multi-layer control scheme. Chapter nine proposes a Model Predictive Control (MPC) strategy, formulated under a stabilizing control law assuming that this law (underlying input sequence) is present throughout the predictions. The MPC proposed is an Infinite Horizon MPC (IHMPC) that includes an underlying control sequence as a (deficient) reference candidate to be improved for the tracking control. Then, by solving on line a constrained optimization problem, the input sequence is corrected, and so the learning updating is performed. Chapter ten has its focus on the PID average output feedback controller, implemented in an FPGA, to stabilize the output voltage of a “buck" power converter around a desired constant output reference voltage. Experimental results show the effectiveness of the FPGA realization of the PID controller in the design of switched mode power supplies with efficiency greater than 95%. Chapter eleven aims at discussing parameter estimation techniques to generate suitable models for predictive controllers. Such discussion is based on the most noticeable approaches in Model Predictive Control (MPC) relevant identification literature. The first contribution to be emphasized is that these methods are described in a multivariable context. Furthermore, the comparisons performed between the presented techniques are pointed as another main contribution, since it provides insights into numerical issues and exactness of each parameter estimation approach for predictive control of multivariable plants. Chapter twelve presents a contribution for systems identification using Orthonormal Basis Filter (OBF). Considerations are made based on several characteristics that make them very promising for system identification and their application in predictive control scenario. This book can serve as a bridge between people who are working on the theoretical and practical research on control theory, and facilitate the proposal for development of