Intelligent Control: Principles, Techniques And ApplicationsThis book introduces the development process, structural theories and research areas of intelligent control; explains the knowledge representations, searching and reasoning mechanisms as the fundamental techniques of intelligent control; studies the theoretical principles and architectures of various intelligent control systems; analyzes the paradigms of representative applications of intelligent control; and discusses the research and development trends of the intelligent control.From the general point of view, this book possesses the following features: updated research results both in theory and application that reflect the latest advances in intelligent control; closed connection between theory and practice that enables readers to use the principles to their case studies and practical projects; and comprehensive materials that helps readers in understanding and learning. |
From inside the book
Results 1-5 of 17
Page 16
... entropy . Originally , the entropy is a measure to the total useless energy lost during the process of thermal transformation in thermos - mechanics . In information science , we define it as follows : Definition 1.9 . Entropy is the ...
... entropy . Originally , the entropy is a measure to the total useless energy lost during the process of thermal transformation in thermos - mechanics . In information science , we define it as follows : Definition 1.9 . Entropy is the ...
Page 17
Zixing Cai. could get a total entropy . The total entropy represents the total cost of actions . A criterion for building the intelligent control system would be to minimize its total entropy [ 71 ] . Entropy function is one of the ...
Zixing Cai. could get a total entropy . The total entropy represents the total cost of actions . A criterion for building the intelligent control system would be to minimize its total entropy [ 71 ] . Entropy function is one of the ...
Page 19
Zixing Cai. paradigms of the intelligent control systems : theory of hierarchical control , entropy methods for hierarchical controller design , principle of increasing precision with decreasing intelligence , design methods for expert ...
Zixing Cai. paradigms of the intelligent control systems : theory of hierarchical control , entropy methods for hierarchical controller design , principle of increasing precision with decreasing intelligence , design methods for expert ...
Page 88
You have reached your viewing limit for this book.
You have reached your viewing limit for this book.
Page 90
You have reached your viewing limit for this book.
You have reached your viewing limit for this book.
Contents
1 | |
CHAPTER 2 METHODOLOGIES OF KNOWLEDGE REPRESENTATION | 35 |
CHAPTER 3 GENERAL INFERENCE PRINCIPLES | 64 |
CHAPTER 4 HIERARCHICAL CONTROL SYSTEMS | 87 |
CHAPTER 5 EXPERT CONTROL SYSTEMS | 139 |
CHAPTER 6 FUZZY CONTROL SYSTEMS | 182 |
CHAPTER 7 NEUROCONTROL SYSTEMS | 242 |
CHAPTER 8 LEARNING CONTROL SYSTEM | 302 |
CHAPTER 9 INTELLIGENT CONTROL SYSTEMS IN APPLICATIONS | 353 |
CHAPTER 10 PROSPECTTVES OF INTELLGENT CONTROL | 432 |
BIOGRAPHY | 441 |
SUBJECT INDEX | 443 |
Other editions - View all
Common terms and phrases
activities adaptive control application architecture artificial intelligence automatic control Automation CMAC cognitive complex components control process control rules control strategy coordination level defined Definition defuzzification diagnosis dynamic entropy Equation error example expert control system expert system fault feedback fuzzy control system fuzzy logic fuzzy relation fuzzy sets fuzzy system genetic algorithm goal graph heuristic hierarchical intelligent control human hybrid IEEE IEEE Trans implemented inference engine input intelligent control system intelligent machines interface isoflurane iterative learning control knowledge base knowledge representation knowledge-based layer learning algorithm learning control system linguistic measurement membership function method module neural network neurocontrol neuron NN-based node nonlinear on-line operation optimal organization level parameters performance Petri net PID controller planning plant Proc procedure real-time reasoning repetitive events represent robotic systems semantic network sensors shown in Figure signal simulation solved structure symbol task techniques variables vector