A neural network-based tracking control system

An application of the backpropagation neural network to the tracking control of industrial drive systems is presented. The merits of the approach lie in the simplicity of the scheme and its practicality for real-time control. Feedback error trajectories, rather than desired and/or actual trajectories, are employed as inputs to the neural network tracking controller. It can follow any arbitrarily prescribed trajectory even when the desired trajectory is changed to that not used in the training. Simulation was performed to demonstrate the feasibility and effectiveness of the proposed scheme. >

[1]  Richard S. Sutton,et al.  Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  Michio Sugeno,et al.  An introductory survey of fuzzy control , 1985, Inf. Sci..

[3]  Jean-Jacques E. Slotine,et al.  Robust trajectory control of underwater vehicles , 1985 .

[4]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[5]  Susumu Tadakuma,et al.  Microprocessor-Based Adjustable-Speed DC Motor Drives Using Model Reference Adaptive Control , 1987, IEEE Transactions on Industry Applications.

[6]  Hideki Hashimoto,et al.  A Microprocessor-Based Robot Manipulator Control with Sliding Mode , 1987, IEEE Transactions on Industrial Electronics.

[7]  A. Guez,et al.  A trainable neuromorphic controller , 1988 .

[8]  A. Sideris,et al.  A multilayered neural network controller , 1988, IEEE Control Systems Magazine.

[9]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..

[10]  M. A. El-Sharkawi,et al.  Tracking Control Technique for Induction Motors , 1989, IEEE Power Engineering Review.

[11]  M. El-Sharkawi,et al.  Variable Structure Tracking of DC Motor for High Performance Applications , 1989, IEEE Power Engineering Review.

[12]  Takayuki Yamada,et al.  An extension of neural network direct controller , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[13]  L.G. Kraft,et al.  A comparison between CMAC neural network control and two traditional adaptive control systems , 1990, IEEE Control Systems Magazine.

[14]  T. A. Lasky,et al.  Robust independent joint controller design for industrial robot manipulators , 1991 .

[15]  Yoshiki Uchikawa,et al.  Trajectory control of robotic manipulators using neural networks , 1991 .