Title of the Paper: Sampled tracking for
linear delayed plants using piecewise functioning controller
DOWNLOAD FULL PDF
Authors: Wang Haoping, Vasseur Christian,
Chamroo Afzal And Koncar Vladan
Abstract: This article presents a control method to realize tracking of
linear plants that deliver a delayed and sampled state. To do so, we make
use of a class of piecewise functioning controller (PFC): bi-sampled
controller. The use of this type of controller allows sampled tracking with
a delay twice as much as that on the state’s output. Thus, we propose an
optimal mathematical approach of the dynamics of our controller. We then
give an adaptation of this mathematical approach, using only the delayed and
sampled state. Computer simulation results are given so as to enhance the
theoretical aspect of our method.
Keywords: sampled tracking, bi-sampled controller, delayed sampled state
Title of the Paper: Decentralized Adaptive Fuzzy
Control for a class of Nonlinear
Systems
DOWNLOAD FULL PDF
Authors: A.Errahmani, H.Ouakka,
M.Benyakhlef and I.Boumhidi
Abstract: In this paper, stable direct and indirect decentralized adaptive fuzzy controls are proposed for a
class of large-scale nonlinear systems with the strong interconnected. The feedback and adaptive
mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a
reference trajectory. In both approaches, the proposed controllers are used to approximate the unknown
subsystems. In addition, each subsystem is able to adaptively compensate for interconnections without
known bounds. Simulation results are given to illustrate the tracking performance of the proposed methods. Keywords:
Decentralized Control, Fuzzy Controller, Interconnected Nonlinear System.
Title of the Paper: Adaptive Inverse Control of Excitation System
with Actuator Uncertainty
DOWNLOAD FULL PDF
Authors: Xiaofang Yuan, Yaonan
Wang, Lianghong Wu
Abstract: This paper addresses an inverse controller design for excitation system with changing parameters
and nonsmooth nonlinearities in the actuator. The existence of such nonlinearities and uncertainty imposes a
great challenge for the controller development. To address such a challenge, support vector machines (SVM)
will be adopted to model the process and the controller is constructed using SVM. The SVM, used to approximate
nonlinearities in the plant as well as the actuator, are adjusted by an adaptive law via back propagation
(BP) algorithms. To guarantee convergence and for faster learning, adaptive learning rates and convergence
theorems are developed. Simulations show that the proposed inverse controller has better performance in system
damping and transient improvement. Keywords:
nonlnear control, inverse system, support vector machines, adaptive control, model identification,
actuator uncertainty
Title of the Paper: On robustness of suboptimal min-max model predictive control
DOWNLOAD FULL PDF
Authors: De-Feng He, Hai-Bo Ji, Tao
Zheng
Abstract: With the hard computation of an exact solution to non-convex
optimization problem in a limited time, we propose a suboptimal min-max
model predictive control (MPC) scheme for nonlinear discrete-time systems
subjected to constraints and disturbances. The idea of input-to-state
stability (ISS) is introduced and a Lyapunov-like sufficient condition for
ISS is presented. Based on this, we show that the suboptimal predictive
controller obtained here holds back the disturbance robustly in the present
of constraints on states and inputs. Keywords:
Nonlinear predictive control; Suboptimal control; Input-to-state stability;
Constraints
|
