Improved Lyapunov-based decentralized adaptive controller

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Adaptive control systems., Manipulators (Mechanism)., Lyapunov funct
Statementby Reza A. Dai.
The Physical Object
Pagination49 leaves, bound :
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Open LibraryOL15195468M

A successful controller design is crucial for establishing and maintaining an optical link between free-space communication stations engaged in a laser com Lyapunov-based decentralized adaptive control for laser beam tracking systems - IEEE Journals & Magazine.

Nonlinear Dynamical Systems and Control presents and develops an extensive treatment of stability analysis and control design of nonlinear dynamical systems, with an emphasis on Lyapunov-based methods. Dynamical system theory lies at the heart of mathematical sciences and engineering.

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The application of dynamical systems has crossed interdisciplinary boundaries from chemistry to Cited by: Lyapunov-Based Decentralized Adaptive Control for Laser Beam Tracking Systems Article in IEEE Transactions on Aerospace and Electronic Systems 39(4) - November with 13 Reads.

Abstract. Graduation date: An improved robot manipulator decentralized non-linear adaptive\ud controller that performs well in the presence of disturbances with\ud unknown parameters and non-linearities is presented in this work.\ud The proposed decentralized adaptive structure is a modification of\ud the controller developed by Seraji [] and is characterized by an\ud auxiliary signal.

Decentralized adaptive controller, which is synthesized based on improved Lyapunov-based Model Reference Adaptive Control (MRAC) technique, is suggested to solve the problem. The controllers consist of proportional derivative terms plus auxiliary term with variable coefficient.

systems. besides, lyapunov based controller design (obtaining the adaptation laws using direct lyapunov method) is considered only for the linear case in [6,10].

To the best of our knowledge, lyapunov based model reference adaptive controller design for a class of nonlinear n-Author: Seyed Mohammad Moein Mousavi, Mohammad T.

Beheshti, Amin Ramezani. Barrier Lyapunov function-based decentralized adaptive neural control for uncertain high-order stochastic nonlinear interconnected systems with output constraints. Author links open overlay panel Wenjie Si a Xunde Dong b.

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and the system stability via Improved Lyapunov-based decentralized adaptive controller book improved generalized uniform dominance was designed in. However, for these control Cited by: 4. A Lyapunov-based adaptive control framework for discrete-time non-linear systems with exogenous disturbances TOMOHISA HAYAKAWAy, WASSIM M.

HADDADy and ALEXANDER LEONESSAz* A direct adaptive non-linear control framework for discrete-time multivariable non-linear uncertain systems with exogenous bounded disturbances is developed. ized adaptive controller for multiple manipulators moving an unknown payload.

Our work applies results from Model Reference Adap-tive Control (MRAC) [20]. Further, our work is related to decentralized adaptive control, wherein adaptive controllers are designed for interconnected systems, as in [21], [22].File Size: 1MB.

This is an im­provement over Ho and Datta (), where the par­tially decentralized adaptive control system with good performance was presented, not totally decentralized.

Remark The same discussion in this section is available to the normal robust adaptive control Author: Takanori Fukao, Hisashi Kashima, Norihiko Adachi.

Decentralized adaptive control. In: Ioannou P.A., Kokotovic P.V. (eds) Adaptive Systems with Reduced Models. Lecture Notes in Control and Information Sciences, vol This item: Adaptive Control: Second Edition (Dover Books on Electrical Engineering) by Karl J.

Astrom Paperback $ Only 11 left in stock (more on the way). Ships from and sold by FREE Shipping on orders over $ Details/5(22).

LYAPUNOV-BASED ROBUST AND ADAPTIVE CONTROL OF NONLINEAR SYSTEMS USING A NOVEL FEEDBACK STRUCTURE By Parag Patre August Chair: Warren E. Dixon Major: Mechanical Engineering The focus of this research is an examination of the interplay between different intelligent feedforward mechanisms with a recently developed continuous robust feedbackFile Size: 3MB.

ized adaptive controller for multiple manipulators moving an unknown payload. Our work applies results from Model Reference Adap-tive Control (MRAC) [19]. Further, our work is related to decentralized adaptive control, wherein adaptive controllers are designed for interconnected systems, as in [20], [21].

Nonlinear Dynamical Systems and Controlpresents and develops an extensive treatment of stability analysis and control design of nonlinear dynamical systems. The adaptive controller constructed in the proof of Theorem consists of a control law u = ~(x, 0) given by (), and an update law 0 = Fz(x,O) with ().

It is of interest to interpret this controller as a certainty equivalence controller. The certainty equivalence approach, prevalent in the adaptive control of linear systems, is not.

The broad field of adaptive control has developed over the past forty years as an effective control methodology for dealing with uncertainty. This accounts for the title of the project, which includes both decentralized control as well a decentralized adaptive control.

Objective of. Parametric and non- parametric uncertainties in the quadrotor model make it difficult to design a controller that works properly in various conditions during flight time. Decentralized adaptive controller, which is synthesized based on improved Lyapunov-based Model Reference Adaptive Control (MRAC) technique, is suggested to solve the problem.

Lyapunov-Based Adaptive Feedback for Spacecraft Planar Relative Maneuvering via Differential Drag. Nanosatellites swarm deployment using decentralized differential drag-based control with communicational constraints.

Acta Astronautica, Vol. Cited by: Improved Lyapunov-Based Decentralized Adaptive Controller." (). Model Reference Adaptive Control of Manipulators. A direct adaptive non-linear control framework for discrete-time multivariable non-linear uncertain systems with exogenous bounded disturbances is developed.

The adaptive non-linear controller addresses adaptive stabilization, disturbance rejection and adaptive tracking. The proposed framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop system; Cited by: Decentralized, Adaptive Coverage Control for Networked Robots Mac Schwager, Daniela Rus∗, and Jean-Jacques Slotine † November, Revised July, Abstract A decentralized, adaptive control law is presented to drive a network of mobile robots to an optimal sensing configuration.

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Improved Lyapunov-Based Decentralized Adaptive Controller I. INTRODUCTION The problem of designing an adequate control system to accurately follow a desired fast trajectory has been of concern to many re-searchers. There are many control techniques for controlling robotic manipulators, and each of these techniques has its own unique impact on.

Decentralized adaptive controller, which is synthesized based on improved Lyapunov-based Model Reference Adaptive Control (MRAC) technique, is suggested to solve the problem. The proposed control scheme does not need knowing the value of any physical parameter for generating appropriate control signals, and retuning the controller is not required for different Cited by: The classical control methods are normally a feedback method relies on monitoring the change in the process variable with respect to the set point and control designed for worst case conditions.

Alternatively, adaptive control strategies are available where controller parameters and/or control structure are modified online as conditions change.

Robust and Adaptive Control Workshop Adaptive Control: Introduction, Overview, and Applications Nonlinear Dynamic Systems and Equilibrium Points • A nonlinear dynamic system can usually be represented by a set of n differential equations in the form: – x is the state of the system – t is time •If f does not depend explicitly on time File Size: 2MB.

Lyapunov-based Safe Policy Optimization for Continuous Control. 01/28/ ∙ by Yinlam Chow, et al. ∙ 6 ∙ share. We study continuous action reinforcement learning problems in which it is crucial that the agent interacts with the environment only through safe policies, i.e., policies that do not take the agent to undesirable situations.

control systems. The book is organized into eleven chapters that include 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. Connected cruise control with delayed feedback and disturbance: An adaptive dynamic programming approach.

Mengzhe Huang; Weinan Gao; Zhong‐Ping Jiang. LYAPUNOV DESIGN Shuzhi Ge Department of Electrical and Computer Engineering, The National University of Singapore, Singapore Keywords: Control Lyapunov Function, Lyapunov Design, Model Reference Adaptive Control, Adaptive Control, Backstepping Design.

Contents 1. Introduction 2. Control Lyapunov Function 3. Lyapunov Design via Lyapunov Equation. G. Hu and W. E. Dixon "Lyapunov-Based Adaptive Visual Servo Tracking Control Using Central Catadioptric Camera," IEEE Multi-Conference on Systems and Control, OctoberSuntec City, Singapore, pp.

An adaptive control is the automatic tuning of feedback controllers [4]. Adaptive control allows operating parameters to be changed continuously in response to a changing environment in order to achieve optimum performance [5]. An adaptive control system is a system where in addition toAuthor: Adam Misbawu, Adjei-Saforo Kwafo Edmund, Ebrahimpanah Shahrouz.Adaptive control is the control method used by a controller which must adapt to a controlled system with parameters which vary, or are initially uncertain.

For example, as an aircraft flies, its mass will slowly decrease as a result of fuel consumption; a control law is needed that adapts itself to .