Study On New Sliding Mode Control Strategy Of Seesaw System

The seesaw system is a typical inherently unstable system,which has the characteristics of severe nonlinearity,strong coupling property and underactuation.It is an ideal experimental platform for testing control algorithms.Its balance control principle is similar to ship balance control,aircraft attitude adjustment and other practical systems.In view of the characteristics of the seesaw system,three new control strategies are studied in this paper.The main work is as follows:(1)Based on the analysis of the structural characteristics and operation principle of the seesaw system,the dynamics model of the system is established by Lagrange equation.(2)Aiming at the characteristics of the seesaw system which is inherently unstable and sensitive to disturbance,an exponentially convergent disturbance observer without the second derivative information of the system state is designed to estimate and compensate the system disturbance.Furthermore,aiming at the characteristics of strong coupling and underactuation of the seesaw system,a hierarchical sliding mode controller based on observer disturbance compensation is designed comprehensively by using the idea of hierarchical sliding mode control,which improves the balance control performance of the seesaw system.(3)In order to deal with the chattering problem of traditional sliding mode control,the super twisting sliding mode control algorithm is applied to balance control of seesaw system,and particle swarm optimization algorithm is used to optimize the parameters of super twisting sliding mode controller,which improves the dynamic performance of balance control of seesaw system.(4)In order to solve the problem that the particle swarm optimization algorithm is difficult to realize real-time parameter tuning,and the existing adaptive super twisting algorithm usually needs to estimate the upper bound of unknown disturbance manually or make certain assumptions about the unknown disturbance,the disturbance observer designed is used to estimate the unknown disturbance,and the parameter adaptive law satisfying the stability of the system is derived based on the quasi-quadratic Lyapunov function.An adaptive super twisting sliding mode controller without the upper bound of unknown disturbance is designed,which can suppress chattering and overcome the conservatism of artificial parameter selection,and the balance control performance of the seesaw system is further improved.(5)There are three control strategies applied to the actual control of the seesaw system.And the experimental results further indicate that the proposed control strategies are effective and feasible.