Robust Safety-Critical Control

Theory, Application and Experiments

Inbunden, Engelska, 2026

AvTengfei Liu,Si Wu,Zhi Liu,Zhong-Ping Jiang

1 939 kr

Kommande

Practical tools and techniques to achieve objectives in safety-critical control This book offers a systematic framework for the safety-critical control of nonlinear uncertain systems, with key contributions such as the development of novel small-gain synthesis and feasible-set reshaping techniques to address interactions between the nominal controlled system and dynamic uncertainties. Incorporating recent advancements in the field, this book showcases the strengths of the proposed framework by tackling key theoretical challenges in safety-critical control across multiple benchmark systems. It further highlights the real-world impact of the developed methods and algorithms through practical applications involving vehicles, quadrotors, and robotic manipulators. All results are supported by laboratory experiments with clear explanations. Written by a team of highly qualified authors, Robust Safety-Critical Control includes: Insights into the challenges of designing controllers that maintain safety while achieving desired objectives, in the presence of uncertainties, nonlinear dynamics, and multiple constraintsA mathematical foundation for robust safety-critical control, presented in the appendices covering quadratic optimization, Lyapunov stability theory, input-to-state stability, and the nonlinear small-gain theoremChapter-by-chapter problem formulations and detailed, rigorous developments of the theory and methods, guiding the reader through the process of addressing the fundamental challengesComprehensive system setups for safety-critical control simulations and experimentsReady-to-use code implementations for key algorithms, including the feasible-reshaping technique and small-gain control methodsRobust Safety-Critical Control is an excellent reference for researchers and graduate students in systems and control, robotics, transportation and AI seeking to expand their knowledge bases. The text is also highly valuable for engineers and practitioners in control engineering, civil and urban engineering, robotics, and manufacturing.

Produktinformation

Utgivningsdatum2026-12-22
FormatInbunden
SpråkEngelska
Antal sidor352
FörlagJohn Wiley & Sons Inc
ISBN9781394400188

Tillhör följande kategorier

Tengfei Liu is a Professor at Northeastern University, China. He has been deeply engaged in developing and applying nonlinear control methods to engineering systems. Si Wu is a Postdoctoral Researcher at the State Key Laboratory of Synthetical Automation for Industrial Processes, Northeastern University, China, and a key contributor to the feasible-set reshaping technique for safety-critical control. Zhi Liu is a PhD student at Northeastern University, China, focusing on developing safety-critical control methods for mechanical systems that fully leverage their inherent energy properties. Zhong-Ping Jiang is an Institute Professor at New York University, USA. He has made seminal contributions to stability theory, nonlinear control, robust adaptive dynamic programming, learning-based control, and their applications to information, mechanical, transportation and biological systems.

Contents1 Introduction1.1 Characterization of Safety for Dynamical Systems1.2 Robust Safety1.3 Safety-Critical Control: A Quadratic Programming Approach1.4 A Practical Scenario of Robust Safety-Critical Control1.5 Challenges1.6 Outline of This Book1.7 Notes 2 Safety-Critical Control Subject to Dynamic Uncertainties: A Nonlinear Small-Gain Approach2.1 Problem Formulation 2.2 Robust Safety-Critical Controller Design 2.3 Interaction Between Velocity Tracking and Safety 2.4 Small-Gain Synthesis for Safety of the Closed-Loop System2.5 Simulation and Experiment 2.6 Notes 3 Safety-Critical Control Under Multiple Constraints: A Feasible-Set Reshaping Technique3.1 Problem Formulation 3.2 Trial of Directly Extending the Safety Margin 3.3 A Feasible-Set Reshaping Technique for Robust Safety-Critical Control 3.4 Interaction Between Velocity Tracking and Safety 3.5 Small-Gain Synthesis for Safety of the Closed-Loop System3.6 Simulation and Experiment 3.7 Notes 4 Safety-Critical Control in Cluttered Environments: Set-Valued Measurement and Feasible-Set Reshaping4.1 Problem Formulation 4.2 A Continuous, Reactive Safety-Critical Controller 4.3 Safety of the Closed-Loop System 4.4 Special Case: An Integrator-Like Mobile Robot 4.5 Simulation and Experiment 4.6 Notes 5 Safety-Critical Control of Multi-Agent Systems: Feasible-Set Reshaping and Nonlinear Small-Gain Synthesis 5.1 Problem Formulation 5.2 Trials with Standard Designs 5.3 Feasible-Set Reshaping and Controller Design 5.4 Properties of the Proposed Design and Proofs 5.5 Small-Gain Analysis for Safety of the Multi-Agent System5.6 Tuning the Safety-Critical Controllers 5.7 Numerical Simulation and Experiment 5.8 Notes 6 Safety-Critical Control of Euler-Lagrange Systems: IncorporatingBarrier and Energy Functions6.1 Problem Formulation 6.2 Outer Loop: Safety-Oriented Controller Design 6.3 Inner Loop: Velocity-Tracking Controller Design 6.4 Safety Verification: Incorporating Barrier and Energy Functions6.5 Numerical Simulation and Experiment 6.6 Notes 7 Safety-Critical Control of Cascade Systems: Towards a ConstructiveControl Framework7.1 Problem Formulation 7.2 Design Ingredient: Plants with Relative Degree One7.3 Design Ingredient: Refined Feasible-Set Reshaping 7.4 Constructive Design for Plants in the Cascade Form 7.5 Experiment: VTOL Taking Off in a Narrow Space 7.6 Notes A Mathematical PreliminariesA.1 Real Vectors and Matrices A.2 Basis and Positive Basis A.3 Sets and Convexity A.4 Continuity, Differentiability and Convexity of Functions A.5 Comparison Functions A.6 Nonsmooth Analysis A.7 Set Invariance B Quadratic ProgrammingB.1 Quadratic Optimisation ProblemsB.2 Lipschitz Continuity of QP Solutions C Lyapunov Stability, Input-to-State Stability, and the NonlinearSmall-Gain TheoremC.1 Lyapunov Stability Theory C.2 Input-to-State Stability C.3 The Nonlinear Small-Gain Theorem