Modelling and Implementation of PID Control for Balancing of an Inverted Pendulum - Abeysekera, B; Wanniarachchi, I (My University, 2018)
Inverted pendulum (IP) has become a popular topic among physicist and control engineers due to advanced applications related to this particular pendulum. Two wheel balancing robots, rockets and missile guidance systems are some complex applications of the IP. The IP is highly unstable and to maintain the vertical upright position, an active control system is needed. Proportional, Integral and Derivative (PID) controller is one of the best controlling methods used in various dynamic control systems recently because of the simplicity and applicability. In this paper, two PID controllers are used to balance the IP and an error optimization method is used for filtering unwanted sensor responses. The PID controllers have been designed for controlling of each sub-system. PID gain parameters are tuned separately and manually using trial and error approach. Mathematical model of this IP is developed to determine the dynamic properties of the IP system and through this model, state space model of the IP system is developed. With the help of state space model, Kalman filter is developed and used to optimize the error in sensor readings. Then control system of the IP based on the PID controllers and the Kalman filter (control algorithm) is implemented on a microcontroller based platform in order to balance the inverted pendulum on a trolley using the mechanical system which is controlled by the microcontroller. Main objective of this control system is to balance the IP in an upright position in the middle of the two rails. Behavior of the IP system with this control algorithm is monitored through the real-time data acquisition system. The data of the IP system is used to contrast the IP behavior with each PID gain parameter through a graphical representation. With proper gain parameters, the IP system shows best smooth behavior of it.
Keywords: Inverted Pendulum, Kalman Filter, Lagrangian, Microcontroller, PID, Space State Modeling