Titlebook: Radial Basis Function (RBF) Neural Network Control for Mechanical Systems; Design, Analysis and Jinkun Liu Book 2013 Tsinghua University Pr

prick-test

莎草

聾子

Adaptive Robust RBF Control Based on Local Approximation,This chapter introduces three kinds of adaptive robust RBF controllers for robotic manipulators based on local approximation, including robust adaptive controller based on nominal model, adaptive controller based on local model approximation, and adaptive controller based on task space.

Exposition

轉(zhuǎn)折點(diǎn)

opprobrious

Adaptive RBF Observer Design and Sliding Mode Control,This chapter introduces a kind of adaptive observer with RBF neural network approximation. Using this observer, a speedless sliding mode controller is designed. Stability analysis of the observer and the closed control system are presented. Simulation examples for single-link manipulator are given.

完成

Jinkun LiuFundamental and thorough understanding in the neural network control system design.Typical adaptive RBF neural controllers design and stability analysis are given in a concise manner.Many engineering

OGLE

Chromatic

DEBT

Adaptive RBF Control Based on Global Approximation,ol law, adaptive neural network control law with sliding mode robust term, and adaptive neural network control law with HJI. The closed-loop system stability can be achieved based on the Lyapunov stability.