Indirect control of a class of nonlinear dynamic systems

Identification and control designs are considered using neural networks for a class of nonlinear partially known dynamic systems. Real-time implementation of two designs, a neural identifier and a proposed neural controller, using an experimental system, comparisons with two other neural networks as well as conventional schemes, and an implementation architecture are reported. The proposed control design facilitates incorporation of available knowledge about the structure of the system. The study also illustrates the inherent capability of neural networks to handle nonlinearities and perform control effectively for a real world system, based on minimal system information.

[1]  Kumpati S. Narendra,et al.  Disturbance rejection in nonlinear systems using neural networks , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[2]  Bernard Widrow,et al.  30 years of adaptive neural networks: perceptron, Madaline, and backpropagation , 1990, Proc. IEEE.

[3]  W. Thomas Miller,et al.  Sensor-based control of robotic manipulators using a general learning algorithm , 1987, IEEE J. Robotics Autom..

[4]  B. Widrow,et al.  Neural networks for self-learning control systems , 1990, IEEE Control Systems Magazine.

[5]  Anuradha M. Annaswamy,et al.  Stable Adaptive Systems , 1989 .

[6]  Michael Athans,et al.  Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics , 1985 .

[7]  S.S. Nair,et al.  Identification and control experiments using neural designs , 1994, IEEE Control Systems.

[8]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[9]  S. I. Mistry,et al.  Neural network designs for partially known dynamic systems , 1994 .

[10]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[11]  Snehasis Mukhopadhyay,et al.  Disturbance rejection in nonlinear systems using neural networks , 1993, IEEE Trans. Neural Networks.

[12]  M. Kawato,et al.  Hierarchical neural network model for voluntary movement with application to robotics , 1988, IEEE Control Systems Magazine.

[13]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

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

[15]  Kumpati S. Narendra,et al.  Gradient methods for the optimization of dynamical systems containing neural networks , 1991, IEEE Trans. Neural Networks.

[16]  Satish S. Nair,et al.  A New Neural Network Control Architecture for a Class of Nonlinear Dynamic Systems , 1993, 1993 American Control Conference.

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

[18]  Satish S. Nair,et al.  Experimental Implementation of Neural Control Architectures for a Class of Nonlinear Dynamic Systems , 1993, 1993 American Control Conference.