Barrier Lyapunov Function-Based Adaptive Back-Stepping Control for Electronic Throttle Control System

Abstract

This paper presents an adaptive constraint control approach for Electronic Throttle Control System (ETCS) with asymmetric throttle angle constraints. The adaptive constraint control method, which is based on barrier Lyapunov function (BLF), is designed not only to track the desired throttle angle but also to guarantee no violation on the throttle angle constraints. An ETC mathematic model with complex non-linear system is considered and the asymmetric barrier Lyapunov function (ABLF) is introduced into the design of the controller. Based on Lyapunov stability theory, it can be concluded that the proposed controller can guarantee the stability of the whole system and uniformly converge the state error to track the desired throttle angle. The results of simulations show that the proposed controller can ensure that there is no violation on the throttle angle constraints.

Smooth, Singularity-Free, Finite-Time Tracking Control for Euler–Lagrange Systems

“…[47] is a constrained control for nonlinear systems and is a suitable candidate to investigate the efficacy of the proposed constrained control framework. The simulation results of the three controllers applied to the robotic manipulator (25) are illustrated in In fact, the main focus of the constrained controls (5) and (20) in Berger [47] is to satisfy constraints on the tracking error, and they are not able to make the tracking errors converge to zero. Based on this example, the proposed control accomplishes superior performance over the two controls in Berger [47].…”

“…For instance, to prevent the end effectors of robot manipulators from colliding with obstacles in the environment, they have to work within a specific space. During the recent years, several approaches such as Barrier Lyapunov Function (BLF) [25] and prescribed performance control (PPC) [26] have been employed to achieve certain safety measures and performance requirements in the transient and steady-state responses of EL systems. To provide output constraints of a robot manipulator, a combination of adaptive neural network control and the BLF approach is utilized in [27].…”

Adaptive Second-Order Fixed-Time Sliding Mode Controller with a Disturbance Observer for Electronic Throttle Valves

“…However, controlling the ETV is complex due to various nonlinear factors, including stick-slip friction, gear clearance, and discontinuous nonlinear springs [ 5 ]. In recent years, several control strategies have been proposed for ETV, including PID control [ 6 , 7 , 8 ], optimal control [ 9 , 10 ], adaptive control [ 11 , 12 , 13 , 14 ], and sliding mode control [ 15 , 16 , 17 , 18 ]. Among them, sliding mode (SM) control is a powerful nonlinear control method that can achieve stable and robust control even in the presence of model uncertainties and external disturbances, which makes SM well-suited for ETVs.…”

“…Further, Liu et at. [ 14 ] and Wang et al [ 13 ] applied adaptive control to the electronic throttle system and made progress in the tracking error. However, in specific applications, ensuring the stability of these intelligent methods is challenging, and incorrect parameter update rules could result in system instability.…”

Stability Analysis and Chaos Control of Electronic Throttle Dynamical System

“…Because electronic throttle valve systems feature many nonsmooth nonlinearities, the system is very hard to control [13][14][15]. Several studies have investigated nonlinear control for electronic throttle systems [16][17][18][19][20], which are typically depicted by a nonlinear dynamical system [13,17]. Modifying one of these parameters alters the dynamics that exhibit chaos motion, leading to instability of engine running.…”