Owing to the competitive advantages of fast response speed, large pushing force, high reliability, and high precision, the permanent magnet linear synchronous motor (PMLSM) has played an increasingly vital role in various high-speed and high-precision control systems. However, PMLSM exhibits nonlinear behavior in actual operation, and position tracking precision is negatively affected by friction, load changes, and other external disturbances. To meet the growing demand and solve the position tracking control problem for the PMLSM, the control system is critical. Sliding-mode control (SMC) has been used extensively in nonlinear control systems due to its superior performance characterized by simplicity, good dynamic response and insensitivity to parameter perturbation and external disturbances, and has been implemented in PMLSMs to track practical position. The objective of this article is to classify, scrutinize and review the major sliding-mode control approaches for position control of PMLSM. The three different conventional SMC methods, namely the boundary layer approach, the reaching law approach and the disturbance observer-based SMC, are discussed in detail. The four advanced forms of SMC, namely terminal SMC, super-twisting SMC, adaptive SMC and intelligent SMC, are also presented. A comparison of these approaches is given, in which the advantages and disadvantages of each approach are presented; additionally, they are presented in table form in order to facilitate reading. It is anticipated that this work will serve as a reference and provide important insight into position control of PMLSM systems.

A hydraulic system is a key subsystem of heavy-duty machine tools with a high failure intensity, the failure of which often causes shutdown of production and economic loss in machining. Therefore, it is necessary to implement failure analysis to identify the weak links of system and improve the reliability. For hydraulic system, there is often an amount of failure data collected in field, which help to calculate the occurrence probability of basic events through fault tree analysis method. However, the data are incomplete and uncertain. To address this issue, this study presents a fault tree analysis methodology. Experts’ opinions are utilized, combined with field data based on the Dempster–Shafer theory and rough set theory to fill the incompleteness and eliminate the uncertainty. For application in a case study, a fault tree of the hydraulic system of heavy-duty machine tools is firstly constructed. Then, the importance analysis is performed to help identify the weak links of hydraulic system. The results show the critical basic events affecting the safety and reliability of a hydraulic system.

Traditional stick-slip piezoelectric actuators generally have problems such as large backward motion and small load capacity, which affect the driving effect. In this study, the effect of no backward motion and large load capacity is realized by controlling two sawtooth wave-driven piezoelectric stacks on the basis of umbrella-shaped flexible mechanism. The trajectory of the driving foot is simulated by transient simulation and verified by experiment. A prototype of actuator is made, and the effects of voltage, symmetry of sawtooth wave, and the phase difference of the two waves on the driving effect are investigated through experiments, and the optimal driving waveform is found. Experiments have shown that no displacement regression and stable driving is achieved when driving with two sets of sawtooth waves with 100 V, 100% symmetry and 20 V, 70% symmetry. With this drive waveform at 1 Hz, the maximum horizontal and vertical loads are 150 g and 1400 g, respectively. And the maximum driving speed is 13 935 μm s⁻¹ when the driving frequency is 7000 Hz. Experimentally, it is proved that the actuator is able to realize smooth driving and large load capacity without backward motion, and has the same forward and reverse working performance, which has greater research value and market application scenarios.

Heavy-duty machine tools are composed of many subsystems with different functions, and their reliability is governed by the reliabilities of these subsystems. It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities. However, traditional ranking methods based on failure mode effect and critical analysis (FMECA) does not consider the complex maintenance of products. Herein, a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information. In this method, eight reliability indexes, including maintainability and maintenance cost, are considered in the generalized FMECA information. Subsequently, the cognition best worst method is used to calculate the weight of each screened index, and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution. Finally, based on the failure data collected from certain domestic heavy-duty horizontal lathes, the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method. An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.