CHAOS CONTROL AND SYNCHRONIZATION USING SYNERGETIC CONTROLLER WITH FRACTIONAL AND LINEAR EXTENDED MANIFOLD

In this manuscript, for the first time, a fractional-order manifold in a synergetic approach using a fractional order controller is introduced. Furtheremore, in the synergetic theory a macro variable is expended into a linear combination of state variables. An aim is to increase the convergence rate as well as time response of the whole closed loop system. Quality of the proposed controller is investigated to control and synchronize a nonlinear chaotic Coullet system in comparison with an integer order manifold synergetic controller. The stability of the proposed controller is proven using the Lyapunov method. In this regard stabilizing control effort is yielded. Simulation result confirm convergence of states towards zero. This is achieved through a control effort with fewer oscillations and lower amplitude of signls which confirm feasibility of the control effort in practice. KEYWORDS:  synergetic control theory; fractional order system; synchronization; nonlinear chaotic Coullet system; chaos contro

INTELLIGENT FRACTIONAL ORDER ITERATIVE LEARNING CONTROL USING FEEDBACK LINEARIZATION FOR A SINGLE-LINK ROBOT

In this paper, iterative learning control (ILC) is combined with an optimal fractional order derivative (BBO-Da-type ILC) and optimal fractional and proportional-derivative (BBO-PDa-type ILC). In the update law of Arimoto's derivative iterative learning control, a first order derivative of tracking error signal is used. In the proposed method, fractional order derivative of the error signal is stated in term of 'sa' where  to update iterative learning control law. Two types of fractional order iterative learning control namely PDa-type ILC and Da-type ILC are gained for different value of a. In order to improve the performance of closed-loop control system, coefficients of both  and  learning law i.e. proportional , derivative  and  are optimized using Biogeography-Based optimization algorithm (BBO). Outcome of the simulation results are compared with those of the conventional fractional order iterative learning control to verify effectiveness of BBO-Da-type ILC and BBO-PDa-type IL

Control of oxygen excess ratio in a PEM fuel cell system using high-order sliding-mode controller and observer

The main objective of this manuscript is to design a high-order sliding-mode observer to provide finite time estimation of unmeasurable states (x4 : oxygen mass, x5 : nitrogen mass) together with the oxygen excess ratio (ratio of the input oxygen ow to the reacted oxygen ow in the cathode). This is done by applying second-order sliding modes through either super twisting or suboptimal controllers to control the proton exchange membrane fuel cell's breathing. The estimated oxygen excess ratio is controlled in a closed-loop system using 2 distinct sliding-mode approaches: a cascaded super twisting controller and a single-loop suboptimal structure. Simulation results are presented to make a quantitative comparison between the cascade and the single-loop configuration. The results verify that the cascade provides accurate reference tracking while the single-loop presents faster convergence

Control of PEM fuel cell system via higher order sliding mode control

This paper presents a multi-input multi-output (MIMO) dynamic model of polymer electrolyte membrane (PEM) fuel cells. A non-linear controller is designed to prolong the stack life of the PEM fuel cell. A moderate deviation between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell. Therefore, a second-order sliding mode strategy is applied to the PEM fuel cell system. This controller is combined with a new step by step differentiators as an output-feedback controller. The differentiator estimates a successive derivative of the measured error signal up to n - 1 order after a finite time transient. Simulation procedure shows performance of the SOSM approach to control PEMFC stack pressure to provide robustness against uncertainties and disturbances. Copyright © 2012 Inderscience Enterprises Ltd

Control of oxygen excess ratio in a PEM fuel cell system using high-order sliding-mode controller and observer

The main objective of this manuscript is to design a high-order sliding-mode observer to provide finite time estimation of unmeasurable states (x4 : oxygen mass, x5 : nitrogen mass) together with the oxygen excess ratio (ratio of the input oxygen ow to the reacted oxygen ow in the cathode). This is done by applying second-order sliding modes through either super twisting or suboptimal controllers to control the proton exchange membrane fuel cell's breathing. The estimated oxygen excess ratio is controlled in a closed-loop system using 2 distinct sliding-mode approaches: a cascaded super twisting controller and a single-loop suboptimal structure. Simulation results are presented to make a quantitative comparison between the cascade and the single-loop configuration. The results verify that the cascade provides accurate reference tracking while the single-loop presents faster convergence

Design of finite-time high-order sliding mode state observer: A practical insight to PEM fuel cell system

This paper presents a scheme of designing finite-time high-order sliding mode (HOSM) observer which provides some essential requirements to be used in a sensorless control. The observer design technique is proposed to estimate some key states in a Multi-Input Multi-Output (MIMO) proton exchange membrane fuel cell (PEMFC) in a finite-time. Since variation of the load current deeply affects the life time of the cell, estimation and control of oxygen excess ratio (λO2) is suggested to detect and prevent the damage. As a practical application, the observer reconstructs oxygen excess ratio using measurable variables, such as the compressor angular speed, the supply, the return manifold pressures and the load current. The estimation is performed to keep stability without need of any transformation to a canonical form in a finite time. The designed finite-time observer is shown with some increases in the response time indices, improves the accuracy whilst guarantees a fast convergence with respect to using flow sensors. Simulation results verify the achievements whilst signify the fast response as well as robust against uncertainties and disturbances. © 2013 Published by Elsevier Ltd. All rights reserved