Robust Control of Nonlinear Systems Using Neural Networks

Robust Control of Nonlinear Systems Using Neural Networks PDF Author: Xiang Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 99

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Book Description

Robust Control of Nonlinear Systems Using Neural Networks

Robust Control of Nonlinear Systems Using Neural Networks PDF Author: Xiang Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 99

Get Book Here

Book Description


Differential Neural Networks for Robust Nonlinear Control

Differential Neural Networks for Robust Nonlinear Control PDF Author: Alexander S. Poznyak
Publisher: World Scientific
ISBN: 9789812811295
Category : Science
Languages : en
Pages : 464

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Book Description
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.

Robust Control for Nonlinear Time-Delay Systems

Robust Control for Nonlinear Time-Delay Systems PDF Author: Changchun Hua
Publisher: Springer
ISBN: 9811051313
Category : Technology & Engineering
Languages : en
Pages : 301

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Book Description
This book reports on the latest findings concerning nonlinear control theory and applications. It presents novel work on several kinds of commonly encountered nonlinear time-delay systems, including those whose nonlinear terms satisfy high-order polynomial form or general nonlinear form, those with nonlinear input or a triangular structure, and so on. As such, the book will be of interest to university researchers, R&D engineers and graduate students in the fields of control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of nonlinear time-delay systems.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

Neural Network Control Of Robot Manipulators And Non-Linear Systems PDF Author: F W Lewis
Publisher: CRC Press
ISBN: 9780748405961
Category : Technology & Engineering
Languages : en
Pages : 470

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Book Description
There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.

Robust Control Design for Sampled Data and Nonlinear Systems Using Fuzzy-neural Networks

Robust Control Design for Sampled Data and Nonlinear Systems Using Fuzzy-neural Networks PDF Author: Tsung-Chih Lin
Publisher:
ISBN:
Category :
Languages : en
Pages :

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How Can Robust Control of Nonlinear Systems be Achieved? Examining Optimization Techniques

How Can Robust Control of Nonlinear Systems be Achieved? Examining Optimization Techniques PDF Author: Bhawna Tandon
Publisher: GRIN Verlag
ISBN: 3346038653
Category : Technology & Engineering
Languages : en
Pages : 170

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Book Description
Doctoral Thesis / Dissertation from the year 2019 in the subject Engineering - General, Basics, grade: A.00, , language: English, abstract: The following text examines the questions, how nonlinear system can better be controlled by new optimisation techniques such as feedback linearization. Due to the inevitable nonlinearities in real systems, several nonlinear control methods like feedback linearization, sliding mode control, backstepping approach and further modes are described in detail in the literature. Due to limitations in application of well known classical methods, researchers have struggled for decades to realize robust and practical solutions for nonlinear systems by proposing different approaches or improving classical control methods. The feedback linearization approach is a control method which employs feedback to stabilize systems containing nonlinearities. In order to accomplish this, it assumes perfect knowledge of the system model to linearize the input-output relationship. In the absence of perfect system knowledge, modelling errors inevitably affect the performanceof the feedback controller. Many researchers have come up with a new form of feedback linearization, called robust feedback. This method gives a linearizing control law that transforms the nonlinear system into its linear approximation around an operating point. Thus, it causes only a small transformation in the natural behavior of the system, which is desired in order to obtain robustness. The controllers are required to provide various time domain and frequency domain performances while maintaining sufficient stability robustness. In this regard, the evolutionary optimization techniques provide better option as these are probabilistic search procedures and facilitate inclusion of wide variety of time and frequency domain performance functionals in the objective functions. A significant scope of work remains to be done which provides motivation for the research in the design of robust controllers using evolutionary optimization. Also, emerging techniques using LMI also find potential in controller design for feedback linearized systems.The thrust of the study here is to design robust controllers for nonlinear systems using Evolutionary optimization and LMI. Furthermore, latest control methods for nonlinear system have been studied, deeply, in this thesis. Combining feedback linearization with non linear disturbance observer based control (NDOBC) obtains promising disturbance rejection and reference tracking performance as compared to other robust control methods.

Robust and Fault-Tolerant Control

Robust and Fault-Tolerant Control PDF Author: Krzysztof Patan
Publisher: Springer
ISBN: 303011869X
Category : Technology & Engineering
Languages : en
Pages : 209

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Book Description
Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.

Applications of Nonlinear Control

Applications of Nonlinear Control PDF Author: Meral Altınay
Publisher: BoD – Books on Demand
ISBN: 9535106562
Category : Science
Languages : en
Pages : 216

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Book Description
A trend of investigation of Nonlinear Control Systems has been present over the last few decades. As a result the methods for its analysis and design have improved rapidly. This book includes nonlinear design topics such as Feedback Linearization, Lyapunov Based Control, Adaptive Control, Optimal Control and Robust Control. All chapters discuss different applications that are basically independent of each other. The book will provide the reader with information on modern control techniques and results which cover a very wide application area. Each chapter attempts to demonstrate how one would apply these techniques to real-world systems through both simulations and experimental settings.

Recent Advances in Robust Control

Recent Advances in Robust Control PDF Author: Andreas Müller
Publisher: BoD – Books on Demand
ISBN: 953307339X
Category : Science
Languages : en
Pages : 478

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Book Description
Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics.

Dynamic Neural Network-based Robust Control Methods for Uncertain Nonlinear Systems

Dynamic Neural Network-based Robust Control Methods for Uncertain Nonlinear Systems PDF Author: Huyen T. Dinh
Publisher:
ISBN:
Category :
Languages : en
Pages : 114

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Book Description
This result is achieved by combining the DNN-identification strategy with a RISE (Robust Integral of the Sign of the Error) controller. In Chapters 4 and 5, a class of second-order uncertain nonlinear systems with partially unmeasurable states is considered. A DNN-based observer is developed to estimate the missing states in Chapter 4, and the DNN-based observer is developed for an output feedback (OFB) tracking control method in Chapter 5. In Chapter 6, an OFB control method is developed for uncertain nonlinear systems with time-varying input delays. In all developed approaches, weights of the DNN can be adjusted on-line: no off-line weight update phase is required. Chapter 7 concludes the proposal by summarizing the work and discussing some future problems that could be further investigated.