As well known, Brushless DC (BLDC) motors are widely utilized in numerous applications because of their high efficiency, compact size, and low maintenance. The BLDC motor was generated with an expectation of replacing conventional direct current motor. In the speed control loop, disturbance of the motor system is then mainly caused by the load torque. To deal with the unknown load torque problem, the sliding mode control (SMC) for speed control of the BLDC motor is presented in this paper. Firstly, the mathematical model of BLDC motor and the preliminary mathematics are shown. Secondly, sliding mode controller (SMC) is constructed for speed loop control, and verified stability by using Lyapunov condition. Finally, the feasibility of the given control method was validated by experiment. The obtained result shows that the proposed method is robust with the unknown disturbance value.

The increasing global energy demand is driving the deployment of renewable energy in the electrical power infrastructure, which emphasizes the critical importance of grid-connected inverters (GCIs). As the power injected into the utility grid increases, GCIs commonly operate in parallel. However, interactions between multiple GCIs and the presence of LC grid impedance pose significant challenges to the stable operation of GCIs. Existing control strategies to deal with multiple GCIs often neglect the capacitive component of grid impedance, which results in instability and deteriorated power quality in a complex grid condition. To overcome these problems, this study proposes a current control scheme and stability assessment of multiple GCIs. To effectively mitigate high-frequency resonance, the proposed method is achieved by an incomplete state feedback control which eliminates the feedback control terms for unmeasurable states. Furthermore, resonant and integral control terms are incorporated to reduce steady-state error as well as to improve harmonic compensation induced by the PCC voltages. A full-state observer is employed to reduce sensing requirements and simplify system complexity. Multiple-GCI behavior is comprehensively analyzed under complex grid environments. A comprehensive stability assessment is also conducted to evaluate the interactions of multiple GCI systems with LC grid impedance. The effectiveness of the designed controller in enhancing power quality and guaranteeing system stability is validated by theoretical analysis, PSIM simulations, and experimental tests on a DSP-controlled 2 kW prototype system.

As renewable energy source-based distributed generation is more widely connected to the grid, stable current control and power quality improvement in grid-connected inverters (GCIs) become more important. To satisfy increasing power demand, multi-inverter systems connected to the grid in parallel are being widely adopted. However, parallel operation may degrade current quality and stability because of inverter interactions under harsh grid conditions. In particular, grid voltage harmonics, voltage imbalance, and frequency variations can also impair current control performance and system stability. To address these concerns, a frequency-adaptive current controller integrated with a Kalman filter (KF)-based observer is developed to ensure a stable operation of multiple GCIs. Moreover, a stability evaluation is presented for multi-inverter systems by using admittance-based stability analysis. A Kalman filter-based state observer is applied to improve the estimation accuracy under noisy measurement conditions. In addition, a moving average filter-based phase-locked loop (MAF-PLL) is applied to improve the detection accuracy and reliability of the grid frequency and phase angle under harsh grid conditions to ensure an effective frequency-adaptive control design. The effectiveness and performance of the proposed current controller are assessed through the PSIM simulations. The simulation results show that the MAF-PLL reduces the maximum frequency fluctuation from $\pm$7 Hz to $\pm$1.1 Hz. In addition, the KF-based observer reduces the RMS estimation error to 0.0001 A. On the other hand, those values are 1.3 A with the conventional observer and 0.0003 A with the LQR-based observer, respectively. The practicality of the proposed scheme is also confirmed experimentally using 2 kW parallel multiple GCI prototype systems under harsh grid conditions.