scholarly journals Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Algorithms ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 106 ◽  
Author(s):  
Gerardo Navarro-Guerrero ◽  
Yu Tang
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Adaptive Controller ◽  
Model Reference Adaptive Control ◽  
Loop Model ◽  
Unknown Parameters ◽  
Model Reference ◽  
State Measurement ◽  
Model Reference Adaptive

The design of a fractional-order closed-loop model reference adaptive control (FOCMRAC) for anesthesia based on a fractional-order model (FOM) is proposed in the paper. This proposed model gets around many difficulties, namely, unknown parameters, lack of state measurement, inter and intra-patient variability, and variable time-delay, encountered in controller designs based on the PK/PD model commonly used for control of anesthesia, and allows to design a simple adaptive controller based on the Lyapunov analysis. Simulations illustrate the effectiveness and robustness of the proposed control.

Composite Model Reference Adaptive Control for a Class of Nonlinear Fractional Order Systems

2015 ◽  
Author(s):  
Yiheng Wei ◽  
Shu Liang ◽  
Yangsheng Hu ◽  
Yong Wang
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Prediction Errors ◽  
Model Reference ◽  
Closed Loop Systems ◽  
The Stability ◽  
Model Reference Adaptive

This article presents a novel model reference adaptive control of fractional order nonlinear systems, which is a generalization of existing method for integer order systems. The formulating adaptive law is in terms of both tracking and prediction errors, whereas existing methods only depends on tracking error. The transient performance of the closed-loop systems with the proposed control strategy improves in the sense of generating smooth system output. The stability and tracking convergence of the resulting closed-loop system are analyzed via the indirect Lyapunov method. Meanwhile, the proposed controller is implemented by employing some fractional order tracking differentiator to generate the required fractional derivatives of a signal. Numerical examples are provided to illustrate the effectiveness of our results.

scholarly journals Study of Closed-Loop Model Reference Adaptive Control of Smart MicroGrid with QNU and Recurrent Learning

2017 ◽  
Vol 21 (4) ◽  
pp. 34-39
Author(s):  
Vladimír Malý ◽  
Martin Veselý ◽  
Peter M. Beneš ◽  
Petr Neuman ◽  
Ivo Bukovský
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Model Reference Adaptive Control ◽  
Loop Model ◽  
Model Reference ◽  
Model Reference Adaptive

Switched Fractional Order Model Reference Adaptive Control for First Order Plants: a Simulation-Based Study

2021 ◽  
Author(s):  
Norelys Aguila Camacho ◽  
JorgeE García Bustos ◽  
EduardoI Castillo López ◽  
Javier A. Gallego ◽  
JuanC TraviesoTorres
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Reference Model ◽  
Model Reference Adaptive Control ◽  
System Behavior ◽  
Order Model ◽  
Model Reference ◽  
First Order ◽  
Fractional Order Model ◽  
Model Reference Adaptive

Abstract This paper presents the results and analysis of an exhaustive simulation study where Switched Fractional Order Model Reference Adaptive Control (SFOMRAC) is used for first order plants, along with the analytical proof of boundedness and convergence of the scheme. The analysis is focused on the controlled system behavior through the integral of the timed squared control error (ITSE) and on the control energy though the integral of the squared control signal (ISI). Controller parameters such as fractional order, adaptive gain and switching time are varied along the simulation studies, as well as plant parameters and reference models. The results show that SFOMRAC controllers can be found for every plant and reference model used, such that both system behavior and control energy can be improved, compared to equivalent non switched fractional order and integer order control strategies.

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