Research on Real-time Simulation and Control of Linear 1-stage Inverted Pendulum

Abstract

Inverted pendulum system is a complex, unstable and nonlinear system. In order to make it become an adaptive and robust stable system in control strategy, the mathematical model of linear l-stage inverted pendulum has been established by means of Newton mechanics. The control strategies including classic control methods and modern control methods, such as the PID control algorithm, the pole assignment algorithm and the T-S fuzzy control algorithm.The real-time control results show that the PID control algorithm and the pole assignment algorithm based on the dynamic model have different qualities and characteristic. The structure of PID control is smiple, but the PID controller parameters is more difficult to select, and the overshoot of the system is easy to be increase because of the system strong instability. In addition, the traditional PID control algorithm can only control the pendulum's angle, and can't control displacement. Pole placement method has the better robustness and transient characteristics, but it mainly relies on the experience of engineers to select the desired pole, so it does not have the convenience and simplicity of the PID. The T-S fuzzy controller doesn't need to build an accurate mathematical model of the object, the nonlinear system can be fuzzified into local linera model based on the empirical knowledge. The T-S fuzzy controller reduce the dimension of fuzzy controller and simplify the rules. The real-time control results analysis shows the pendulum and cart position can quickly be stabilized with strong robustness. In real-time control of the inverted pendulum system, car position, car speed and the pendulum angle and angular velocity, etc not only to be considered, but also the state variables, measurement accuracy and sensitivity of the sensor have to consider. So there are a lot of work to do in the real-time control of inverted pendulum system.

Comparison of PPC and LQR Controller for Stabilization of Cart Pendulum System: Simulation and Real-Time Study

“…Correspondingly, the modern control theory controllers are idealized to control nonlinear system and consume less time as compared to intelligent controllers. Song et al [7] studied the comparison between PID (Proportional-Integrate-Derivative), pole placement and fuzzy logic controller to control the stabilization problem of cart pendulum system. They concluded that the pole placement controllers give better dynamic and steadystate performance as compared to other two controllers.…”

Algorithm Apriori Association Rule in Determination of Fuzzy Rule Based on Comparison of Fuzzy Inference System (FIS) Mamdani Method and Sugeno Method

“…The modelling techniques based on FIS are appealing and have found many successful applications in various fields including Fuzzy PID position control approach in computer numerical control machine tool ; research on real-time simulation and control of linear 1-stage inverted pendulum (Song, 2013); as well as on a study on the control methods based on 3-DOF helicopter model (Gao, 2012;Wang, 2014).…”

Design and implementation of the inverted pendulum optimal controller based on hybrid genetic algorithm

“…The control method has a wide range of uses in the field of military industry, aerospace science and technology, robot and general industrial process. In recent years, many scholars have used the classical control theory, modern control theory and a variety of intelligent control methods [1,2]in this system and successfully achieved stability control of inverted pendulum system.…”