Inertial support for hybrid AC/DC microgrid systems is provided by the virtual synchronous generator (VSG). However, the fast performance of the system is neglected while enhancing the stability of the system. To address this problem, an adaptive virtual inertia control strategy based on VSG technology is proposed. This control approach adaptively adjusts the system virtual inertia when the system operation deviates from the nominal value, by slowing down the rate of change of AC frequency and DC voltage and improving the deviation of AC frequency and DC voltage. Meanwhile, when the AC frequency and DC voltage restore back to the rated value, the rate of change of AC frequency is accelerated and the DC voltage fluctuation is reduced by dynamically adjusting the virtual inertia of the system. The proposed adaptive virtual inertia control method combines the advantages of large and small inertia to effectively improve the dynamic response of the system voltage and frequency in both rectifier and inverter modes. Finally, the simulation and experimental results verify the effectiveness of the proposed control algorithm.
The pattern synthesis and activated element selection for conformal array is investigated based on hybrid particle swarm optimization-gravitational search algorithm (PSOGSA) in this paper. With the introduction of PSOGSA algorithm which is a novel hybrid optimization technique, the element excitations are optimized to obtain the desired pattern for conformal array in the case of considering uncoupled and coupled element pattern. Numerical simulation and full-wave electromagnetic calculation verify the advantage and efficiency of our method. Then, a novel strategy of activated element selection based on PSOGSA algorithm is proposed for saving the energy consumption in conformal array.
The inverted pendulum is a multivariable, rapid, nonlinear unstable system. LQR optimal control is often used in inverted pendulum control for its good stability. According to optimal determination problem of the weighting matrix Q and R in LQR, an improved hybrid genetic algorithm is adopted in LQR optimal controller design in double inverted pendulum and the optimal parameter values can be find by effective use of its intelligent search, progressive optimization features characters. This controller is successfully used in double inverted pendulum. The experimental results show that the optimal controller designed by this method has small overshoot and fast response. It can actually control the inverted pendulum system to achieve stability and proves the feasibility of the control method.
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