Partial state reference model adaptive control of multivariable systems
Automatica (Journal of IFAC)
Outline for a Logical Theory of Adaptive Systems
Journal of the ACM (JACM)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Fuzzy system as parameter estimator of nonlinear dynamic functions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Decentralized adaptive fuzzy control of robot manipulators
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Control of a Bipedal Walking Robot Using a Fuzzy Precompensator
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Evolutionary neural networks and DNA computing algorithms for dual-axis motion control
Engineering Applications of Artificial Intelligence
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The results obtained by a rule-based proportional, integral, derivative (PID) precompensator controller applied to a two-joint manipulator are discussed. The end effector is made to follow a specified trajectory obtained from the inverse kinematics by an appropriate design of a fuzzy control law. The desired trajectory is determined by the values of the joint variables and the structural kinematics parameters of the manipulator. The performance of the PID controller is exploited here to build a fuzzy precompensator that will enhance the conventional PID and to obtain better performances and results. The fuzzy rule base of the precompensator designed is found by associating two evolutionary algorithms that search for the optimal solution.