For elevators, appropriate speed control is pivotal for ensuring the safety and comfort of passengers and optimizing energy efficiency, system stability, and service life. Therefore, the design and implementation of effective speed control strategies are crucial for the operation and management of modern elevator systems. In response to this issue, this paper establishes a dynamic model of an elevator through mechanism analysis. Then, a novel fractional-order sliding mode control strategy with the assistance of a fixed-time adaptive sliding mode observer is proposed. The designed observer can effectively monitor and counteract external perturbations, thereby enhancing the stability and precision of the control system. The fractional-order sliding mode controller can realize a fixed-time convergence property, which is rigorously proven in the sense of Lyapunov. Finally, the effectiveness and superiority of the control scheme are validated by simulations compared with benchmark controllers.

The Weibull distribution is widely used in reliability estimation across industries, but accurately identifying its parameters remains a challenging task. This research proposes an efficient method for estimating Weibull distribution parameters by combining the maximum likelihood method with optimization theory. First, the parameter estimation problem is formulated as an optimization problem. A constrained search space partitioning framework is introduced, leveraging parameter-specific minimum and maximum bounds for the shape, location, and scale parameters. By dividing the search space into smaller subspaces for each parameter, the method constrains the search direction, significantly reducing estimation time. To address the local optima problem common in heuristic algorithms, a randomness operator is integrated into the optimization process. The proposed constrained search space partitioning framework is implemented using a conventional g-best version of the particle swarm optimization algorithm with historical fault data. Experimental results demonstrate that the proposed scheme outperforms state-of-the-art methods and conventional optimization-based approaches in terms of estimation accuracy and computational efficiency.

This paper proposes a passive fault-tolerant control strategy for a multi-caliper disc elevator brake system subject to unknown external disturbances and multiple actuator faults. Initially, a detailed analysis of the dynamic equations of the actuator in a multi-caliper disc elevator brake system with actuator faults is conducted. Subsequently, a nonsingular terminal sliding mode fault-tolerant control scheme with rapid fixed-time convergence is proposed, where the settling time is independent of the system’s initial state and can be preset through design parameters. The upper bound of the convergence time is derived using Lyapunov theory, ensuring that the faulty elevator brake control system converges within a predetermined fixed time. Ultimately, theoretical analysis and numerical simulation results confirm that the proposed controller can effectively handle the effects of actuator faults, parametric uncertainties, and external disturbances, ensuring satisfactory tracking accuracy.