미지의 제어입력계수를 갖는 세그웨이를 위한 모델-프리 제어기 설계

Abstract

The Segway is becoming more prevalent on urban sidewalks. In order to design the controller for Segway, the linear controllers such as PID and LQR were firstly proposed. These methods require the linearized model of Segway and thus, have the limit due to the narrow operating range. To solve this problem, various nonlinear control methods such as sliding mode control and adaptive control based on the backstepping technique were proposed. As it is well known, the backstepping technique requires the differentiation of virtual controls and this complicates the controller. Although the dynamic surface control method can remove the disadvantage of the backstepping technique, it is still complex because it should use the adaptive technique or neural network to deal with the uncertainties. To reduce the complexity of the nonlinear control methods, a low-complexity control method was recently proposed. By using the prescribed performance function, it can adjust the transient and stead-state response. Further, it does not require the adaptive technique and neural network to compensate the uncertainties. Hence, the controller can be implemented more simply. In this regard, several controllers for Segway were presented using this method. However, previous works assume that the unknown control coefficient is constant. This assumption is not applicable to real systems because it is time-varying. Thus, we need to relax this assumption. Motivated by these observations, we propose a model-free controller for Segway in the presence of the unknown control coefficient and model uncertainties. Firstly, we employ the Nussbaum gain technique to deal with the unknown time-varying control coefficient. Then, the approximation-free controller using the prescribed performance function is designed to compensate the uncertainties. For the stability of the proposed scheme, we prove that all error signals of the closed-loop control system are bounded using the Lyapunov stability theory. Finally, the simulation results are provided to demonstrate the effectiveness of the proposed control method.