Abstract. This paper proposes a particle swarm optimization algorithm tuned fuzzy terminal sliding mode control for the application of UPS inverters. Though classic sliding mode control (SMC) is insensitive to system uncertainties, it possesses an infinite system-state convergence time. For high-accuracy tracking control, a terminal sliding mode control (TSMC) is developed to provide a finite system-state convergence time. However, difficult estimation occurs in TSMC, and incurs high UPS inverter voltage harmonics and slow dynamic response. To obtain high-quality UPS inverter output voltage, a fuzzy logic (FL) with a computationally simple and practically easy estimator is integrated into TSMC to resolve system uncertainties. Simultaneously, the particle swarm optimization (PSO) algorithm is applied to optimally tune the control gains of the TSMC with a fuzzy estimator. Results indicate that the presented combination of PSO, FL and TSMC yields a closed-loop UPS inverter with good performance under various loading conditions. Simulation and experimental results indicate that the proposed control can achieve low total harmonic distortion (THD) under nonlinear loading conditions and fast dynamic response under transient loading conditions.

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This paper focuses on the front wheel angle tracking control problem of the steer-by-wire system subject to unmodeled dynamics, uncertain parameters, external disturbances and measurement noises. Considering the measurement uncertainties of front wheel angle and angular velocity, a new steering dynamics model with matched and unmatched disturbances is built for control design. An unmatched disturbance observer is designed to attenuate the effects of unmatched measurement uncertainties and further improve the angle tracking precision of steady-state. A matched disturbance observer is developed to cancel the effects of matched disturbances, and to alleviate the chattering of sliding mode control. Based on the outputs of these two disturbance observers and the sliding mode controller (SMC), a proportional differential sliding mode control (pdSMC) approach is developed by a new sliding manifold for angle tracking of the steer-by-wire system. The developed approach has been downloaded into a steering control unit, and tested in real-world conditions using vehicle test bench to fully realize electric motor steering by wire in engineering practice. Experimental results show that compared with the SMC controller, the pdSMC controller reduces the mean absolute error of the front wheel angle by 52% and 58.9% in the steering tests of step response and slalom path, respectively.

Abstract. In this paper, a fuzzy grey predictor (GP) compensated time-varying variable structure controller (TVVSC) is developed and applied to solar inverters. TVVSC can shorten the reaching phase and ensure the sliding mode occurrence from an arbitrary initial state. However, while loading is a severe nonlinear condition, the TVVSC may suffer from chattering and steady-state error problems, thus deteriorating solar inverter performance. A GP is thus devoted to alleviate the chattering when the system uncertainty bounds are overestimated, and to reduce the steady-state error when the system uncertainty bounds are underestimated. However, the GP with a fixed forecasting value causes long rise time or large overshoot of the system response. Thus, fuzzy logic (FL) is applied to obtain flexible forecasting values to improve the system performance. With the proposed controller, the robustness of the solar inverter system can be enhanced, and a high-quality solar inverter sinusoidal output voltage with low voltage harmonics and fast dynamic response can be obtained, even under nonlinear loading. The theoretical analysis, design procedure, computer simulations, and digital signal processing (DSP)-based experimental implementation for solar inverters are presented to verify the efficacy of the proposed controller.