Permanent magnet synchronous motor (PMSM) AC servo system has the characteristics of uncertainty, time-varying, nonlinear and fractional order. Applying the traditional control method is difficult to achieve the desired control effect. The fuzzy control has strong adaptability to the parameter change, nonlinearity and imprecise model of the controlled object. The simulation model of permanent magnet synchronous motor three closed-loop systems is established. The control principle and the realization of space vector pulse width modulation (SVPWM) are studied by using a vector control strategy. Due to the fractional-order characteristic of the motor, a fuzzy logic algorithm is used to realize the parameter self-tuning of the fractional-order proportional integral differential (PID) controller. The controller is selected as the position regulator of the servo motor. It combines the precision of fractional-order PID controller with the adaptability of fuzzy control and adds feed-forward to improve the response speed. The path tracking experiments on several different paths are carried out, and the results show that the control method is effective and can meet the trajectory tracking requirements of servo control. Finally, the speed and position tracking test of the PMSM AC servo system is carried out on the test verification platform, which verifies the effectiveness of the control algorithm.

This paper investigates the fault-tolerant tracking control problem of high-speed trains (HSTs) subject to unknown model parameters with unavailable uncertainties, unmeasurable additional disturbance, and unpredictable actuator faults constrained by actuator saturation. An adaptive passive fault-tolerant tracking control strategy based on variable-gain proportion-integral-derivative (PID)-type sliding mode surface is proposed to handle the problem. Unknown model parameters, gains of the PID-type sliding mode surface, and upper bounds of the lumped system uncertainty which includes additional disturbance, modeling uncertainties, and uncertainties resulting from actuator faults, are estimated online by adaptive technology. The input saturation (actuator output saturation) constraint is handled by introducing an auxiliary signal. The proposed controller can compensate for the effects of the lumped uncertainty and the actuator faults effectively. Moreover, the controller is model-independent, which means it requires no prior knowledge of model parameters and upper bounds of the lumped uncertainty, and does not depend upon fault detection and diagnosis module. The asymptotic stability of the closed-loop train system is demonstrated by Lyapunov theory. Good fault-tolerant tracking capacity, effective anti-actuator saturation ability, and strong robustness of the proposed controller are verified via numerical simulation.

In recent years, with the rapid development of various cities, the operation and maintenance of the public transport system has become increasingly prominent problems, the development of the intelligent public transport system has been imperative. This paper takes the intelligent public transport system as the research object, using wireless network transmission technology, big data retrieval and processing, cloud computing platform and other technologies, analyzes the main requirements of the intelligent public transport system. This system adopts the classic three-layer architecture of the Internet of Things, namely, the perception layer, the network layer and the platform layer. Intelligent public transport dispatching system is the core system of intelligent public transport. The paper uses frog leaping algorithm as the dispatching algorithm to realize the function of public transport dispatching. Through the test, it can complete the task of adding or reducing vehicles according to the increase or decrease of passenger flow. The design and implementation of the cloud platform provides a strong support for the renewal and development of modern urban public transportation system, and has a certain guiding significance. As a complete system with more rapid and accurate management, more convenient and efficient operation, it improves the public transport dispatching ability and improves the travel experience of passengers, and has a cross-era significance for the development of urban public transportation.

Permanent magnet synchronous motor (PMSM) AC servo system shows the characteristics of uncertainty, time-varying and non-linearity, which makes it difficult for traditional PID control to achieve ideal control effect. Fuzzy control has strong adaptability to the problems of parameter variation, non-linearity and model inaccuracy of the controlled object. Vector control strategy is used to study its control principle and the realization of SVPWM. Because the motor object has certain fractional order characteristics, the fuzzy parameter self-tuning PIλ control is chosen as the position regulator of servo motor. It combines the accuracy of fractional order PI control and the adaptability of fuzzy control. A simulation model of PMSM three-closed-loop system is built in MATLAB/Simulink environment. The results show that the control method is effective and can satisfy the trajectory tracking of servo control.