2 edition of **Quadratic optimal control of a two-flexible-link robot manipulator** found in the catalog.

Quadratic optimal control of a two-flexible-link robot manipulator

A. S. Morris

- 96 Want to read
- 7 Currently reading

Published
**1995**
by University, Dept. of Control Engineering in Sheffield
.

Written in English

**Edition Notes**

Statement | A.S. Morris and A. Madani. |

Series | Research report / University of Sheffield, Department of Automatic Control and Systems Engineering -- no. 590, Research report (University of Sheffield. Departmentof Automatic Control and Systems Engineering) -- no.590. |

Contributions | Madani, A. |

ID Numbers | |
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Open Library | OL20831793M |

In recent years, much attention has been paid to the use of PID control for robotic manipulators. The survey on PID control for robotic manipulators can be found in references cited therein. In this paper, a PID control scheme is developed and implemented for trajectory tracking problem of two-link robotic manipulator. Linear quadratic optimal control is a collective term for a class of optimal control problems involving a linear input-state-output system and a cost functional that is a quadratic form of the state and the input. The aim is to minimize this cost functional over a given class of input functions.

control of the position of a simpliﬁed vectored thrust aircraft and speed control for an automobile. 1 Linear Quadratic Regulator The ﬁnite horizon, linear quadratic regulator (LQR) is given by x˙ = Ax+Bu x ∈ Rn,u ∈ Rn,x 0 given J˜= 1 2 Z T 0 ¡ x TQx+u Ru ¢ dt+ 1 2 xT(T)P 1x(T) where Q ≥ 0, R > 0, P1 ≥ 0 are symmetric, positive. Sun J and Yong J () Stochastic Linear Quadratic Optimal Control Problems in Infinite Horizon, Applied Mathematics and Optimization, , (), Online publication date: 1-Aug Bertsimas D and Georghiou A () Binary decision rules for multistage adaptive mixed-integer optimization, Mathematical Programming: Series A and B,

This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the s: 5. Equation (29) gives the optimal matrix K. Thus, the optimal control law to the quadratic optimal control problem, when the performance index is given by equation (28) is linear and is given by u(t) = -Kx(t) = R-1B*Px(t) The matrix P in equation (31) must satisfy equation (29) or the following reduced equation.

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Optimal Trajectories for Flexible-Link Manipulator Slewing Using Recursive Quadratic Programming: Experimental Verification Optimal Control of Systems with Hard Control Bounds – 7. Feddema, J. T., Eisler, G. R., and Segalman, D.

J.,“Integration of Model-Based and Sensor-Based Control for a Two-Link Flexible Robot Arm Cited by: 3. The development of a two-flexible-link system controller is therefore very relevant to larger manipulators, because it can be readily expanded by adding simple controllers for the other rigid links.

Two alternative controllers are developed in this paper, a computed-torque controller and a quadratic optimal by: Quadratic Optimal Control of a Two Flexible-Link Robot Manipulator. By A.S. Morris and A. Madani. Get PDF (8 MB) Abstract. This paper is addressed at the problem of controlling a two-flexible-link manipulator system.

Manipulators with some flexible links are attractive if high speed motion is required in manufacturing operations because they Author: A.S. Morris and A. Madani. An optimized Linear Quadratic Regulator is employed to control the manipulator.

After that, a Linear Quadratic Regulator (LQR) controller is used for optimal control of the manipulator. In this paper a new optimal approach to parallel force-position control of robot manipulator is presented.

Parallel control may be needed in situation where we are interest to control. This also led to the development of independent sensor-based quadratic cost-optimal control algorithms for robot manipulators [35].

The influence of flexibility on robot dynamics was first considered in the late s and early s (see, e.g., Book [36]).

The inclusion of the effects of the dynamics of flexibility into the controller design. This work presents the study of linear quadratic regulator control strategy for a flexible single-link robotic manipulator.

The dynamic modeling and step input tracking control. This book describes a novel quadratic programming approach to solving redundancy resolutions problems with redundant manipulators.

Known as ``QP-unified motion planning and control. Dawson, Grabbe and Lewis () used a general control law known as modified computed torque control (MCTC) and quadratic optimal control theory to derive a parameterized proportional-derivative (PD) form for an auxiliary input to the controller.

However, in actual situations, the robot dynamics is rarely completely known, and it is thus. An implicit force control scheme for flexible link manipulators is considered in this article.

The control output is composed of a feedforward and a feedback term. The feedforward torque component compensates the underlying rigid arm dynamics along the desired trajectory.

Optimal linear quadratic regulator, (LQR) control. It is a model based control technique. The optimal performances are the main advantages of this technique. The general design structure of this control technique is given in to minimize the cost function and to find a gain matrix given by.

paper: linear-quadratic optimal control with integral quadratic constraints. OPTIMAL CONTROL APPLICATIONS AND METHODS Optim. Control Appl. Meth., 20, (). The theory of optimal control is concerned with operating a dynamic system at minimum cost.

The case where the system dynamics are described by a set of linear differential equations and the cost is described by a quadratic function is called the LQ problem. One of the main results in the theory is that the solution is provided by the linear–quadratic regulator (LQR), a feedback.

Control methods for two-link ﬂexible manipulators are developed using energy-based nonlinear con-trol [4, 13], neural adaptive control [13], and iterative learning control [9].

Other controller designs for two-link ﬂexible systems can be found in references herein. The book. Quadratic programming for inverse kinematics control of a hexapod robot with inequality constraints Conference Paper (PDF Available) January.

This paper presents an algorithm for continuous-time quadratic optimization with neural compensation of motion control. A simpler reformulation explicit solution to the Hamilton-Jacobi-Bellman equation for optimal control of rigid robot motion is found by solving an algebraic Riccati matrix equation.

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 manipulators and devices, neural network intelligent control, and implementation of advanced controllers on actual robotic systems.

Select the appropriate positive constants; then the robust quadratic stabilization tracking control law can be obtained from Theorem 7. Simulation Results. In this section, the proposed control approach is applied to control a two-link manipulator.

The dynamic equation and parameters of the manipulator are similar to those in. hierarchical control on robotic manipulator using fuzzy logic [3]. Bannerjee, et al have used a Fuzzy Logic Controller to achieve position control of a two-link manipulator [4].

Adams, et al [5] have used GA to optimize the membership functions and rule bases of a multi-stage fuzzy PID controller with a fuzzy switch ror robot control. Abstract. Mechanical flexibility in robot manipulators is due to compliance at the joints and/or distributed deflection of the links.

Dynamic models of the two classes of robots with flexible joints or flexible links are presented, together with control laws addressing the motion tasks of regulation to constant equilibrium states and of asymptotic tracking of output trajectories.

Optimal Control Theory (book chapter) Rotating objects using quaternions (online tutorial) R. Stengel, Optimal Control and Estimation (book) L. Siavicco and B. Siciliano, Modelling and Control of Robot Manipulators (book) Code plotmat.m: visualization of 2-by-2 matrices.The Nonlinear Feedback method of robot control is an exact linearizing and decoupling control algorithm based on Differetial Geometric Control Theory.

It is a Task Servo scheme. In this paper experimental results of the trajectory tracking performance of the Nonlinear Feedback based task servo controller on a PUMA manipulator is presented.A dynamic model for flexible manipulator using the Timoshenko beam theory is derived and µ-synthesis control design technique is used to synthesize the robot manipulator [1].

Uncertain system can also be analysed and controlled by the Adaptive control [2] and Robust control [3], [4] .