22results about How to "Improve dynamic response characteristics" patented technology

The invention discloses an active and passive composite vibration reduction system, and particularly relates to the technical field of vibration reduction equipment, the active and passive composite vibration reduction system comprises a bottom shell, a load platform, a passive vibration reduction device and an active vibration reduction device, and the passive vibration reduction device and the active vibration reduction device are both arranged between the bottom shell and the load platform; the passive damping device comprises a positive stiffness mechanism and a negative stiffness mechanism which are arranged in parallel; the active damping device comprises a controller, a sensor, a piezoelectric actuator and a flat plate type voice coil motor, the sensor is fixed on the load platform, the sensor, the piezoelectric actuator and the flat plate type voice coil motor are all in signal connection with the controller, and the controller processes signals transmitted by the sensor and transmits commands to the piezoelectric actuator and the flat plate type voice coil motor. The method has higher control precision, stronger anti-interference capability and more excellent adaptability and flexibility, the inherent frequency and the formant peak value of the damping device are effectively reduced, the high attenuation of high-frequency vibration is ensured, and broadband vibration attenuation is realized.

The invention is suitable for the technical field of energy storage, and provides a flywheel energy storage charging control method, which comprises the following steps of: 1, modeling a high-speed permanent magnet synchronous motor, establishing a flywheel energy storage system type, simplifying a PMSM mathematical model, constructing a PMSM model under an ABC coordinate system, and converting to a PMSM model under a d-q coordinate system; and 2, performing model prediction current control on the MRAS, performing double-vector model prediction current control, performing model reference adaptive method, performing parameter identification precision verification based on the MRAS, and adopting a parameter step-by-step identification method based on the MRAS to solve the problem that the model prediction current control height depends on prediction model accuracy, so that the accuracy of the model prediction current control is not influenced. The problem that prediction current control performance of a double-vector model is reduced due to mismatching of model parameters is solved, the identification precision of rotor flux linkage, stator resistance and stator inductance is high, meanwhile, the speed regulation range is widened, the dynamic response characteristic is improved, and the motor model can reflect the actual situation more accurately.

The invention relates to a DC-DC converter control method based on an intelligent agent reinforcement learning algorithm, and the method comprises the steps: firstly building an intelligent agent for a DC-DC buck converter which supplies power to a constant-power load, obtaining a state observation quantity formed by all preset environment variable values of the DC-DC buck converter through the intelligent agent, and obtaining the state observation quantity of the DC-DC buck converter; and a reward value corresponding to a difference value between the output voltage and a preset reference voltage is processed by the intelligent agent, and a corresponding action signal is output and used for controlling the DC-DC buck converter. And then through reinforcement learning training of the intelligent agent, the trained model controls the DC-DC buck converter, so that the output voltage of the DC-DC buck converter has good adaptivity and dynamic response characteristics under different working conditions, and the designed intelligent agent has good steady-state performance in application, so that the stability of the DC-DC buck converter is improved. Model parameter uncertainty caused by component aging can be dealt with, and the stability in practical application is ensured.

This invention relates to the field of flexible DC transmission technology for offshore wind power, and discloses a method and system for collaborative optimization of control parameters of converter stations and wind turbine converters in offshore wind power flexible DC systems. The method includes: constructing an electromagnetic transient simulation model comprising a sending-end converter station, a receiving-end converter station, a DC transmission line, and a wind farm; introducing multiple disturbance conditions and combining variations in control parameters, recording dynamic response process data; establishing a collaborative optimization criterion composed of multiple performance indicators directly mapped from the dynamic response process data; and employing a multi-objective evolutionary optimization mechanism with control parameters as the variables to be optimized and performance indicators as the optimization guide for iterative search. This invention achieves global collaborative configuration of control parameters for converter stations and wind turbine converters, solving the problem of traditional step-by-step tuning methods neglecting dynamic interaction effects, and significantly improving the overall operational robustness of offshore wind power flexible DC systems under multiple disturbance conditions.