To improve the equilibrium control performance of the seesaw system under external disturbances,a composite control strategy based on the combination of exponentially convergent disturbance observer and switching gain fuzzy adaptive hierarchical sliding mode control is proposed.Firstly,an exponentially convergent disturbance observer is designed to estimate and compensate for the uncertainties of the system subjected to external disturbances to improve the robustness of the controller.The observer does not need the information of the second-order derivatives of the state variables,which can cope with the problem that it is difficult to obtain the acceleration signals by means of derivatives in practical engineering.Then,a hierarchical sliding mode control algorithm is proposed for strongly coupled underdriven systems such as seesaw,and furthermore,to address the problem that the switching gain of the sliding mode control algorithm is too large in the presence of unknown large disturbances,the switching gain is blurred through the design of fuzzy rules in order to reduce the system jitter.Finally,the simulation and experimental results show that the hierarchical sliding mode control algorithm has stronger interference immunity and lower switching gain compared with the traditional sliding mode control algorithm.The stategy can be applied to the real system of seesaw-like balance control.
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