Fault Diagnosis and Fault Tolerant Control for Manipulator with Actuator Multiplicative Fault
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ISSN:1598-6446 eISSN:2005-4092 http://www.springer.com/12555
Fault Diagnosis and Fault Tolerant Control for Manipulator with Actuator Multiplicative Fault Yawei Wu and Lina Yao* Abstract: In this paper, a new fault diagnosis and fault tolerant control algorithm for manipulators with actuator multiplicative fault is proposed. The dynamic model of the manipulator with disturbance is taken as the research object. When faults occur in the actuator, a nonlinear observer based on radial basis function (RBF) neural network is used to estimate the fault information. After the fault information is obtained, an adaptive back-stepping sliding mode controller is used to control the manipulator to reach the desired trajectory. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and satisfactory results have been obtained. Keywords: Actuator multiplicative fault, fault diagnosis, fault-tolerant control, manipulator, RBF.
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INTRODUCTION
With the continuous development of science and technology, the related applications of robot-related technologies have become more and more common. As an important part of robots, the safety and reliability of manipulator control systems has been paid more and more attention. When the manipulator works in a harsh working environment, the actuators, sensors and other system components of the manipulator are very prone to failure, which will affect the overall performance of the manipulator system. The study of fault diagnosis and fault-tolerant control methods in [1–5] can help us to solve these urgent problems. Nowadays, more and more researchers have been involved in the study of fault diagnosis and fault-tolerant control. In the field of fault detection technology based on analytical redundancy, observer-based fault detection methods have been widely used. By using the residual between the actual system output and the observer system output, the estimated value of the fault can be obtained. Adaptive observer, sliding mode observer and unknown input observer are three kinds of observers commonly used by researchers. In [6], a novel fault diagnosis method is presented for the nonlinear system with coupled fault and disturbance via the adaptive observer technique. In [7], an unknown input observer is proposed to estimate the states and unknown inputs of a class of Lipschitz nonlinear systems. The design of sliding mode multiple observer for estimating the state vector of a nonlinear
dynamical system is discussed in [8]. However, when estimating the multiplicative fault, it is difficult to estimate the fault accurately. This is because the front coefficient of the multiplicative fault in the system state equation is often the time-varying system input. The adaptive observer is often used to estimate the multiplicative fault of the system, but it can only estimate the constant fault. In a manipulator, faults may occur in actuators, sensors and other components of the system, but there is no doubt that faults are more likely to occur in actuators and
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