Fuzzy Logic and Intelligent Systems One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised the major obstacles in building a real intelligent machine involve dealing with random disturbances processing large amounts of imprecise data interacting with a dynamically changing environment and coping with uncertainty. Neural fuzzy techniques help one to solve many of these problems. Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic and their application in intelligent systems. In addition the balance between theoretical work and applications makes the book suitable for both researchers and engineers as well as for graduate students. Improvement of Fuzzy Control Methods Neural Networks and Fuzzy Basis Functions for Functional Approximation Ordering Fuzzy Real Quantities Fuzzy Logic Controllers for Aircraft Flight Control A Classical Controller: A Special Case of The Fuzzy Logic Controller Real Time Fuzzy Logic Controller for Balancing a Beam and Ball System Design of Fuzzy Controllers Based on Frequency And Transient Characteristics Fuzzy Inference Integrating 3D Measuring System with Adaptive Sensing Strategy Robot Hand Eye Coordination Based on Fuzzy Logic Using FPGA Technique for Design and Implementation of a fuzzy Inference System An Empirical Analysis of One Type of Direct Adaptive Fuzzy Control Automatic Optimal Design of Fuzzy Systems Based on Universal Approximation and Evolutionary Programming Intelligent Control Using Dynamic Neural Networks with Robotic Applications Camcorder Operation Judgement Using a Neural Computing Approach Model Reduction and Control of Multistage Flash (MSF) Desalinization Plants.