4 results about "Input output linearization" patented technology

A distributed photovoltaic dynamic voltage control method based on feedback linearization, the method comprising: establishing a nonlinear input-output model on the basis of voltage control, a nonlinear relationship between an operating voltage and output current of a photovoltaic array inside a distributed photovoltaic power generation system, and a nonlinear relationship between a direct-current bus voltage state and an output power (S21); performing linearized feedback on a nonlinear input and nonlinear output of the nonlinear input-output model, so as to obtain a feedback control model, an input and output of which are linearized (S22); and acquiring a current reference value of a response current and a voltage reference value of a direct-current bus voltage, and controlling the nonlinear input on the basis of the current reference value, the voltage reference value and the feedback control model (S23). The distributed photovoltaic dynamic voltage control method based on feedback linearization can accurately respond to a current required by a voltage deviation, thereby improving the distributed photovoltaic dynamic voltage control precision.

A Q-learning genetic algorithm-based intelligent electric vehicle path tracking control method relates to the field of intelligent electric vehicle path tracking control. The method first establishes a path tracking model based on the vehicle's dynamic motion mechanism. Then, the output of the path tracking system is redefined by considering the slip state, trajectory tracking error, and yaw stability of the four wheels. The path tracking system is decomposed into an input-output subsystem and a zero-dynamic subsystem through input-output linearization. An adaptive generalized sliding mode control method is proposed for the input-output subsystem, allowing the state of the input-output subsystem to quickly follow its ideal value. Stability conditions for the zero-dynamic subsystem are obtained through stability analysis, and based on this, a controller parameter design method based on Q-learning genetic algorithm optimization is proposed to achieve asymptotic stability of the intelligent electric vehicle path tracking control system near the equilibrium point. The present invention effectively improves the path tracking capability of the intelligent electric vehicle and ensures its dynamic stability under extreme operating conditions.

The invention discloses a non-linear pitch control method for an offshore wind turbine based on a time disturbance observer. First, the invention considers the platform negative damping effect of a floating wind turbine and designs the rated generator speed according to the platform pitching motion; then, a pitch dynamics model of the floating wind turbine is established; by using the feedback linearization theory, the established pitch dynamics model is linearized in terms of input and output; the pole placement method is used to complete the design of the linearized model controller; an adaptive preset-time sliding mode disturbance observer is designed to compensate for the external uncertainty disturbances in the system. Compared with the traditional control method, the invention can better stabilize the power generation of the wind turbine under time-varying wind speeds and has better dynamic performance.

The present application relates to the field of unmanned aerial vehicle control, in particular to a rotor unmanned aerial vehicle control method based on lift feedback, the rotor unmanned aerial vehicle control method based on lift feedback includes designing unmanned aerial vehicle control framework with lift feedback power system and lift closed loop controller based on rotor lift model and motor electric governor model. First, remove the motor speed inverse solution module in the traditional power system in the unmanned aerial vehicle control framework, increase the lift feedback control module, use the sensor to measure the lift generated by the rotor, realize closed loop control;Second, the power system model of multi-rotor unmanned aerial vehicle is established, the motor throttle is taken as the input, and the rotor lift is taken as the output;Finally, based on this model, the input-output linearization force closed loop controller is designed to accurately control the lift output. The method solves the problems of low control accuracy and poor flight stability of the rotor unmanned aerial vehicle in the wind disturbance environment operation or maneuvering flight process. By applying this control method to the rotor unmanned aerial vehicle to ensure its high precision control and stable flight in the wind disturbance environment and maneuvering flight process.