Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Theoretical aspects of fuzzy control
Theoretical aspects of fuzzy control
Nonlinear Control Systems II
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Stable fuzzy control system design with pole-placement constraint: an LMI approach
Computers in Industry
A methodology to design stable nonlinear fuzzy control systems
Fuzzy Sets and Systems
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy piecewise multilinear and piecewise linear systems as universal approximators in Sobolev norms
IEEE Transactions on Fuzzy Systems
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
Reduction of fuzzy rule base via singular value decomposition
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Sufficient Conditions to Impose Derivative Constraints on MISO Takagi–Sugeno Fuzzy Logic Systems
IEEE Transactions on Fuzzy Systems
A Descriptor System Approach to Fuzzy Control System Design via Fuzzy Lyapunov Functions
IEEE Transactions on Fuzzy Systems
Computation of Lyapunov functions for smooth nonlinear systems using convex optimization
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
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The price to be paid for the great dynamic richness of nonlinear systems is the lack of a unitary theory that allows control-system design to be tacked in a way that is parallel or analogous to that of linear systems. We propose a general methodology that uses fuzzy logic to systematically and formally synthesize nonlinear control systems, which are stable by design. Although this methodology is based on Lyapunov theory, it avoids searching for Lyapunov functions. This allows the synthesis procedure to be systematic as well as formal and, especially, independent of heuristics. Some examples of nonlinear control are solved in this paper, thus allowing assessment of the proposed methodology.