Hybrid Control Systems ( HCS ) are a kind of complex systems, which typically possess a hierarchical structure, characterized by continuous variable dynamics at the lowest level and logical decision-making at the highest. The final target of HCS research is to achieve the intelligent control for complex system. As one of the most important foundations for intelligent control . Soft-Computing ( SC ) is becoming more and more popular in the design and deployment of intelligent systems . The application of SC in HCS will be helpful to improve the intelligence of HCS and eventually lead to so-called hybrid intelligent systems. This thesis focuses on the application of fuzzy logic . neural network in the modeling, analysis and design of hierarchical HCS. The main works include : · First after summarizing the HCS and SC , we pointed out their methodological meanings. · Second. a kind of Fuzzy Dynamic System ( FDS ) model based on concept of general dynamic fuzzy system is proposed, and its formal description is presented. It is analyzed and explained by using atomic linguistic values, synthesized linguistic values, fuzzy rules and other fuzzy logic theories & methods. Its ability of utilizing hybrid qualitative and quantitative information is proved. Also its advantage over DEDS and the difference between them are presented. · Third . a new kind of Fuzzy Hybrid Control System ( FHCS ) model is proposed, and its general structure and formal description are presented. The modeling process is demonstrated through a case study. The difference between FHCS and common HCS that based on discrete states, and the advantage of FHCS over common HCS are discussed. The difference between FHCS and common Fuzzy Logic Control System ( FLCS ) and the advantage of FHCS over FLCS are presented, too. Moreover. the main application of FHCS are classified into 3 types. ~ Forth, we analyze the stability of FHCS in the continuos domain by using the common Lyapunov theory and Multiple Lyapunov Function( MLF ) theory, and 4 theorems for stability analysis are proposed. The continuity problem is discussed, and we prove that the continuous mappings from the measurement to control spaces are achieved in FHCS. and the validity of common FLCS is also explained from the view of FHCS . We also analyze the characteristics of the local control law and global control law in FHCS qualitatively at qualitative level. · Fifth, we proposed Direct Design Method ( DDM ) for the Class I application of FHCS and Indirect Design Method (IDM )for the Class II application of FHCS. DDM does not depend on the plant model, and the controller is obtained through online tuning A DDM based on FNN & Reinforcement Learning Algorithm is proposed. IDM does depend on the plant model, and can fully utilized the stability design methods for linear systems. 2 IDMs based on LQ method and pole placement method are presented. The validit
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