Dual Heuristic Programming Based Neurocontroller for Vibration Isolation Control

The dual heuristic programming (DHP) approach has a superior capability to solve approximate dynamic programming problems in the family of adaptive critic designs (ACDs). In this paper, a DHP based controller is developed for vibration isolation applications. In the specific case of an active-passiv...

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Veröffentlicht in:2008 IEEE International Conference on Networking, Sensing and Control S. 874 - 879
Hauptverfasser: Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong Liu
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.04.2008
Schlagworte:
Adaptive critic designs (ACDs)
approximate dynamic programming (ADP)
Convergence
dual heuristic programming (DHP)
Dynamic programming
Feedforward neural networks
Isolators
Multi-layer neural network
Neural networks
Neurocontrollers
optimal control
Robust control
Signal processing
Vibration control
vibration isolator
ISBN:142441685X, 9781424416851
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Zusammenfassung:The dual heuristic programming (DHP) approach has a superior capability to solve approximate dynamic programming problems in the family of adaptive critic designs (ACDs). In this paper, a DHP based controller is developed for vibration isolation applications. In the specific case of an active-passive isolator, a multilayer feedforward neural network is pre- trained as a differentiable model of the plant for the adaptation of the critic and action networks. In addition, in order to avoid plunging in the local minima during the training process, pseudorandom signals, which represent the vibrations of the base, are applied to the vibration isolation system. This technique greatly improves the robustness of the DHP controller against unknown disturbances. Moreover, the "shadow critic" training strategy is adopted to improve the convergence rate of the training. Simulation results have shown that the developed DHP controller alleviates vibration disturbances more effectively and have better control performance in comparison with the passive isolator. Additionally, as compared with the one adapted on-line, the pre-trained model network leads the training to be more efficient. Therefore, it further demonstrates the effectiveness of the DHP controller designed with the pre-trained model network even in the presence of unmodeled uncertainties.
ISBN:142441685X
9781424416851
DOI:10.1109/ICNSC.2008.4525339