103 research outputs found

    A novel fault-tolerant control strategy for near space hypersonic vehicles via least squares support vector machine and backstepping method

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    Near Space Hypersonic Vehicle (NSHV) could play significant roles in both military and civilian applications. It may cause huge losses of both personnel and property when a fatal fault occurs. It is therefore paramount to conduct fault-tolerant research for NSHV and avoid some catastrophic events. Toward this end, this paper presents a novel fault-tolerant control strategy by using the LSSVM (Least Squares Support Vector Machine)-based inverse system and Backstepping method. The control system takes advantage of the superiority of the LSSVM in solving the problems with small samples, high dimensions and local minima. The inverse system is built with an improved LSSVM. The adaptive controller is designed via the Backstepping which has the unique capability in dealing with nonlinear control systems. Finally, the experiment results demonstrate that the proposed method performs well

    Adaptive Control of an Active Magnetic Bearing with External Disturbance

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    Adaptive back stepping control (ABC) is originally applied to a linearized model of an active magnetic bearing (AMB) system. Our control goal is to regulate the deviation of the magnetic bearing from its equilibrium position in the presence of an external disturbance and system uncertainties. Two types of ABC methods are developed on the AMB system. One is based on full state feedback, for which displacement, velocity, and current states are assumed available. The other one is adaptive observer based back stepping controller (AOBC) where only displacement output is measurable. An observer is designed for AOBC to estimate velocity and current states of AMB. Lyapunov approach proves the stabilities of both regular ABC and AOBC. Simulation results demonstrate the effectiveness and robustness of two controllers

    A Fault Tolerant Control for Sensor and Actuator Failures of an Non Linear Hybrid System

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    We focused in this work on a fault tolerant control of a non linear hybrid system class based on diagnosis method (determine and locate the defects and their types) and on the faults reconfiguration method.In literature we can found many important research activities over the fault-tolerant control of non linear systems and linear Hybridsystems. But it dosen´t exist too many for the non linear hybridsystem.The main idea in this paper is to consider a new approach to improve the reconfiguration performance of the non linear hybrid system by using hammerstein method which is designed to works only for linear systems. This method compensated the effect of the faults and guarantees the closed-loop system stable. The proposed method is simulated with a hydraulic system of two tanks with 4 modes

    Integral sliding mode fault tolerant control allocation for a class of affine nonlinear system

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    This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.This paper develops novel fault tolerant integral sliding mode control allocation schemes for a class of over-actuated affine nonlinear system. The proposed schemes rely on an existing baseline controller and the objective is to retain the nominal (fault-free) closed-loop performance in the face of actuator faults/failures by effectively utilizing actuator redundancy. The online control allocation reroutes the control effort to the healthy actuators using knowledge of the actuator effectiveness level estimates. One of the proposed schemes is tested in simulation using a well known high fidelity model of a large civil transport aircraft (B747) from the literature. Good simulation results show the efficacy of the scheme

    Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

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    In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

    Modeling and Robust Control of Flying Robots Using Intelligent Approaches Modélisation et commande robuste des robots volants en utilisant des approches intelligentes

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    This thesis aims to modeling and robust controlling of a flying robot of quadrotor type. Where we focused in this thesis on quadrotor unmanned Aerial Vehicle (QUAV). Intelligent nonlinear controllers and intelligent fractional-order nonlinear controllers are designed to control. The QUAV system is considered as MIMO large-scale system that can be divided on six interconnected single-input–single-output (SISO) subsystems, which define one DOF, i.e., three-angle subsystems with three position subsystems. In addition, nonlinear models is considered and assumed to suffer from the incidence of parameter uncertainty. Every parameters such as mass, inertia of the system are assumed completely unknown and change over time without prior information. Next, basing on nonlinear, Fractional-Order nonlinear and the intelligent adaptive approximate techniques a control law is established for all subsystems. The stability is performed by Lyapunov method and getting the desired output with respect to the desired input. The modeling and control is done using MATLAB/Simulink. At the end, the simulation tests are performed to that, the designed controller is able to maintain best performance of the QUAV even in the presence of unknown dynamics, parametric uncertainties and external disturbance

    A Survey of Decentralized Adaptive Control

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