A PID backstepping controller for two-wheeled self-balancing robot

Abstract

This paper presents a method to design and control a two-wheeled self-balancing robot and it focus on hardware description, signal processing, discrete Kalman filter algorithm, system modelling and PID backstepping controller design. In the system, signals from angle sensors are filtered by a discrete Kalman filter before being fed to the PID backstepping controller.The objectives of the proposed controller are to stabilize the robot while try to keep the motion of robot to track a reference signal.The proposed PID backstepping controller has three control loops, in which the first loop uses a backstepping controller to maintain the robot at equilibrium, the second loop uses a PD controller to control the position of robot and the last uses a PI controller to control the motion direction. Simulations and experimental results show that the proposed control system has good performances in terms of quick response, good balance, stability .

A neural network combined with sliding mode controller for the two-wheel self-balancing robot

“…There are many effective control methods available for the TWSB robot with nonlinear kinetics, such as the method using a proportional integral derivative (PID) controller [2], the optimal controller based on the linear-quadratic regulator (LQR) [3], [4], the robust-adaptive control [5], the backstepping control [6], [7], the sliding mode control [8], the fuzzy logic control structure [9] and the control system based on a neural network [10]. However, there is a lot of noise during outdoor operation that negatively affects the control system's quality.…”

Robot Keseimbangan dengan Kendali PID dan Kalman Filter

“…Penelitian tentang robot keseimbangan telah banyak dilakukan oleh peneliti sebelumnya dengan menggunakan berbagai macam pengendali seperti LQR (Linear Quadratic Regulator) [2], PD (Proporsional Derivatif) [3], PID (Proporsional Integral Derivatif) [4], Neural Network Control [5], Backstepping [1]. Namun, penelitian tersebut masih sebatas pada simulasi.…”