Robotic Fault Detection Diagnosis Torlerant Control And Experimental Research

Robots are applied in the world abroad and deeply. In this background, the index of robotic safty has becoming the important aspect during human use them. Faults in robotic system have very high randomicity. With the machines become dated, the fault occuring frequency rise exponentially. The importance of fault detection, diagnosis, and tolerant control is evident. Although there are some meaningful research results in the aspect of the safty in robotic system, many pivotal problems need effective solving methods. Especially some complex problems ask for available techniques, for example, the faults in encoder and actuator. In another aspect, the fault tolerance on systemic actuators demands higher intellegence and adaptability. Focusing on these practical problems about the safty of robotic system, the research results can be summarized as follows:(1) On the aspect of fault detection in robotic system, firstly, as the very important feedback equipment in postion loop, encoder could lose codes or pause codes. Benifiting from the redundant signal of motor velocity in normal robotic system, a PCA-based mehod was developped. With numerical simulation, the validity and conveniency was tested.And considering normal robot runs under the velocity mode of driver equipment, when the applied torque turns into unconventionality and works in its nominal area, servo equipment would not give off alarm. A thought of treating the robotic nonlinear dynamic model as nonlinear kerel function was presented, where using PCA to detecting the relativity of the output position signal and torque monitoring signal. According to the noncorrelation of unconventionality, fault can be detected. The efficiency of this method was tested when an X-Y motion platform impacts a roadblock.At the same time, aiming at the contingent collision fault, between machines or robot and outer circumstance, the wavelet-based fault detection method is given, from which property of the collision can be reflected. An experiment was developped to testing the efficiency of this method, where an X-Y platform impacted two different obstacles under same motion velocity. (2) The fault diagnosis method using thought of machine learning, considering the nonlinear property of position/angle and applied torque in robotic system, nonlinear support vecter machine was introduced to diagnosing the faults in robotic system, and the commonly fault diagnosing framework was developed for this system. This method was validated in the X-Y platform where different faults were simulated practically.(3) In order to implement fault tolerant control when robot driver equipment falls into saturation state, a method was advanced using the thought of fuzzy rule adjustment. Under it, the close-loop control system is stable and satisfying the requirement of speedability. The globle stability was proved under the Lyapunov sable theory. The effectiveness of this thought was validated on a two degree of freedom manipulators.All of the above fault detecting, fault diagnosis and fault tolerant control methods were developped under the thought of practicability and effectiveness. They were mainly validated on a classical X-Y motion control platform with open configuration. A few methods validated using Matlab because it was hard to simulating these types of faults. As a conclusion, this work gives some new thoughts and methods for solving the safty-related problems in robotic system.