Table Of ContentFRONTIERS 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 orders@intechopen.com
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
