Abstract:
Based on the approximation capability and generalization property of the backpropagation neural networks (BPNNs) for nonlinear mapping on a compact set, this paper presen...Show MoreMetadata
Abstract:
Based on the approximation capability and generalization property of the backpropagation neural networks (BPNNs) for nonlinear mapping on a compact set, this paper presents a novel approach for designing adaptive neurocontroller (ANC) for unknown multivariable discrete nonlinear systems in general form. The key ideas of the proposed control strategy are of applying the Clarke's one-step-ahead weighted predictive control performance index and linearizing the feedforward BPNNs identifier models. Simulation results demonstrate the effectiveness of the new adaptive neural control scheme.<>
Date of Conference: 14-16 December 1994
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-1968-0
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Neural Network ,
- System Dynamics ,
- Nonlinear Dynamics ,
- Adaptive Control ,
- Nonlinear Function ,
- Nonlinear Systems ,
- Neural Control ,
- Back Propagation Neural Network ,
- Unknown System ,
- Adaptive Neural Control ,
- Time Step ,
- Learning Rate ,
- Artificial Neural Network ,
- Cost Function ,
- Optimal Control ,
- Linear System ,
- Control Input ,
- Control Problem ,
- System Identification ,
- Closed-loop System ,
- Unknown Plant ,
- Dynamic Design ,
- Non-minimum Phase ,
- Back Propagation Neural Network Model ,
- Back-propagation Network ,
- Time-varying Systems ,
- Linear Time-varying Systems ,
- Adaptive Control Law ,
- Backpropagation Algorithm ,
- Steady Error
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Neural Network ,
- System Dynamics ,
- Nonlinear Dynamics ,
- Adaptive Control ,
- Nonlinear Function ,
- Nonlinear Systems ,
- Neural Control ,
- Back Propagation Neural Network ,
- Unknown System ,
- Adaptive Neural Control ,
- Time Step ,
- Learning Rate ,
- Artificial Neural Network ,
- Cost Function ,
- Optimal Control ,
- Linear System ,
- Control Input ,
- Control Problem ,
- System Identification ,
- Closed-loop System ,
- Unknown Plant ,
- Dynamic Design ,
- Non-minimum Phase ,
- Back Propagation Neural Network Model ,
- Back-propagation Network ,
- Time-varying Systems ,
- Linear Time-varying Systems ,
- Adaptive Control Law ,
- Backpropagation Algorithm ,
- Steady Error
