Title of the Paper: Automatic Gain Control for Unity Feedback Control Systems with
Large Parameters Variations
DOWNLOAD FULL PDF
Authors: Tain-Sou Tsay
Abstract: In this paper, an automatic gain control scheme is first proposed for analyses and designs of unity
feedback control systems. The controlled system is a nonlinear feedback control system. The overall system is
equivalent to a conventional automatic gain control loop with command tracking error input. Therefore, it gives
good command tracking behaviour while keeping robust characteristic of the original AGC loop. Furthermore,
it gives good robustness for coping with fast large parameter variations. The stability and effective of controlled
systems are verified by time responses, frequency responses, and parameter variation testing with three
numerical examples. Comparisons are also made with the PID control.
Keywords: Automatic gain Control, nonlinear feedback System.
Title of the Paper: Control for stability and Positivity of 2-D linear
discrete-time systems
DOWNLOAD FULL PDF
Authors: Mohammed Alfidi and Abdelaziz Hmamed
Abstract: This paper investigate the stabilizability of 2-D linear discrete-time systems described by the
Roesser model with closed-loop positivity. Necessary and sufficient condition for the existence of desired
state-feedback controllers guaranteeing the resultant closed-loop system to be asymptotically stable and
positive is obtained. The synthesis of state-feedback controllers, including the requirement of positiveness
of the controllers and its extension to uncertain plants are solved in terms of Linear Matrix Inequalities
(LMIs) which can be easily verifies by using standard numerical software. Numerical examples are provided
to illustrate the proposed conditions. Keywords:
Positive Systems, 2-D Systems, Linear Matrix Inequalities (LMIs), Stability,
Stabilization,
Positive Control, Roesser Model.
Title of the Paper: Adaptive Fuzzy Tracking Control of Nonlinear Systems
DOWNLOAD FULL PDF
Authors: Song-Shyong Chen, Yuan-Chang Chang, Chen Chia Chuang,
Chau-Chung Song and Shun-Feng Su
Abstract: Adaptive linearization controllers have been shown to have nice control performance. However, two functions in the controllers are derived from the considered system. Thus, those controllers can only work for known systems. In this paper, we proposed a fuzzy modeling approach to model those two functions. The proposed approach is called the adaptive model reference fuzzy control. In this approach, the considered dynamic nonlinear model can be unknown. Different from previous adaptive fuzzy controllers, our approach does not need any auxiliary operations on input trajectories and on system states. The proposed controller and the weight update laws only need system states and the current desired output without using any their derivatives. The Lyapunov stability theorem is used to derive controller parameters update laws, which ensure that the system states be bounded and the plant output asymptotically tracks an arbitrary piecewise reference trajectory. The proposed method is successfully applied to an unstable nonlinear system and a chaotic system. The learning and control performance of our approach is nice and also superior to that of previous approaches. Keywords:
model reference, adaptive ,fuzzy control, Lyapunov stability, nonlinear system
|
