Search Results (4)

Ventilation systems are susceptible to errors, external disruptions, and nonlinear dynamics. Maintaining stable operation and regulating these dynamics require an efficient control system. This study focuses on the speed control of ventilation systems using a super twisted sliding mode observer (STSMO), which provides robust and efficient state estimation for sensorless control. Traditional SM control methods are resistant to parameter fluctuations and external disturbances but are affected by chattering, which degrades performance and can cause mechanical wear. The STSMO leverages the super twisted algorithm, a second-order SM technique, to minimize chattering while ensuring finite-time convergence and high resilience. In sensorless setups, rotor speed and flux cannot be measured directly, making their accurate estimation crucial for effective ventilation drive control. The STSMO enables real-time control by providing current and voltage estimations. It delivers precise rotor flux and speed estimations across varying motor specifications and load conditions using continuous control rules and observer-based techniques. This paper outlines the mathematical formulation of the STSMO, highlighting its noise resistance, chattering reduction, and rapid convergence. Simulation and experimental findings confirm that the proposed observer enhances sensorless ventilation performance, making it ideal for industrial applications requiring reliability, cost-effectiveness, and accuracy. Full article

This paper delves into a comprehensive study of a wide-speed-range sensorless control approach for surface-mounted permanent magnet synchronous motors (SPMSMs). In the low-speed range, a novel high-frequency pulse voltage injection (HFPVI) method is introduced for rotor position estimation, which does not depend on motor saliency and is well-suited for SPMSMs. This method incorporates a second-order generalized integrator (SOGI) and a new modulation signal to enhance the accuracy of rotor position estimation. For medium-to-high speeds, an improved super-twisting sliding mode observer (STSMO) utilizing a continuous hyperbolic tangent function is proposed to mitigate chattering. Additionally, a new phase-locked loop (NPLL) is introduced to accurately obtain the rotor position. Furthermore, this paper designs an exponential weighted switching function to facilitate a smooth transition of the motor from the low-speed domain to the medium- and high-speed domains. The effectiveness and superiority of the proposed methods are validated through simulations and experiments conducted on an RTU-BOX platform. The rotor position estimation errors of the proposed new HFPVI method and the improved STSMO method under various operating conditions are both approximately 0.05 rad (2.8 elc·deg), and the SPMSM can switch smoothly from the low-speed range to the medium- and high-speed ranges. Full article

To enhance the control performance of a permanent magnet linear synchronous motor (PMLSM) and to improve its dynamic response performance and steady-state accuracy, a PMLSM model predictive integrated control (MPC) system based on a super-twisting sliding mode observer (ST-SMO) is proposed. According to the mathematical model of a PMLSM, this paper designs a three-step model to predict the comprehensive control correction factor, optimize the prediction speed and current, reduce the response time, and enhance the system’s stability. Meanwhile, in order to solve the problem of the PMLSM’s high dependence on mechanical sensors, the ST-SMO is introduced to observe the rotation speed of PMLSM, which has better tracking performance and observation accuracy than a traditional sliding mode observer (SMO). Finally, the experimental verification is carried out on the PMLSM experimental platform. The software simulation and hardware experiment results show that the control system designed in this paper not only simplifies the overall structure of the system, but it also has better control performance and tracking ability. Compared with traditional control methods and SMO, it has better control performance, stability, and speed-tracking performance. Full article

A novel method for Li-ion battery state of charge (SOC) estimation based on a super-twisting sliding mode observer (STSMO) is proposed in this paper. To design the STSMO, the state equation of a second-order RC equivalent circuit model (SRCECM) is derived to represent the dynamic behaviors of the Li-ion battery, and the model parameters are determined by the pulse current discharge approach. The convergence of the STSMO is proven by Lyapunov stability theory. The experiments under three different discharge profiles are conducted on the Li-ion battery. Through comparisons with a conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF), the superiority of the proposed observer for SOC estimation is validated. Full article