Extended State Observer Based Adaptive Back-Stepping Sliding Mode Control of Electronic Throttle in Transportation Cyber-Physical Systems

Abstract

Considering the high accuracy requirement of information exchange via vehicle-to-vehicle (V2V) communications, an extended state observer (ESO) is designed to estimate the opening angle change of an electronic throttle (ET), wherein the emphasis is placed on the nonlinear uncertainties of stick-slip friction and spring in the system as well as the existence of external disturbance. In addition, a back-stepping sliding mode controller incorporating an adaptive control law is presented, and the stability and robustness of the system are analyzed using Lyapunov technique. Finally, numerical experiments are conducted using simulation. The results show that, compared with back-stepping control (BSC), the proposed controller achieves superior performance in terms of the steady-state error and rising time.

Extended state observer–based intelligent double integral sliding mode control of electronic throttle valve

“…Moreover, the function g(z) should satisfy the following conditions 8,28 1. g(z) is continuously differentiable; 2. g(0) = 0;…”

“…So, controller performance of square wave signal is discussed here. As a matter of fact, according to working range of the nonlinear spring in Hu et al, 6 the minimum and maximum values of square wave are, respectively, set as 10 8 and 80 8 . Figures 11 and 12 show the square wave signal tracking performance of IDISMC and SMC.…”

“…Therefore, the disturbance would result in the performance deterioration. Recently, Li et al 8 proposed an extended state observer (ESO)-based backstepping sliding mode control (SMC) approach for the ET valve. Especially, an ESO was designed based on the ET nonlinear model to estimate the throttle opening angle change and uncertainty of ET simultaneously and then the backstepping sliding mode controller was developed to improve the control performance.…”

Robust Longitudinal Speed Control of Hybrid Electric Vehicles with a Two-Degree-of-Freedom Fuzzy Logic Controller

“…is a decreasing function. Let be the membership level of , as shown in Figure 2; we obtain: Consider the uncertain interval model Equation (13). Assume that the only information available for the values of the uncertain parameters p 0 , q 0 , q 1 , q 2 , q 3 and q 4 , is the linguistic information "around the nominal value of Table 1", by using interval arithmetic (affine linearization) [17,19,20] (Figure 3).…”

“…In addition, HEV speed control must combine ETCS with nonlinear vehicle dynamics. Because of factors such as the uncertainty parameters of nonlinear elements and instability from environmental disturbances, designing an algorithm for HEV speed control is challenging [13].…”