Modeling research of train tracing based on UML sequence diagram and UPPAAL

The zone control subsystem is a real-time control system,which requests the correctness of the control process.Train tracing scene is an important function of the zone controller(ZC)in the communication based train control(CBTC)system.In the process of deep development and design,to ensure the safety of the system,the system needs to be modeled,simulated and verified to discover the system design flaws.Unified modeling language(UML)is combined with timed automata,and timed automata network models of train-filter and train tracing demarcation-point are established.At the same time,the verification tool of UPPAAL is applied to simulate the system,and verify the requirements of performance and function of system.The results show that the function of train tracing demaraction-point meets the requirements of system safety and limited activity.Therefore,the method is feasible and can be applied to the modeling and verification of other scenes of train control system.

Nonlinear dynamic fractional sliding mode control to the motor of mining locomotive

The harsh operating environment and complex operating conditions of the mine electric locomotive affect the control performance of the locomotive traction motor.In order to improve the speed control performance of electric locomotive traction motors,a dynamic fractional-order sliding mode control(DFOSMC)algorithm considering uncertain factors was proposed.A load torque sliding mode observer was designed for the complex load disturbance of the traction motor,and its observations were integrated into the DFOSMC controller to overcome the influence of load disturbance.Finally,the stability of the designed controller was proved by Lyapunov's theorem.Besides,the control performance of DFOSMC controller was compared with integer-order sliding mode controller and fractional-order sliding mode controller through simulation experiments.Compared with integer-order sliding mode and fractional-order sliding mode controllers,the dynamic and static performance of the DFOSMC controller with load observation is better,and it has stronger anti-interference ability.The DFOSMC controller effectively improves the control performance of the traction motor of the mining locomotive.

Speed sensorless FCS-MPTC based on FOSM-MRAS five-phase permanent magnet synchronous motor

For the two-level five-phase permanent magnet synchronous motor(FP-PMSM)drive system,an improved finite-control-set model predictive torque control(MPTC)strategy is adopted to reduce torque ripple and improve the control performance of the system.The mathematical model of model reference adaptive system(MRAS)of FP-PMSM is derived and a method based on fractional order sliding mode(FOSM)is proposed to construct the model reference adaptive system(FOSMMRAS)to improve the motor speed estimation accuracy and eliminate the sliding mode integral saturation effect.The simulation results show that the FP-PMSM speed sensorless FCS-MPTC system based on FOSM-MRAS has strong robustness,good dynamic performance and static performance,and high reliability.

Application of interacting multiple model in integrated positioning system of vehicle

To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） , the paper presents an adaptive filter algorithm that combines interacting multiple model （IMM） and non linear Kalman filter. The algorithm describes the motion mode of vehicle by using three state spacemode]s. At first, the parallel filter of each model is realized by using multiple nonlinear filters. Then the weight integration of filtering result is carried out by using the model matching likelihood function so as to get the system positioning information. The method has advantages of nonlinear system filter and overcomes disadvantages of single model of filtering algorithm that has poor effects on positioning the maneuvering target. At last, the paper uses IMM and EKF methods to simulate the global positioning system （OPS）/inertial navigation system （INS）/dead reckoning （DR） integrated positioning system, respectively. The results indicate that the IMM algorithm is obviously superior to EKF filter used in the integrated positioning system at present. Moreover, it can greatly enhance the stability and positioning precision of integrated positioning system.