Control Design for a Clas of Unstable Nonlinear Systems with Input Constraint

Control Design for a Clas of Unstable Nonlinear Systems with Input Constraint PDF Author: Pai-Hsueh Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 212

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Control Design for a Clas of Unstable Nonlinear Systems with Input Constraint

Control Design for a Clas of Unstable Nonlinear Systems with Input Constraint PDF Author: Pai-Hsueh Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 212

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Book Description


Iterative Learning Control

Iterative Learning Control PDF Author: Hyo-Sung Ahn
Publisher: Springer Science & Business Media
ISBN: 1846288592
Category : Technology & Engineering
Languages : en
Pages : 237

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Book Description
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

Model Predictive Control Approach Based Sliding Mode Controller Design and Input Constraint for a Class of Chaotic Nonlinear Systems with Mismatched Disturbance

Model Predictive Control Approach Based Sliding Mode Controller Design and Input Constraint for a Class of Chaotic Nonlinear Systems with Mismatched Disturbance PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Analysis and Design of Nonlinear Control Systems

Analysis and Design of Nonlinear Control Systems PDF Author: Alessandro Astolfi
Publisher: Springer Science & Business Media
ISBN: 3540743588
Category : Technology & Engineering
Languages : en
Pages : 485

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Book Description
This book is a tribute to Prof. Alberto Isidori on the occasion of his 65th birthday. Prof. Isidori’s proli?c, pioneering and high-impact research activity has spanned over 35 years. Throughout his career, Prof. Isidori has developed ground-breaking results, has initiated researchdirections and has contributed towardsthe foundationofnonlinear controltheory.In addition,his dedication to explain intricate issues and di?cult concepts in a simple and rigorous way and to motivate young researchers has been instrumental to the intellectual growth of the nonlinear control community worldwide. The volume collects 27 contributions written by a total of 52 researchers. The principal author of each contribution has been selected among the - searchers who have worked with Prof. Isidori, have in?uenced his research activity, or have had the privilege and honour of being his PhD students. The contributions address a signi?cant number of control topics, including th- retical issues, advanced applications, emerging control directions and tutorial works. The diversity of the areas covered, the number of contributors and their international standing provide evidence of the impact of Prof. Isidori in the control and systems theory communities. The book has been divided into six parts: System Analysis, Optimization Methods, Feedback Design, Regulation, Geometric Methods and Asymptotic Analysis, re?ecting important control areas which have been strongly in- enced and, in some cases, pioneered by Prof. Isidori.

Data-driven Nonlinear Control Designs for Constrained Systems

Data-driven Nonlinear Control Designs for Constrained Systems PDF Author: Roland Harvey
Publisher:
ISBN:
Category :
Languages : en
Pages : 105

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Book Description
Systems with nonlinear dynamics are theoretically constrained to the realm of nonlinear analysis and design, while explicit constraints are expressed as equalities or inequalities of state, input, and output vectors of differential equations. Few control designs exist for systems with such explicit constraints, and no generalized solution has been provided. This dissertation presents general techniques to design stabilizing controls for a specific class of nonlinear systems with constraints on input and output, and verifies that such designs are straightforward to implement in selected applications. Additionally, a closed-form technique for an open-loop problem with unsolvable dynamic equations is developed. Typical optimal control methods cannot be readily applied to nonlinear systems without heavy modification. However, by embedding a novel control framework based on barrier functions and feedback linearization, well-established optimal control techniques become applicable when constraints are imposed by the design in real-time. Applications in power systems and aircraft control often have safety, performance, and hardware restrictions that are combinations of input and output constraints, while cryogenic memory applications have design restrictions and unknown analytic solutions. Most applications fall into a broad class of systems known as passivity-short, in which certain properties are utilized to form a structural framework for system interconnection with existing general stabilizing control techniques. Previous theoretical contributions are extended to include constraints, which can be readily applied to the development of scalable system networks in practical systems, even in the presence of unknown dynamics. In cases such as these, model identification techniques are used to obtain estimated system models which are guaranteed to be at least passivity-short. With numerous analytic tools accessible, a data-driven nonlinear control design framework is developed using model identification resulting in passivity-short systems which handles input and output saturations. Simulations are presented that prove to effectively control and stabilize example practical systems.

Robust Nonlinear Control Design

Robust Nonlinear Control Design PDF Author: Randy Freeman
Publisher: Springer Science & Business Media
ISBN: 9780817647582
Category : Science
Languages : en
Pages : 276

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Book Description
This softcover book summarizes Lyapunov design techniques for nonlinear systems and raises important issues concerning large-signal robustness and performance. The authors have been the first to address some of these issues, and they report their findings in this text. The researcher who wishes to enter the field of robust nonlinear control could use this book as a source of new research topics. For those already active in the field, the book may serve as a reference to a recent body of significant work. Finally, the design engineer faced with a nonlinear control problem will benefit from the techniques presented here.

Introduction to Nonlinear Control

Introduction to Nonlinear Control PDF Author: Christopher M. Kellett
Publisher: Princeton University Press
ISBN: 0691240485
Category : Mathematics
Languages : en
Pages : 551

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Book Description
"This will be the first textbook on nonlinear control at the upper undergraduate level, reflecting the many updates in the field that have occurred since the 1990s. Nonlinear control is a control engineering course usually taught at the graduate level and preceded by a full semester course on nonlinear systems analysis, yet - as the authors of this textbook argue -- these tools and techniques are accessible to an undergraduate audience and practicing engineers, if presented in the right way. This book is class-tested, growing out of a third-year undergraduate course on nonlinear control and estimation for mechatronics, mechanical and electrical engineering, and mathematics students at the University of Newcastle, Australia. It is part of a trend toward reimagining the content of undergraduate control engineering curricula, to render widely-used tools and techniques accessible to students much earlier in their education, opening them up to those who will not go on to the graduate level. This alternative course sequence currently begins with the text Feedback Systems: An Introduction for Scientists and Engineers by Aström and Murray (PUP 2008); this new project is designed to follow Aström and Murray in the undergraduate sequence, as a second or third year course"--

Control Systems with Input and Output Constraints

Control Systems with Input and Output Constraints PDF Author: A.H. Glattfelder
Publisher: Springer Science & Business Media
ISBN: 1447100476
Category : Technology & Engineering
Languages : en
Pages : 511

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Book Description
From the reviews: [The authors] "...have succeeded in their intention to produce the first reference in the area that will be available for a broad audience. I think that this book will be a standard reference for a long time." Control Engineering Practice

Optimization-based Feedback Control of Nonlinear Systems Subject to Input Constraints

Optimization-based Feedback Control of Nonlinear Systems Subject to Input Constraints PDF Author: Dimitrios Stylianos Parsinas Pylorof
Publisher:
ISBN:
Category :
Languages : en
Pages : 266

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Book Description
In this work, we are studying and solving feedback control problems for input constrained nonlinear systems under the influence of uncertainty. Our results are developed by fusing fundamental Lyapunov stability concepts with tools and techniques from the field of convex optimization that enable the derivation of computationally efficient control laws accompanied by robust stabilization guarantees. When a nonlinear control system is subject to input constraints, a critical aspect of the stabilization problem with simple control laws based on a particular Control Lyapunov Function (CLF) is to characterize a subset of the state space starting from where stabilization to the origin is guaranteed. We consider polynomial systems which are affine in a control input constrained in a convex and compact polytope. We propose two alternative analysis methods that ultimately yield sufficient conditions for asymptotic stabilization under such input constraints and provide an estimate of the stabilization set for the system and the given CLF. Both methods relax the problem to the solution of Sum-of-Squares programs, which nominally can be cast as Semidefinite Programs that are solvable with interior point algorithms. Given a particular CLF, it is also possible to sequentially optimize over its coefficients to the end of reshaping or enlarging the stabilization set, and thus, favorably altering the set of initial conditions from where the control objectives can be attained. A class of constrained control laws based on a particular CLF is shown to attain values equal to the minimizer of a Quadratic Program (QP), which is guaranteed to remain feasible along any closed loop trajectory emanating from the stabilization set. The input constraints are always respected and the closed loop system is rendered asymptotically stable. Additionally, such a QP is of a rather low dimension and can be solved efficiently, enabling the embedded implementation of the proposed control laws even on resource-constrained computational platforms. For the case of systems subject to unknown, bounded uncertainties that enter the dynamics in an affine way, the aforedescribed results are extended to provide robust stabilization subject to input constraints. With the proposed methods, the min-max conditions typically encountered in Lyapunov methods with Robust CLFs (RCLFs) for such systems are handled in both the (R)CLF analysis and the feedback control problem. Therefore, one can estimate a subset of the robust stabilization set with SOS programming and, subsequently, calculate - online - the stabilizing control inputs using state feedback to render the system robustly practically stable. An often encountered challenge in nonlinear control design and implementation is the large dimension of the underlying system, often resulting from the interconnection of multiple subsystems which interact with each other. The concept of Vector (Control) Lyapunov functions allows studying or warranting the applicable stability notion by focusing at the subsystem level and the respective subsystem-to-subsystem interactions. We are leveraging the premise of VCLF methods with our results on the robust stabilization problem to enable the solution of the input constrained robust stabilization problem for large scale systems, either in a distributed or a decentralized way (or in a combination of both), depending on whether state information is exchanged between interacting subsystems or not. Lastly, we examine how uncertainty in the measurements of the system can affect the stabilization problem under input constraints. We propose a control framework with which one can steer a system to a neighborhood of the origin using only imperfect state feedback. The latter is achieved by enforcing a causality relationship between stabilizing the system from the point of view of an imperfect feedback control law and stabilizing the actual system. Ultimately, we use control laws based, again, on the minimizer of simple QPs, to provingly achieve the robust stabilization objective in a subset of the measurement space which is characterized by solving a sequence of SOS programming problems. For the case where only imperfect measurements either of a subset of the state vector of the system or of a linear combination of state vector components are available, we propose an extension of Lyapunov-based nonlinear observer design results from the literature to account for uncertainty in the dynamics and the measurement equation. The robust observer synthesis process takes place through SOS programming and produces observers with explicit performance guarantees with regards to the behavior of the state determination error. The factors considered in this work are relevant to contemporary safety-critical control applications; nonlinearity, input constraints, uncertainty, and the need for embeddability and low footprint implementation are ubiquitous in control problems across fields ranging from robotics to industrial engineering, space exploration and cyber-physical systems. The proposed methods aim to collectively provide a theoretically sound, algorithmically implementable and practically useful framework to study and tackle challenging control problems

Computer-aided Nonlinear Control System Design

Computer-aided Nonlinear Control System Design PDF Author: Amir Nassirharand
Publisher: Springer Science & Business Media
ISBN: 144712149X
Category : Technology & Engineering
Languages : en
Pages : 189

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Book Description
A systematic computer-aided approach provides a versatile setting for the control engineer to overcome the complications of controller design for highly nonlinear systems. Computer-aided Nonlinear Control System Design provides such an approach based on the use of describing functions. The text deals with a large class of nonlinear systems without restrictions on the system order, the number of inputs and/or outputs or the number, type or arrangement of nonlinear terms. The strongly software-oriented methods detailed facilitate fulfillment of tight performance requirements and help the designer to think in purely nonlinear terms, avoiding the expedient of linearization which can impose substantial and unrealistic model limitations and drive up the cost of the final product. Design procedures are presented in a step-by-step algorithmic format each step being a functional unit with outputs that drive the other steps. This procedure may be easily implemented on a digital computer with example problems from mechatronic and aerospace design being used to demonstrate the techniques discussed. The author’s commercial MATLAB®-based environment, available separately from insert URL here, can be used to create simulations showing the results of using the computer-aided control system design ideas characterized in the text. Academic researchers and graduate students studying nonlinear control systems and control engineers dealing with nonlinear plant, particularly mechatronic or aerospace systems will find Computer-aided Nonlinear Control System Design to be of great practical assistance adding to their toolbox of techniques for dealing with system nonlinearities. A basic knowledge of calculus, nonlinear analysis and software engineering will enable the reader to get the best from this book.