Control Systems with Actuator Saturation: Analysis and Design

By Tingshu Hu, Zongli Lin. 2001

1,358 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/b4df16d79eaaddf7b039b561c7807c5b1036738a

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In Control and Systems Engineering

Citations in the corpus

Composite quadratic Lyapunov functions for constrained control systems (2002, methodology): “It can be shown with methods in [6], Chapter 11, that there exists a positive number k such that Lvc (1) is contractively invariant under the saturated linear feedback law”
Control of nonlinear systems with partial state constraints using a barrier Lyapunov function (2011, methodology): “For linear systems, methods to handle constraints are usually based on notions of set invariance using Lyapunov analysis (Liu and Michel 1994 ; Hu and Lin 2001 ), exploiting the fact that positive invariant sets can be obtained constructively in linear systems.”
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems (2009, methodology): “Existing methods to handle constraints include model predictive control (Allgöwer, Findeisen, & Ebenbauer, 2003; Mayne, Rawlings, Rao, & Scokaert, 2000), reference governors (Bemporad, 1998; Gilbert & Kolmanovsky, 2002), and the use of set invariance notions (Hu & Lin, 2001; Liu & Michel, 1994).”
Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation (2002, background): “Remark 1: Theorem 3 gives a condition for the region to be inside the domain of attraction for the closed-loop system (4) under a linear constant feedback control law (9).”
Analysis and design for discrete-time linear systems subject to actuator saturation (2001, methodology): “By combining Theorem 2 and Hu and Lin’s method [6], the maximal E(P; ) is E(P; ∗) with ∗ =2:3490.”
Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints (2015, background): “During the past several decades, considerable efforts have been made to enhance the control performance of uncertain nonlinear systems with control constraints [1]–[4].”
Removing the Feasibility Conditions Imposed on Tracking Control Designs for State-Constrained Strict-Feedback Systems (2019, methodology): “There are numerous methods for dealing with state constraints in the literature, including model predictive control [20], reference governors [1], [3], and set invariance notions [2], [7], [8].”
Control of Linear Systems with Regulation and Input Constraints (2000, background): “Over the past decade, several books have been published that deal with the subject of control systems with constraints, whether the constraints are on the states of the system or on the control inputs of the system (see, e.g., [ 2 ]–[5]).”
An analysis and design method for linear systems subject to actuator saturation and disturbance (2002, methodology): “A related problem was addressed by Hu and Lin (2001b) and Saberi, Lin, and Teel (1996), where the disturbances are input additive and enter the system before the saturating actuator, i.e., the system has a state equation: ˙ x = Ax + BB(u + w).”
Barrier Lyapunov functions-based adaptive control for nonlinear pure-feedback systems with time-varying full state constraints (2017, background): “Many fruitful results on constraint-handling methods have been generated, such as the model predictive control [2, 6], the set invariance notions [7, 8] and reference governors [9, 10].”
Robust control of uncertain discrete-time Markovian jump systems with actuator saturation (2006, methodology): “For further development, we recall some important notations and results which have been given in Hu and Lin ( 2001 ), Cao et al .”