Output Feedback Neural Network Adaptive Robust Control With Application to Linear Motor Drive System

2006 ◽  
Vol 128 (2) ◽  
pp. 227 ◽  
Author(s):  
J. Q. Gong ◽  
Bin Yao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Output Feedback ◽  
Linear Motor ◽  
Adaptive Robust Control ◽  
Drive System ◽  
Motor Drive ◽  
Feedback Neural Network ◽  
Motor Drive System

Indirect Neural Network Adaptive Robust Control of Linear Motor Drive System

2002 ◽  
Author(s):  
J. Q. Gong ◽  
Bin Yao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Tracking Error ◽  
Linear Motor ◽  
Adaptive Robust Control ◽  
Operating Conditions ◽  
Tracking Performance ◽  
Motor Drive ◽  
Output Tracking ◽  
On Line

In this paper, an indirect neural network adaptive robust control (INNARC) scheme is developed for the precision motion control of linear motor drive systems. The proposed INNARC achieves not only good output tracking performance but also excellent identifications of unknown nonlinear forces in system for secondary purposes such as prognostics and machine health monitoring. Such dual objectives are accomplished through the complete separation of unknown nonlinearity estimation via neural networks and the design of baseline adaptive robust control (ARC) law for output tracking performance. Specifically, recurrent neural network (NN) structure with NN weights tuned on-line is employed to approximate various unknown nonlinear forces of the system having unknown forms to adapt to various operating conditions. The design is actual system dynamics based, which makes the resulting on-line weight tuning law much more robust and accurate than those in the tracking error dynamics based direct NNARC designs in implementation. With a controlled learning process achieved through projection type weights adaptation laws, certain robust control terms are constructed to attenuate the effect of possibly large transient modelling error for a theoretically guaranteed robust output tracking performance in general. Experimental results are obtained to verify the effectiveness of the proposed INNARC strategy. For example, for a typical point-to-point movement, with a measurement resolution level of ±1μm, the output tracking error during the entire execution period is within ±5μm and mainly stays within ±2μm showing excellent output tracking performance. At the same time, the outputs of NNs approximate the unknown forces very well allowing the estimates to be used for secondary purposes such as prognostics.

New Neural Network Inverse Control of Two-Motor Drive System

2013 ◽  
Vol 416-417 ◽  
pp. 447-453
Author(s):  
Mei Kang ◽  
Wen Xiang Zhao ◽  
Jing Hua Ji ◽  
Guo Hai Liu
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Motor System ◽  
Rbf Neural Network ◽  
Particle Swarm ◽  
Drive System ◽  
Motor Drive ◽  
Swarm Optimization ◽  
Synchronous System ◽  
Motor Drive System

Two-motor drive system is a multi-variable, nonlinear and strongly coupled system. A new synchronous control strategy for two-motor system is proposed based on radial basis function (RBF) neural network inverse with particle swarm optimization. To enhance the system performance, the particle swarm optimization is adopted to optimize the RBF nerve center, an optimized RBF neural network inverse and a two-motor system is connected in series to form composite pseudo-linear system. This two-motor synchronous system can be decoupled into two independent linear subsystems for speed and tension. Then, the decoupled control is implemented by designing a linear closed-loop adjustor. The experimental results verify that the two-motor synchronous system can be decoupled well for speed and tension based on the proposed neural network inverse system. Also, the proposed system can deal with external disturbances with strong robustness.

Robust Control of a CSI-Fed Induction Motor Drive System

1987 ◽  
Vol IA-23 (4) ◽  
pp. 610-616 ◽  
Author(s):  
Rajiva Prakash ◽  
S. Vittal Rao ◽  
Frank J. Kern
Keyword(s):  
Robust Control ◽  
Induction Motor ◽  
Drive System ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Motor Drive System
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