Research Of Adaptive Robust Fault-Tolerant Control Based On T-S Fuzzy Model

The reliability is the key index t o adjust whether the controlled system maintains.normal operation or not. The signal type or slight degree faults which present in the components, such as sensors and actuators in the controlled system, may influence the control capability and reliability of the whole system more or less. In some cases, it may cause the entire system failure. Today, the adaptive fault-tolerant control as an advanced intelligent control technology has applied to many control areas of practical engineering to achieve the goal of enhance and improve the system reliability. However, the current adaptive fault-tolerant control technology are mostly aim to the nonlinear system which has single controlled object and simple controlled process. There are few researches about the adaptive fault-tolerant control for the nonlinear system with multi-target and global.Thus, the adaptive fault-tolerant control research in this dissertation focuses on the descriptor nonlinear system which contains double time-delays and parameter uncertainties. The research was divided into the following two aspects, one was fault detection and estimation, the other was adaptive fault-tolerant control and reliability optimization of the controlled system.In fault detection and estimation, the main work was to establish the fault estimation model. First, the controlled system model which contains multi-sensor and multi-actuator was constructed, and the complex nonlinear system with double time-delays and parameter uncertainties based on T-S fuzzy model was also described, then the H-fuzzy state feedback controller and observer was designed to realize fault detection and estimation in real-time.In structuring the fault-tolerant control model, the first step was to choose an appropriate sliding surface, and combined the algorithm of sliding control and adaptive generic model control together. Then the state observer was applied to the designed sliding adaptive generic model, and the decision model with dynamic fault reconfiguration was build. Then, the goal of this dissertation about the adaptive robust fault-tolerant control for the complex nonlinear controller system was achieved. The MATLAB simulations verify that the designed adaptive robust fault-tolerant control dynamic decision model based on T-S fuzzy model has good robustness for system parameter uncertainties and external interference. It also can estimate the system states and faults in real-time, shorten the time of faults detection, and the controlled system also can get satisfy output even as faults occur. Above all, the designed fault-tolerant control strategy is effective for complex nonlinear controlled system.