Applied Research On Active Disturbance Rejection Of Double Inverted Pendulum System

Inverted pendulum are multivariable, nonlinear, unstable, strong coupling of the fast system, these features lead to the achievement of its control more difficult, so its research under control has general importance to scholars these years. Study of the inverted pendulum can be attributed to the multi-variable nonlinear system, its control methods and ideas for dealing with industrial processes in general also has guiding significance.In the stabilization of double inverted pendulum, if there has a disturb on the swing rod, it will dump, the system is out of control. that is, the capacity immunity of the system are weaknesses. This study focused on finding an appropriate control algorithm to improve its stability control system after the active disturbance rejection ability. It specifically manifested in: the control algorithm makes the system by the disturbance, the swing rod angle is small, the system return to equilibrium time is short, the system steady-state error is small. In this paper, a double inverted pendulum is derived mathematical model of the state space, and carry out the necessary analysis and validated using the pole placement algorithm, LQR algorithm, LQY method, LQR weighting matrix of genetic algorithm optimization, fuzzy control algorithm which combines the function of fuzzy control algorithm, for a double inverted pendulum control. For each algorithm, the authors describe the use of mathematical algorithms, MATLAB simulation software, SIMULINK offline simulation, parameter adjustment or algorithm optimization, physical control of verification, a variety of algorithms and concluded that - this kind of research and writing ideas, to find a better control algorithm to achieve the purpose of solving the problem.The authors take a specific course of the study of the main measures are:1. Through simulation and experimental LQR algorithm into a matrix Q of the selected elements of the principle embodied in tabular form, not only for physical control and research work with others to reference, but also the physical control to the anti disturbance capacity increased.2. To introduce a genetic algorithm to the Q matrix optimization parameters, the result of this optimization strategy to improve the disturbance rejection algorithm LQR control indicators.3. The simulation and experimental induction of the fuzzy control factor and scale factor to quantify the selection, the impact on system performance, which will help improve the control of fuzzy control algorithm indicators.Through the specific study on linear double inverted pendulum and circle railed double inverted pendulum, the authors ultimately find a proper control algorithm: genetic algorithm based on the integration of optimization function fuzzy control algorithm to achieve the intended purpose, in the physical control of the algorithm of the control algorithm than the others in the system active disturbance rejection indicators have markedly improved capacity.