Study On The Control Of The Single Link Rotary Inverted Pendulum Based On Single Neuron Controller

Inverted pendulum system is a multivariate, strong coupling, nonlinear and typical natural unstable system. Study on the control of inverted pendulum, can reflect many crucial questions in the control theory, such as robust stabilization problem,problem and the tracking problem, therefore, the inverted pendulum can be used to test the effectiveness of various control theory. The research on the control method of the inverted pendulum system, and can be applied in many fields of industrial process,robots and Aerospace Science and technology, the study has important theoretical and engineering value. At present the domestic and foreign research scholars mainly focus on the linear inverted pendulum, the control technology has been basically mature, in the field also has quite many research results. Relatively speaking, research on inverted pendulum is rarely. Inverted pendulum will swing rod is installed in the horizontal rod is connected with the motor shaft, driven by the motor in the rotation to control the inverted pendulum rod, the swing rod can rotate in the vertical plane.Inverted pendulum is a linear inverted pendulum motion control to rotation control,making the whole system more complex and unstable, increasing the difficulty of control.The design of the control loop of an inverted pendulum in its essence, can control problem is a typical multivariate system. But for most of its control strategy using the classical PID control, pole assignment method, LQR control, fuzzy control.This paper is based on an inverted pendulum system as the research object, the first is the use of existing control strategy, and made some extension, such as the double loop PID control, the LQR controller based on fruit fly optimization algorithm. Then the single neuron intelligent control as the core, with PID control, LQR control are combined, the single neuron PID control, state feedback control neurons, these two kinds of control methods make full use of the neuron has the advantages of simple structure and self-learning, adaptive ability of the advantages, has carried on thebeneficial exploration in the single neuron control of multivariate problem. The main research work in this paper includes:(1) the equations of motion are derived using the Lagrange method of rotary inverted pendulum system, and on the basis of the inverted pendulum system stability,controllability and observability are analyzed, the results show that the system is open-loop unstable and controllable, observable.(2) based on the conventional PID control theory, the single loop PID controller is designed for an inverted pendulum and double loop PID controller, the simulation results show that, under the Matlab/Simulink platform, single loop PID controller can control the angle of the pendulum, unable to control the connecting rod angle; and the double loop PID the controller can effectively control the angle and the angle of the pendulum rod.(3) from the viewpoint of multivariate control of complex system, a detailed analysis of the single neuron PID control strategy in the control of the problem of circular inverted, and on the basis of conventional double loop PID controller, a kind of double loop and single neuron PID control method, the simulation results show that,compared with the conventional double loop double loop PID control, single neuron PID controller has better control effect.(4) by using the linear quadratic optimal control in two(LQR) of the basic theory,a LQR controller is designed a ring of an inverted pendulum, and are simulated by Matlab; secondly, using fruit fly optimization algorithm to optimize the design of the LQR controller, and to determine the optimal matrix Q, and the corresponding optimal feedback gain matrix K, get the simulation results are: the system reaches steady state in the 2S inverted pendulum to show that after optimization, LQR controller based on fruit fly optimization algorithm, has better control effect on Circular Inverted Pendulum system.(5) in the analysis of the adaptive neuron control strategy in multivariate control system, introducing the LQR control in the idea of state feedback, a ring of an inverted pendulum state feedback neuron control strategy, the simulation experiments verify the effectiveness and superiority of the control strategy.