Almost disturbance decoupling control of mimo nonlinear system subject to feedback linearization and a feedforward neural network: Application to half-car active suspension system |
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Authors: | T H S Li C J Huang C C Chen |
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Institution: | (1) Department of Mechanical Engineering, POSTECH, San 31 Hyojading, 790-784 Pohang, Korea;(2) Department of Electrical Engineering, National Taiwan University, 106 Taipei, Taiwan, R.O.C. |
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Abstract: | A novel tracking and almost disturbance decoupling problem of multi-input, multi-output (MIMO) nonlinear systems based on
feedback linearization and a multi-layered feedforward neural network approach has been proposed. The feedback linearization
and neural network controller guarantees exponentially global uniform ultimate bounded stability and almost disturbance decoupling
performance without using any learning or adaptive algorithms. The new approach renders the system to be stable with the almost
disturbance decoupling property at each step when selecting weights to enhance the performance if the proposed sufficient
conditions are maintained. One example, which cannot be solved by the existing approach of the almost disturbance decoupling
problem because it requires the sufficient conditions that the nonlinearities that multiply the disturbances satisfy structural
triangular conditions, is proposed to exploit the fact that the tracking and the almost disturbance decoupling performances
are easily achieved by the proposed approach. In order to demonstrate the practical applicability, a famous half-car active
suspension system is investigated. |
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Keywords: | |
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