Study On Fault Diagnosis And Tolerant Control For Mobile Robots

With the development of computer technology, electronic technology, control theory, mechanical engineering and the applications of new material, new components, mobile robot technology changes quickly and continuously. Mobile robots are widely used in industry, agriculture, military, space exploration, deep sea exploration, medical care, rescue, daily life, etc. Modern applications are more and more complicated and people are in pursuit of life quality, which lead to more and more requirement and complication of mobile robot technology. From simple application to intelligent ones, from man intervened mode to autonoums mode, from simple environment to unknown environment, from single robot to multi-robots work correspondly and in formation, the reliability of mobile robots are required in all these applications. If mobile robots are operated with fault, the lifetime of them will be decreased, as well as they may bring adverse impact, sometimes disaster consequences. Unfortunately, studies show that mobile robots are often in fault states when they are applied in complex unknown environments especially in space, deep sea and dangerous environments, though they are well designed and manufactured. So studies on fault diagnosis and fault tolerant control of mobile robots are extremely important because they are unreachable from human kind or too expensive.According to the trend of mobile robot applications, this thesis studies fault diagnosis of mobile robot in unknown environment, simultaneous diagnosis of mobile robot, fault diagnosis and fault tolerance control of mobile robot in formation, fault diagnosis and fault tolerance control of mobile robot in flocking based on the research works from scholars all over the world, and with new technique in relative disciplines adopted. The major work and result are represented as follows:1,Failure classification, main reasons, significance, research status, fault diagnosis methods and their characteristics for mobile robot are surveyed. The problems to be resolved for fault diagnosis of mobile robot and the research trend are studied. 2,A new method for fault diagnosis of mobile robots in unknown environment based on Support Vector Machines(SVMs) is proposed. The key points of fault diagnosis method based on SVM are feature extraction, parameter selection, decreasing noise and rejecting outliers. According to noise sensitivity characteristics of SVM, reconstruction of sampling signals and feature extraction by wavelet method are adopted. Grid searching method and cross validation are introduced to optimize the parameters of SVMs. Fault features are classified by multiple SVMs based on voting system. The adaptability and correct rate for classification is increased by adopting the methods above.3,According to the characteristics of multiple faults may occur simultaneous on a mobile robot, simultaneous fault diagnosis technique based on Kernel Fuzzy Clustering Method is proposed. According to the kinematic model of a mobile robot, a specific Kalman Filter (KF) is designed for each single fault state to filter the fault data of the mobile robot. Residuals of the KFs are classified by Kernel Fuzzy Clustering Method (KFCM) with prior knowledge. Simultaneous faults are diagnosed whether one or two faults occurred according to the fuzzy membership to each single fault set. Simulation has been implemented on a 3-wheeled mobile robot named Pioneer 3 to diagnose 12 common single faults and simultaneous multi-faults, and compare the result with FCM, which shows KFCM for simultaneous fault diagnosis technique is better than FCM.4,Fault diagnosis and tolerant control method is studied when mobile robots are walking in SBC and SSC formation modes. Correlative distributed extended Kalman filters are designed according to SBC and SSC following laws. Faults are diagnosed according to the filtering residuals. Fault tolerant control strategy and obstacle avoidance algorithm is proposed remedy the defects of Diagle's algorithm in which formation is not able to maintain when faults occur or obstacles encounter. Fault spreading model on complex network composed by mass mobile robots in formation control is studied and targeted vaccination algorithm based on spread model on complex network is proposed to decrease the faults spreading probability in formation. 5,Takingα-lattice flocking as research object, the influence and fault tolerance control algorithm when faults occurs in flock are studied. The impact to flocking performance is analyzed by means of flocking property indexes when faults occur. A flocking fault diagnosis method and fault tolerance control strategy based on communication and data association are introduced. Considering failure mobile robots as obstacles, an obstacle avoidance algorithm against complex shaped obstacles is proposed which based on recording the information by grid maps and simulating forces by 4 kinds of agents. The algorithm is well performaned that overcomes the shortage of Olfati-Saber's algorithm that is not able to avoid concave shaped obstacles and long walls without prior knowledge.