Asynchronous Motor Command Filter Neural Network Control Considering Input And State Constraints

Induction motors(IMs)are widely used in industry,agriculture and aerospace fields because of its high reliabilities,low cost and mature manufacturing technologies.The mathematical model of IMs drive systems have the characteristics of high order nonlinearities and uncertain parameters,so it is difficult for traditional scalar control methods to achieve satisfactory control performance.Then,how to propose an advanced control strategy to overcome the above difficulties while achieving high-precision motor control performance has attracted wide attention of related scholars.In addition,the rotor angular speed,stator current and input voltage of the motor are limited in specific applications.Otherwise,it will affect the stabilities of the drive systems and even lead to safety problems.Therefore,the state constraints and saturated input voltage should also be considered in the design processes of the controllers.In this paper,a new strategy is proposed for speed regulation of IMs drive systems considering input saturation/state constraints by using the backstepping method,barrier Lyapunov function and adaptive neural network command filtering control method.The main research results are as follows.Firstly,an adaptive command filter backstepping control strategy is proposed for a class of strict feedback nonlinear systems with input saturation.In addition,a novel barrier Lyapunov functions based adaptive command filtering backstepping control strategy is proposed for a class of strict-feedback nonlinear systems with the state constraints.Combining the barrier Lyapunov function with backstepping can ensure that the system states are limited to reasonable area.Secondly,a speed regulation control of induction motor considering input saturation based on adaptive command filter backstepping technology is studied in this paper.The command filter backstepping technology is introduced to solve the “explosion of complexity” with error compensation mechanism,which has better control accuracy than the dynamic surface technology.The simulation results show that the effectiveness and superiority of the proposed adaptive command filtering backstepping technique.Finally,a novel barrier Lyapunov functions-based adaptive command filtering backstepping speed regulation strategy is designed for IMs drive systems considering state constraints.The principle of barrier Lyapunov functions ensure that the rotor angular speed and stator currents of the IMs drive systems are within reasonable ranges.The simulation results show that the designed controller can limit the rotor angular speed,stator currents and other state variables to given ranges under the premise of ensuring good speed regulation,eliminating the potential safety hazards of the drive systems.