Structure Analysis And Control For Complex Systems Based On Fuzzy Logic System

It is very important to research the control of complex systems for control engineering and theory. This paper proposes a new method based on the fuzzy logical system to deal with the robust control problems of complex systems, which combine the classical Lyapunov method and computer simulation way to study the robust control of complex systems with nonlinear uncertainties, that involve the state feedback stabilization, output feedback stabilization, state observer design and output tracking control problem.The main contributions of this paper are as follows:· By employing the fuzzy logical system which can approximate any nonlinear continuous function with arbitrary, we synthesize the state feedback robust stabilization controller, the output feedback robust stabilization controller, the nonlinear state observer and the decentralized output tracking controller for a class of complex systems with interconnections, which can ensure the states, state errors, tracking errors and all estimate parameter errors to be uniformly ultimately bounded (UUB) in all control layouts.· Both centralized and decentralized robust stabilization controller via states feedback are constructed for a class of general complex systems with interconnection uncertainties. And then by means of the same way, we synthesize the holographic robust controller for a class of complex systems with similar structure.· The method proposed has the advantage of those achievements listed in references, which require some so strict hypotheses that limit its application in engineering. Under some simple conditions, this paper uses sample data of states and the norm of uncertainties of system to be controlled to build fuzzy logical system to control complex systems. It makes the method more suitable for engineering use.· As we known, handling the uncertainties is a critical problem in complex systems control layout, we take a method of centralizing the uncertainties of complex systems to be controlled firstly and then constructing fuzzy logical system to approximate so that the new structural complexities resulted by applying fuzzy logicalsystem are controlled.· Adaptive engines for estimate parameters are applied and estimation accuracy is derived from mathematics inference in all control devise, it overcomes the defects that only simulation can be provided but no mathematics inference in some study results.· The computer simulation models for all control layout work are built up, which described by vivid diagrams in simulation part of every chapter, make the methods more easily use for engineers. It verifies the validity of the method and also shows the way of using this method in practical engineering.· Computer simulating programs developed can be transplanted and reused very easily in other similar problems, it is also helpful to further study the robust control of complex systems.