Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Fuzzy Sets and Systems - Special issue on fuzzy neural control
Switching-type fuzzy controller design by genetic algorithms
Fuzzy Sets and Systems
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
A course in fuzzy systems and control
A course in fuzzy systems and control
Outline for a Logical Theory of Adaptive Systems
Journal of the ACM (JACM)
Genetic Algorithms for Machine Learning
Genetic Algorithms for Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Engineering and Computer Science
Genetic Algorithms in Engineering and Computer Science
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
IEEE Transactions on Fuzzy Systems
Hierarchical Fuzzy Control for C-Axis of CNC Turning Centers Using Genetic Algorithms
Journal of Intelligent and Robotic Systems
Stable Adaptive Fuzzy Control with TSK Fuzzy Friction Estimation for Linear Drive Systems
Journal of Intelligent and Robotic Systems
Recurrent Neuro-Fuzzy Modeling and Fuzzy MDPP Control for Flexible Servomechanisms
Journal of Intelligent and Robotic Systems
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When a mechatronic system is in slow speed motion, serious effect ofnonlinear friction plays a key role in its control design. In this paper, astable adaptive control for drive systems including transmission flexibilityand friction, based on the Lyapunov stability theory, is first proposed. Forease of design, the friction is fictitiously assumed as an unknowndisturbance in the derivation of the adaptive control law. Geneticalgorithms are then suggested for learning the structure and parameters ofthe fuzzy-enhancing strategy for the adaptive control to improvesystem’s transient performance and robustness with respect touncertainty. The integrated fuzzy-enhanced adaptive control is well testedvia computer simulations using the new complete dynamic friction modelrecently suggested by Canudas de Wit et al. for modeling the real frictionphenomena. Much lower critical velocity of a flexible drive system thatdetermines system’s low-speed performance bound can be obtained usingthe proposed hybrid control strategy.