Adaptive linear control of nonlinear systems

1990 ◽  
Vol 35 (11) ◽  
pp. 1253-1257 ◽  
Author(s):  
C. Wen ◽  
D.J. Hill
Keyword(s):  
Nonlinear Systems ◽  
Linear Control

Optimal trajectories and linear control of nonlinear systems

AIAA Journal ◽  
1964 ◽  
Vol 2 (8) ◽  
pp. 1371-1379 ◽  
Author(s):  
ANDREW H. JAZWINSKI
Keyword(s):  
Nonlinear Systems ◽  
Linear Control ◽  
Optimal Trajectories

Vibration Control Applied in a Semi-Active Suspension Using Magneto Rheological Damper and Optimal Linear Control Design

2013 ◽  
Vol 464 ◽  
pp. 229-234 ◽  
Author(s):  
Bruno Sousa Carneiro da Cunha ◽  
Fábio Roberto Chavarette
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Control Design ◽  
Mr Damper ◽  
Active Suspension ◽  
Linear Control ◽  
Linear Feedback ◽  
Optimal Linear ◽  
Magneto Rheological ◽  
Non Linear System

In this paper we study the behavior of a semi-active suspension witch external vibrations. The mathematical model is proposed coupled to a magneto rheological (MR) damper. The goal of this work is stabilize of the external vibration that affect the comfort and durability an vehicle, to control these vibrations we propose the combination of two control strategies, the optimal linear control and the magneto rheological (MR) damper. The optimal linear control is a linear feedback control problem for nonlinear systems, under the optimal control theory viewpoint We also developed the optimal linear control design with the scope in to reducing the external vibrating of the nonlinear systems in a stable point. Here, we discuss the conditions that allow us to the linear optimal control for this kind of non-linear system.

Observer-Based Piecewise Multi-Linear Controller Designs for Nonlinear Systems Using Feedback and Observer Linearizations

2020 ◽  
Vol 24 (1) ◽  
pp. 12-25
Author(s):  
Tadanari Taniguchi ◽  
Michio Sugeno ◽  
◽  
Keyword(s):  
Nonlinear Systems ◽  
Nonlinear Approximation ◽  
Linear Control ◽  
Separation Principle ◽  
Robust Observer ◽  
Linear Controller ◽  
Modeling Errors ◽  
Tracking Controller ◽  
Piecewise Model ◽  
Linear Controllers

This paper proposes observer-based piecewise multi-linear controllers for nonlinear systems using feedback and observer linearizations. The piecewise model is a nonlinear approximation and fully parametric. Feedback linearizations are applied to stabilize the piecewise multi-linear control system. Furthermore, observer linearizations are more conservative in modeling errors compared with feedback linearizations. In this paper, we propose robust observer designs for piecewise multi-linear systems. Moreover, we design piecewise multi-linear controllers that combine the robust observer with various performance such as a regulator and tracking controller. These design methods realize a separation principle that allows an observer and a regulator to be designed separately. Examples are demonstrated through computer simulation to confirm the feasibility of our proposals.

Linear control of nonlinear systems: Interplay between nonlinearity and feedback

AIChE Journal ◽  
2002 ◽  
Vol 48 (9) ◽  
pp. 1957-1980 ◽  
Author(s):  
S. Alper Eker ◽  
Michael Nikolaou
Keyword(s):  
Nonlinear Systems ◽  
Linear Control

Contribution to Stability Control of Nonlinear Systems

2012 ◽  
Vol 463-464 ◽  
pp. 1579-1582
Author(s):  
Ivan Svarc ◽  
Radomil Matousek
Keyword(s):  
Nonlinear Systems ◽  
Control Systems ◽  
Small Region ◽  
Stability Control ◽  
Linear Control ◽  
Linear Control Systems ◽  
Engineering Practice ◽  
Constant Coefficients ◽  
Linear Differential ◽  
Actual Control

The most powerful methods of systems analysis have been developed for linear control systems. For a linear control system, all the relationships between the variables are linear differential equations, usually with constant coefficients. Actual control systems usually contain some nonlinear elements. In the following we show how the equations for nonlinear systems may be linearized. But the result is only applicable in a sufficiently small region in the neighbourhood of equilibrium point. The table in this paper includes the nonlinear equations and their the linear approximation. Then it is easy to find out if the nonlinear system is or is not stable; the task that usually ranks among the difficult tasks in engineering practice.

Vulnerabilities of Cyber-Physical Linear Control Systems to Sophisticated Attacks

2017 ◽  
Author(s):  
Verica Radisavljevic-Gajic ◽  
Seri Park ◽  
Danai Chasaki
Keyword(s):  
Control System ◽  
Nonlinear Systems ◽  
Control Systems ◽  
Feedback Loops ◽  
Linear Control ◽  
Linear Control Systems ◽  
Malicious Attacks ◽  
Physical Systems ◽  
Controllability And Observability ◽  
Time Invariant

The purpose of this paper is to examine fundamentals of linear control systems and consider vulnerability of the main cyber physical control system features and concepts under malicious attacks, first of all, stability, controllability, and observability, design of feedback loops, design and placement of sensors and controllers. The detailed study is limited to the most important vulnerability issues in time-invariant, unconstrained, deterministic, linear physical systems. Several interesting and motivations examples are provided. We outline also some basic vulnerability studies for time-invariant nonlinear systems.

Linear control of nonlinear systems based on nonlinearity measures

2007 ◽  
Vol 17 (3) ◽  
pp. 273-284 ◽  
Author(s):  
Tobias Schweickhardt ◽  
Frank Allgöwer
Keyword(s):  
Nonlinear Systems ◽  
Linear Control ◽  
Nonlinearity Measures
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