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Tuesday, July 14, 2020 | History

3 edition of Robust tuning of robot control systems (grant #NAG 5 1550) found in the catalog.

Robust tuning of robot control systems (grant #NAG 5 1550)

Robust tuning of robot control systems (grant #NAG 5 1550)

final report / I. Minis (P.I.), M. Uebel.

  • 212 Want to read
  • 23 Currently reading

Published by National Aeronautics and Space Administration, National Technical Information Service, distributor in [Washington, DC, Springfield, Va .
Written in English

    Subjects:
  • Robots -- Control systems.

  • Edition Notes

    SeriesNASA contractor report -- NASA CR-190131.
    ContributionsUebel, M., United States. National Aeronautics and Space Administration.
    The Physical Object
    FormatMicroform
    Pagination1 v.
    ID Numbers
    Open LibraryOL15368815M

      Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance. robust control behavior, and significant control tuning effort is required as soon as these elements are introduced. Another drawback of conventional control methods is their lack of First three authors contributed equally, 1 Siemens Corporation, 2 University of California, Berkeley, 3 Hamburg University of Technology. behavior generalization.

    In control theory, robust control is an approach to controller design that explicitly deals with uncertainty. Robust control methods are designed to function properly provided that uncertain parameters or disturbances are found within some (typically compact) methods aim to achieve robust performance and/or stability in the presence of bounded modelling errors. Robot Dynamics and Control This chapter presents an introduction to the dynamics and control of robot manipulators. We derive the equations of motion for a general open-chain manipulator and, using the structure present in the dynam-ics, construct control laws .

    Elements of Feedback Control Systems Servomechanism, Regulator, and Process Control Continuous and Discontinuous Operation of Automatic Control Systems 3. Analysis and Design of Feedback Control Systems Describing the Dynamical Behavior of Systems Performance Objectives Controller Design Non-Standard Types of.   Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls Reviews: 1.


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Robust tuning of robot control systems (grant #NAG 5 1550) Download PDF EPUB FB2

In recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic Control Systems with Genetic Algorithms builds a bridge between genetic.

The aim of this book is to present the theoretical and practical aspects of embedded robust control design and implementation with the aid of MATLAB® and SIMULINK®. It covers methods suitable for practical implementations, combining knowledge from control system design and computer engineering to describe the entire design by: 2.

Get this from a library. Robust tuning of robot control systems (grant #NAG 5 ): final report. [I Minis; M Uebel; United States. National Aeronautics and Space Administration.].

The control strategy is illustrated for three quadrotors carrying two sections of a hose, but the model can be easily expanded to a bigger number of quadrotors system, due to the approach modularity.

Experiments demonstrate the PSO tuning method convergence, which is fast. More than one solution is possible, and control is very by: 9. The book incorporates many new results and techniques fordesigning adaptive-control systems, and derives many previously known results in novel ways that simplify and lend new insights to the theory.

Three nonlinear systems, including a one-link robot, an induction motor, and a rigid-link flexible-joint robot, were used to demonstrate the effectiveness of the proposed scheme. Published in: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

A new analytic tuning method of fractional order controller is developed in the aim to ensure stability and robustness. After the controller tuning a fractional order prefilter is designed and optimized to reach the desired performances.

The proposed method effectiveness will be tested and evaluated based on a real robot. Tuning Fuzzy Logic Controllers for Robust Control System Design, and GA-Fuzzy Hierarchical Control Design Approach are presented in chapters 6 and 7, respectively.

Topics covered in these sections include genetic tuning of fuzzy control systems, fuzzy control system design – for example, study applications of Gas for fuzzy control, and. This paper presents a novel design of a robust visual tracking control system, which consists of a visual tracking controller and a visual state estimator.

This system facilitates human-robot interaction of a unicycle-modeled mobile robot equipped with a tilt camera. Based on a novel dual-Jacobian visual interaction model, a dynamic motion target can be tracked using a single visual tracking. LQ control is a well known optimal control for linear systems without uncertainties.

In this paper, however, an adaptive control scheme is proposed for robot manipulators with LQ performance. This book brings together some of the latest research in robot applications, control, modeling, sensors and algorithms.

Consisting of three main sections, the first section of the book has a focus on robotic surgery, rehabilitation, self-assembly, while the second section offers an insight into the area of control with discussions on exoskeleton control and robot learning among others.

The. This book explores the implementation of MATLAB(R) and Simulink(R) in the development of embedded robust control systems.

Robust control theory allows for changes in a system whilst maintaining stability and performance. Applications of this technique are very important for dependable embedded systems, making technologies such as drones and.

ROBUST TUNING OF ROBOT CONTROL SYSTEMS (Grant # NAG 5 ) FINAL REPORT I. Minis (P.I.), M. Uebel Department of Mechanical Engineering University of Maryland, Baltimore County Campus Baltimore, MD Sponsored by: The Robotics Branch, NASA GSFC Funding Period: May 1, - Ap (NASA-CR) ROBUST TUNING OF ROBOT N robust control of cooperative robotic manipulators.

In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system.

They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation.

This paper presents a calibration approach of a manipulator robot controller using an auto-tuning technique.

Since the industry requires machines to run with increasing speed and precision, an optimal controller is too demanding. Even though the robots make use of an internal controller, usually, this controller does not fulfill the user specification with respect to their applications.

Visual robot control or visual servoing is a feedback control methodology that uses one or more vision sensors (cameras) to control the motion of the robot. Specifically, the control inputs for the robot motors are produced by processing image data (typically, extraction of contours, features, corners, and other visual primitives).

Single Robust Proportional-Derivative Control for Friction Compensation in Fast and Precise Motion Systems With Actuator Constraint. Chunhong Zheng, Chunhong Zheng. The result is a robust and flexible robot control system.

The system is intended to control a robot that wanders the office areas of our laboratory, building maps of its surroundings. In this paper we demonstrate the system controlling a detailed simulation of the robot. Sathyan, A. and Ma, O., “Collaborative Control of Multiple Robots Using Genetic Fuzzy Systems Approach,” In: ASME Dynamic Systems and Control Conference, American Society of Mechanical Engineers () p.

VT03A desired trajectories of motion, or desired exerted forces. Thus, the control system lifts the robot up a level in a hierarchy of abstraction. This book is intended to provide an in-depth study of control systems for serial-link robot arms.

It is a revised and expended version of our book. Chapters have been added on commercial robot. Today, robot control systems are highly advanced with integrated force and vision systems. Mobile robots, underwater and flying robots, robot networks, surgical robots, and others are playing increasing roles in society.

Robots are also ubiquitous as educational tools in K and college freshman experience courses. The Early Years. Robust control of a spatial robot using fuzzy sliding modes.

To control a cart-pole system, tuning the sliding surface slope and control gain of the sliding mode controller at the same time makes the present paper different from the works published in literature. 2. Spatial robot.Currently, there are many research studies on robust control of robots such as Rigatos et al.

have proposed the adaptive controller for controlling the robotic manipulators, Zhang et al. applied the controller to drive the underwater vehicle, Makarov et al.

have proposed a control scheme for motion control of multiple-link elastic-joint robots.