Research on MPC Algorithm of Human Simulating Predictive Control in Energy Storage and Modeling of Stepping Motor

The essence of energy storage and release in the power system is the process of converting the driving mode of the motor, stepper motors have the advantages of fast speed regulation, high output power, and high stability, but its dynamic modeling structure is relatively complex, requiring comprehensive consideration of factors such as mechanical transmission and balance of each component, circuit safety, etc. The article proposes an MPC (Model Predictive Control) algorithm based on humanoid thinking, addressing errors and fluctuations in energy storage during the establishment of model structures, simulating the interaction between manual intervention and automatic control can handle issues such as parameter collection mismatch and mathematical model mismatch. Solving the problem of mutual constraint of parameters in the energy storage structure of stepper motors, which affects the stability and error fluctuation of motor energy storage. When the model structure does not match, the humanoid MPC algorithm does not require accurate model parameters, the energy storage process can be controlled through manual adjustment based on the output results and feedback requirements. It has the advantages of clear physical concepts, high accuracy in simulating human thinking modeling, fast error adjustment and output response time, and high stability.