On upper estimate of anisotropic norm of uncertain system with application to stochastic robust control

2017 ◽  
Vol 91 (11) ◽  
pp. 2411-2421 ◽  
Author(s):  
M. M. Tchaikovsky ◽  
A. P. Kurdyukov
Keyword(s):  
Robust Control ◽  
Uncertain System ◽  
Anisotropic Norm ◽  
Upper Estimate ◽  
Stochastic Robust Control

scholarly journals Adaptive Critic Learning-Based Robust Control of Systems with Uncertain Dynamics

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jun Zhao ◽  
Qingliang Zeng ◽  
Bin Guo
Keyword(s):  
Optimal Control ◽  
Robust Control ◽  
Control Problem ◽  
Control Method ◽  
System Modeling ◽  
Uncertain System ◽  
Nonsmooth Dynamics ◽  
Adaptive Critic ◽  
Uncertain Dynamics ◽  
Critic Neural Network

Model uncertainties are usually unavoidable in the control systems, which are caused by imperfect system modeling, disturbances, and nonsmooth dynamics. This paper presents a novel method to address the robust control problem for uncertain systems. The original robust control problem of the uncertain system is first transformed into an optimal control of nominal system via selecting the appropriate cost function. Then, we develop an adaptive critic leaning algorithm to learn online the optimal control solution, where only the critic neural network (NN) is used, and the actor NN widely used in the existing methods is removed. Finally, the feasibility analysis of the control algorithm is given in the paper. Simulation results are given to show the availability of the presented control method.

The H∞ Robust Control of Global Supply Chain System Based on Demand and Time Uncertainty

2013 ◽  
Vol 442 ◽  
pp. 623-627
Author(s):  
Qi Zhang ◽  
Yi Hong Ru
Keyword(s):  
Supply Chain ◽  
Robust Control ◽  
Simulation Analysis ◽  
Uncertain System ◽  
Global Supply Chain ◽  
Supply Chain System ◽  
Chain System ◽  
Long Run ◽  
Set Up ◽  
Cooperation System

The H robust control problem of linear uncertain system is studied in this article. With international business has expanded largely in all areas of the world, some problems have also appeared in the global supply chain system. The causes of these problems are mostly from the demand and time uncertainties, so we set up a dynamic cooperation system model to reflect these uncertainties. In a further way, we propose the H robust control strategy and LMI algorithm to reduce the uncertainty influences. And using of SIMILINK tool to make simulation analysis of the system is shown at the end of this paper. Through the setback control of inventory state to restrain the disturbance of uncertain factors, we can achieve an ideal state of global supply chain system in the long run.

Adaptive Robust Control for a Class of Nonlinear Uncertain System With Unknown Input Backlash

2009 ◽  
Author(s):  
Jian Guo ◽  
Bin Yao ◽  
Jun Jiang ◽  
Qingwei Chen
Keyword(s):  
Robust Control ◽  
Nonlinear Dynamic System ◽  
Uncertain System ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Unknown Input ◽  
Uncertain Disturbances ◽  
On Line ◽  
Parameterized Model ◽  
Robust Adaptive

An adaptive robust control (ARC) algorithm is developed for a class of nonlinear dynamic system with unknown input backlash, parametric uncertainties and uncertain disturbances. Due to the non-smooth dynamic nonlinear nature of backlash, existing robust adaptive control methods mainly focus on using approximate inversion of backlash by on-line parameter adaptation. But experimental results show that a linear controller alone can perform better than a controller including the selected backlash inverter with a correctly estimated or overestimated backlash gap. Unlike many existing control schemes, the backlash inverse is not constructed in this paper. A new linearly parameterized model for backlash is presented. The backlash nonlinearity is linearly parameterized globally with bounded model error. The proposed adaptive robust control law ensure that all closed-loop signals are bounded and achieves the tracking within the desired precision. Simulations results illustrate the performance of the ARC.

scholarly journals Robust Control Design for an Uncertain Macroeconomic Dynamical System with Unknown Characteristics and Inequality Control Constraint

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaorui Xie ◽  
Ye-Hwa Chen
Keyword(s):  
Dynamical System ◽  
Robust Control ◽  
Design Procedure ◽  
Control Design ◽  
Uniform Boundedness ◽  
Salient Feature ◽  
Uncertain System ◽  
Stabilization Policy ◽  
Bounded Controls ◽  
Robust Control Design

The stabilization problem of a macroeconomic dynamical system is considered in this paper. The main features of this system are that the system uncertainties may be unknown functions of state and time but with known bounds. Furthermore, the control inputs are subject to constraints, which is a salient feature in an economic control problem. To ensure that the controls are within the specified boundaries, in our control design procedure, a creative diffeomorphism, which converts bounded controls into unbounded corresponding signals by choosing an appropriate transformation function, is proposed. For the uncertain system, a deterministic robust control is designed to render the practical stability: uniform boundedness and uniform ultimate boundedness. The range of the input bounds is related to the uncertainties and can be designed according to the actual situation. Numerical simulations are performed to verify the effectiveness of the stabilization policy.

Parameter estimation and upper bounding adaptation in adaptive-robust control approaches for trajectory control of robots

Robotica ◽  
2002 ◽  
Vol 20 (6) ◽  
pp. 653-660 ◽  
Author(s):  
Ibrahim Uzmay ◽  
Recep Burkan
Keyword(s):  
Parameter Estimation ◽  
Adaptive Control ◽  
Robust Control ◽  
Uncertain System ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Lyapunov Theory ◽  
Control Law ◽  
Control Input

In this paper a new robust adaptive control law for n-link robot manipulators with parametic uncertainties is derived using the Lyapunov theory thus guaranteed the stability of an uncertain system. The novelty of the adaptive robust control algorithm is that manipulator parameters and adaptive upper bounding functions are estimated to control the system properly, and the adaptive robust control law is also updated as an exponential function of manipulator kinematics, inertia parameters and tracking errors. The proposed adaptive control input includes a parameter estimation law as an adaptive controller and an additional control input vector as a robust controller. The developed approach has the advantages of both adaptive and robust control laws, without their discolour tags.

Robust Control for Constrained Robot Manipulators

1999 ◽  
Vol 121 (1) ◽  
pp. 129-133 ◽  
Author(s):  
F. Mnif ◽  
E. K. Boukas ◽  
M. Saad
Keyword(s):  
Robust Control ◽  
Asymptotic Stability ◽  
Uniform Boundedness ◽  
Uncertain System ◽  
Control Law ◽  
Parametric Uncertainties ◽  
Feedback Controls ◽  
Constraint Force ◽  
Continuous Feedback ◽  
Constrained Robot

In this paper, a robust control law for constrained manipulators with parametric uncertainties is derived. Two schemes are presented; the first, based on The Corless-Leitmann approach, will guarantee ultimate uniform stability of the system, and hence uniform boundedness errors convergence. As a second approach, a class of continuous feedback controls is proposed to guarantee asymptotic stability of the uncertain system. The analysis is based on a theoretical result of asymptotic stability. In this approach, due to the continuity of the control and asymptotic stability of the system, we can achieve acceleration convergence and, thus, constraint force convergence.

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