The control of clamping force has a significant influence on the braking performance of low-floor trams. However, the load torque variations, strong nonlinearity and complex structure of electromechanical brake (EMB) systems present challenging the clamping force control issues. In this paper, an EMB system mathematical model is established. Then, an enhanced sliding-mode reaching law (ESMRL) is investigated to address these issues. In addition, novel gap distance elimination and adjustment strategies are proposed to improve the response quality and adjust the gap distance in a simple and low-cost way. Taking advantages of minimal chattering and short reaching times, the proposed ESMRL enhances the dynamic performance and tracking accuracy of the clamping force control. Finally, simulation and experimental results are offered to validate the effectiveness and superiority of the proposed control strategy.

This article presents a sensorless control strategy for permanent magnet synchronous motors (PMSMs) with low chattering based on an adaptive sliding mode observer (SMO). The strategy incorporates an improved SMO with a novel adaptive fast power reaching law (NAFPRL-SMO) and a higher-order phase-locked loop based on an extended state observer (ESO-HOPLL). First, the NAFPRL-SMO is designed with adaptive gains to address the issue of slow reaching velocity that is commonly associated with traditional power reaching laws when far from the sliding mode surface. This is achieved by utilizing system state variables for enhancement. Then, to effectively suppress the chattering phenomenon, a sigmoid function is employed as a switching function. Finally, the ESO-HOPLL structure is utilised to reduce the effects of differential noise and improve the performance of the system, allowing for precise estimation of rotor position and speed information. Simulations and experiments are conducted to validate the steady-state and dynamic performance of the proposed sensorless control strategy, demonstrating its effectiveness and potential for enhancing performance in PMSM applications.

The Hall sensor is the most commonly used position sensor of the permanent magnet brushless direct current (PMBLDC) motor. Its failure may lead to a decrease in system reliability. Hence, this article proposes a novel methodology for the Hall sensors fault diagnosis and fault-tolerant control in PMBLDC motor drives. Initially, the Hall sensor faults are analyzed and classified into three fault types. Taking the Hall signal as the system state and the conducted MOSFETs as the system event, the extended finite state machine (EFSM) of the motor in operation is established. Meanwhile, a motor speed observer based on the super twisting algorithm (STA) is designed to obtain the speed signal of the proposed strategy. On this basis, a real-time Hall sensor fault diagnosis strategy is established by combining the EFSM and the STA speed observer. Moreover, this article proposes a Hall signal reconstruction strategy, which can generate compensated Hall signal to realize fault-tolerant control under single or double Hall sensor faults. Finally, theoretical analysis and experimental results validate the superior effectiveness of the proposed real-time fault diagnosis and fault-tolerant control strategy.

This paper presents an asynchronous output-feedback control strategy of semi-Markovian systems via sliding mode-based learning technique. Compared with most literature results that require exact prior knowledge of system state and mode information, an asynchronous output-feedback sliding surface is adopted in the case of incompletely available state and non-synchronization phenomenon. The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem. Based upon the co-occurrence of two subsystems, the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions. Furthermore, a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion. Finally, the proposed theoretical method is substantiated through two numerical simulations with the practical continuous stirred tank reactor and F-404 aircraft engine model, respectively.