Robust controller of permanent magnet synchronous motor based on fuzzy-neural network generalized inverse and construction method thereof

Abstract

The invention discloses a robust controller of a permanent magnet synchronous motor based on a fuzzy-neural network generalized inverse and a construction method thereof. The construction method of the invention comprises the following steps of: combining an internal model controller and a fuzzy-neural network generalized inverse to form a compound controlled object; serially connecting two linear transfer functions and one integrator with the fuzzy-neural network with determined parameters and weight coefficients to form the fuzzy-neural network generalized inverse, serially connecting the fuzzy-neural network generalized inverse and the compound controlled object to form a generalized pseudo-linear system, linearizing a PMSM (permanent magnet synchronous motor), and decoupling and equalizing the linearized PMSM into a second-order speed pseudo-linear subsystem and a first-order current pseudo-linear subsystem; and respectively introducing an internal-model control method in the two pseudo-linear subsystems to construct the internal model controller. The robust controller of the invention has the advantages of overcoming the dependence and local convergence of the optimal gradient method on initial values and solving the problems of randomness and probability caused by using the simple genetic algorithm, obtaining the high performance control, anti-disturbance performance and adaptability of the motor and simplifying the control difficulty, along with simple structure and high system robustness.

Description

Technical field [0001] The invention relates to a permanent magnet synchronous motor controller, which is suitable for the robust control of a permanent magnet synchronous motor driven by a voltage source inverter, and belongs to the technical field of electric drive control equipment. Background technique [0002] Permanent Magnet Synchronous Motor (PMSM) has been widely used in aerospace, weapons and national defense, CNC machine tools, industrial robots, flexible control, communications industry, oil field and chemical industry, and long-running fans and pumps. application. [0003] The control methods of the permanent magnet synchronous motor speed control system mainly include constant voltage-frequency ratio control, vector control, direct torque control and differential geometric state feedback control. Among them, the permanent magnet synchronous motor speed control system under the constant voltage-frequency ratio control method based on the steady-state model has a simpl...

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Problems solved by technology

Among them, the permanent magnet synchronous motor speed control system under the constant voltage frequency ratio control mode based on the steady state model has a simple structure, low cost, and is easy to implement. It can meet the general speed control requirements, but the system performance is not high, and it relies too much on system dynamic mathematics The model is an open-loop control, and the load capacity at low speed is limited. When the load or speed command is suddenly increased, it is prone to out-of-step phenomenon, and the ideal dynamic control performance cannot be obtained.

The permanent magnet synchronous motor speed control system under the vector control mode based on the dynamic model has the advantages of good dynamic performance, wide speed range, and high control accuracy. Widely used, however, due to the great dependence of vector control on motor parameters, the speed and flux linkage can satisfy the decoupling relationship only when the flux linkage reaches a steady state and remains constant. It is difficult to ensure complete decoupling, and the actual control effect is difficult to achieve The result of theoretical analysis, and the vector rotation coordinate transformation used in the process of simulating DC motor control is relatively complicated, and the robustness of the system is greatly reduced

The permanent magnet synchronous motor speed control system under the direct torque control method based on the stator flux orientation is convenient to realize full digitalization, and there is no need to make the AC motor equivalent to the DC motor, and the complicated rotation coordinate transformation and motor model are omitted. In the vector control, the control effect is affected by the change of the rotor parameters. It is only necessary to detect the stator resistance and observe the stator flux linkage of the motor. It uses the torque and flux linkage hysteresis comparison to achieve partial dynamic decoupling. Defects such as large torque ripple

The differential geometry method is a method of linearization and decoupling control of nonlinear systems developed with differential geometry as a tool. The purpose is to transform the complex system into a simple linear system after accurate linearization of the nonlinear system. In this way, the linear theory can be used to analyze and design the linear controller in a wide working range without losing the controllability and accuracy of the system. At the same time, it is required to obtain accurate mathematical models and use complex and abstract mathematical tools, which is difficult to apply in engineering

[0004] At present, although the neural network inverse system control method can realize the linear decoupling of the permanent magnet synchronous motor, the several integral pseudo-linear subsystems formed after decoupling are open-loop unstable, and the neural network based on the empirical risk minimization The network has defects such as local minimum points, over-learning, and the selection of structures and types relies too much on experience. At the same time, in the actual operation of permanent magnet synchronous motors, there are load mutations, many system controllable parameters, unmodeled dynamic effects, and easy out-of-step. etc. These uncertain factors cause model mismatch and make the system deviate from the expected control target

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