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This paper proposes a control strategy based on artificial neural networks (ANNs) for a positioning system with a flexible transmission element, taking into account Coulomb friction for both motor and load, and using a variable learning rate for adaptation to parameter changes and accelerate convergence. A control structure consists of a feedforward ANN that approximates the manipulator's inverse...
This paper proposed a new intelligent controller for a spin missile with uncertainty and unknown parameter. The spin missile controller expression with undetermined parameters can be acquired by using adaptive backstepping design idea, and the controller parameters are optimized online by using genetic algorithm. By using this new method proposed in this paper, not only the stability of the spin missile...
This note deals with the absolute stability of Lur'e control systems with time-varying delay. An augmented Lyapunov functional is introduced to establish some new stability criteria. First, for the nominal system, we develop some new stability conditions, by considering the additional useful terms and introducing some free-weighting matrices. In the proof of our results, we introduce some useful lemmas...
In this paper, a design methodology for enhancing the stability of humanoid robots is presented. Fuzzy Q-learning (FQL) is applied to improve the zero moment point (ZMP) performance by intelligent control of the trunk of a humanoid robot. With the fuzzy evaluation signal and the neural networks of FQL, biped robots are dynamically balanced in situations of time-varying terrains. Compared with scale...
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