Finite-time path following control for a stratospheric airship with input saturation and error constraint

Self Cite

Summary This paper presents an event‐triggered controller for a class of saturated uncertain nonlinear systems. We develop a performance constrained finite‐time controller to guarantee that the tracking error converges at a prescribed convergence rate and does not exceed the given maximum overshoot. A smooth function is designed to replace the absolute and signum operators in existing finite‐time controllers that lead to nondifferentiable virtual controls. Then, a novel backstepping design consisting of an adaptive law and an auxiliary system governed by a smooth switching function is developed to compensate for the uncertainty, the triggering event threshold, and the saturation constraint. Theoretical analysis demonstrates that under the proposed controller, all closed‐loop signals are bounded and the Zeno behavior is avoided. Furthermore, the tracking error will converge toward a residual set in finite time, and the prescribed transient and steady tracking performance bounds are never violated. Results from a comparative simulation study illustrate the effectiveness and advantages of the proposed method.

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Event‐triggered control for a saturated nonlinear system with prescribed performance and finite‐time convergence

Zheng

Lau

Xie

2018

Self Cite

“…Another important consideration in addressing trajectory tracking problems for autonomous agents is about the constraint requirements. In reality, we often need some system variables or their tracking errors to remain in certain sets, to ensure the feasibility of the control design, to guarantee prescribed tracking performance, or to avoid undesirable consequences . For example, if the distance tracking error between the agent and the desired trajectory is too large in a search and rescue mission, the intended target area may not be reached.…”

Section: Introductionmentioning

confidence: 99%

Nonrepetitive trajectory tracking for nonlinear autonomous agents with asymmetric output constraints using parametric iterative learning control

Jin

2019

Summary In this paper, we present a novel parametric iterative learning control (ILC) algorithm to deal with trajectory tracking problems for a class of nonlinear autonomous agents that are subject to actuator faults. Unlike most of the ILC literature, the desired trajectories in this work can be iteration dependent, and the initial position of the agent in each iteration can be random. Both parametric and nonparametric system unknowns and uncertainties, in particular the control input gain functions that are not fully known, are considered. A new type of universal barrier functions is proposed to guarantee the satisfaction of asymmetric constraint requirements, feasibility of the controller, and prescribed tracking performance. We show that under the proposed algorithm, the distance and angle tracking errors can uniformly converge to an arbitrarily small positive number and zero, respectively, over the iteration domain, beyond a small user‐prescribed initial time interval in each iteration. A numerical simulation is presented in the end to demonstrate the efficacy of the proposed algorithm.

Adaptive decentralized finite‐time output tracking control for MIMO interconnected nonlinear systems with output constraints and actuator faults

Jin

2017

In this work, we present a novel adaptive decentralized finite-time fault-tolerant control algorithm for a class of multi-input-multi-output interconnected nonlinear systems with output constraint requirements for each vertex. The actuator for each system can be subject to unknown multiplicative and additive faults.Parametric system uncertainties that model the system dynamics for each vertex can be effectively dealt with by the proposed control scheme. The control input gain functions of the nonlinear systems can be not fully known and state dependent. Backstepping design with a tan-type barrier Lyapunov function and a new structure of stabilizing function is presented. We show that under the proposed control scheme, with the use of graph theory, finite-time convergence of the system output tracking error into a small set around zero is guaranteed for each vertex, while the time-varying constraint requirement on the system output tracking error for each vertex will not be violated during operation. An illustrative example on 2 interacting 2-degree-of-freedom robot manipulators is presented in the end to further demonstrate the effectiveness of the proposed control scheme.