The electro-optical tracking system (ETS) on moving platforms is affected by the vibration of the moving carrier, the wind resistance torque in motion, the uncertainty of mechanisms and the nonlinear friction between frames and other disturbances, which may lead to the instability of the electro-optical tracking platform. Sliding mode control (SMC) has strong robustness to system disturbances and unknown dynamic external signals, which can enhance the disturbance suppression ability of ETSs. However, the strong robustness of SMC requires greater switching gain, which causes serious chattering. At the same time, the tracking accuracy of SMC has room for further improvement. Therefore, in order to solve the chattering problem of SMC and improve the tracking accuracy of SMC, an SMC controller based on internal model control (IMC) is proposed. Compared with traditional SMC, the proposed method can be used to suppress the strongest disturbance with the smallest switching gain, effectively solving the chattering problem of the SMC, while improving the tracking accuracy of the system. In addition, to reduce the adverse influence of sensor noise on the control effect, lifting wavelet threshold de-noising is introduced into the control structure to further improve the tracking accuracy of the system. The simulation and experimental results verify the superiority of the proposed control method.

In this paper, a disturbance compensation strategy based on disturbance observer control (DOBC) is proposed to solve parameter perturbation, friction, coupling and external turbulence for two-axes gimbal control system. Uncertainties, friction, coupling shortcoming of gimbal system is summed up as a disturbance suppression problem, and achieving disturbance compensation through feedforward channel of DOBC. However, the compensation effects of DOBC are determined by modeling accuracy of the nominal plant and feedforward filter design. A H ∞-based filter design is adopted to guarantee robust stability of DOBC when controlled object changed. Because performance weight function of DOBC is derived from stable constraint of closed-loop system, and robust of closed-loop system can also be satisfied. Eventually, we completed proof of H ∞-based robust DOBC algorithm in pod system, and stability performance of the system has been greatly improved.

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