A Fast Nonsingleton Type-3 Fuzzy Predictive Controller for Nonholonomic Robots Under Sensor and Actuator Faults and Measurement Errors
Ardashir Mohammadzadeh, Hamid Taghavifar, Youmin Zhang, Wenjun Zhang
Abstract
This study proposes a novel control scheme for simultaneously tracking and stabilizing nonholonomic wheeled mobile robots (NWMRs) subject to actuator and sensor faults, measurement errors, uncertain dynamics, and time-varying slippage/skid disturbances. To this end, a nonlinear model based on a type-3 (T3) fuzzy logic system (FLS) is developed for NWMR tracking and stabilization. Furthermore, a nonlinear model predictive controller (NMPC) is designed analytically without employing iterative computations, thus achieving fast performance. A new approach of type-3 nonsingleton fuzzification is introduced to handle measurement errors. Additionally, faults in the actuators and sensors are detected by a supervisory scheme and eliminated by a devised compensator. Finally, extensive simulations and experimental validations are conducted to further verify the effectiveness of the proposed scheme, along with a comparative analysis of several benchmarking methods.