Trajectory Tracking Control Strategy Of Double Rotation Inverted Pendulum

The double rotation inverted pendulums is a nonlinear,strong coupling,instability,such as characteristics of the system,at the same time the The double rotation inverted pendulums system is also many of the simplified model of a complex object,which makes the The double rotation inverted pendulums became the hotspot in the research object.In this paper,the The double rotation inverted pendulums trajectory tracking control problem study,at the same time,in view of the dynamic model of secondary rotary inverted pendulum,design without tracking kalman linear quadratic optimal control strategy,fractional order sliding mode control strategy based on neural network,fuzzy switch gain of sliding mode control strategies under strong interference,the thesis mainly work as follows:First,analyze the double rotation inverted pendulum structure.At the same time,it analyzes various modeling methods,selects the combined body inertia method to perform dynamic modeling on the double rotation inverted pendulum,and gives the dynamic equation of the double rotation inverted pendulum,which lays the foundation for subsequent control algorithm strategy research.Secondly,the optimal control strategy of the linear quadratic optimal control strategy is proposed to optimize the control accuracy of the optimal control strategy of the linear quadratic optimal control strategy.From the simulation analysis,and the conventional linear quadratic optimal control strategy,the design of no trace kalman linear quadratic optimal control strategy makes the system control accuracy,overshoot,response time and other performance index improved significantly.Thirdly,the conventional sliding mode variable structure control algorithm is designed,and the advantages and disadvantages of the conventional sliding mode control algorithm are analyzed.Aiming at the problem of large output chattering of the conventional sliding mode control algorithm,a sliding mode control algorithm based on neural network fractional order is designed.(Neural Network Fractional Order Sliding Mode Control,referred to as NNFO-SMC).Optimize fractional tuning parameters through neural networks.From simulation analysis,it is concluded that the designed neural network fractional sliding mode control strategy effectively weakens the output chattering of the system and reduces the system overshoot and response time.Finally,consider the system operating under strong interference and uncertain conditions.The fuzzy switching gain sliding mode control strategy under strong interference is designed.When there are strong disturbances in the outside world,fuzzy control is used to estimate the switching gain based on the arrival conditions of the sliding film.At the same time,the linear relationship between the fuzzy switching gain and the strong disturbance term is used to reduce the influence of strong interference and uncertain environment on the system.From the simulation research and analysis,it is concluded that the proposed fuzzy switching gain gain sliding mode control strategy under strong interference can effectively improve the system's anti-jamming capability,at the same time improve the system's control accuracy and reduce the system's output jitter under strong interference and uncertainty conditions.Vibration phenomenon.