This manuscript proposes an improved DC-DC converter framework using hybrid control algorithm for minimizing brushless DC motor (BLDC) torque ripple (TR). At first, the modeling of the brushless DC motor is intended by an enhanced Cuk converter (ECC). The function and performance of the Cuk converter are updated using application of switched inductor. In this way, the control system integrates two control loops such as speed and torque control loop, which is employed for improving BLDC performance. Therefore, the Invasive Weed Optimization (IWO) and Local Random Search (LRS) are proposed to enhance control loop operations. In the IWO algorithm, the LRS approach is used as part of the dispersion process to build up the course of action to find precision. This manuscript explores the IWO-LRS algorithm for limiting BLDC motor speed and torque error. Nevertheless, the exit from the proposed approach is subject to the speed and torque controller input. The better optimal gain parameters have been worked out for the update of the controller operation through the aid of necessary goal functions. The proposed controller topology is activated in MATLAB/Simulink site and the performance is evaluated using other existing methods, like Particle Swarm Optimization (PSO), Bacterial Foraging (BF) algorithm.
An optimization approach for two-area power system with Unified Power Flow Controller (UPFC) is proposed in this paper. The proposed method is the Atomic Orbital Search (AOS) approach. The proposed approach is applied to achieve full utilization of UPFC and keeps the parameters uncertain. The multivariable PI controller is utilized to control the system controller and eliminates the negative interaction of the controllers. The proposed approach combines the two subsystems by converting algebraic subsystem using differential approximation, which leads to a nonlinear system. The proposed approach provides efficient voltage regulation and quicker damping of inter-area mode oscillations. The proposed UPFC controller eliminates generator oscillation and fault condition, which guarantee the stability of the system as well as provides dynamic power flow control under the tie-line. At last, the proposed method is simulated on MATLAB platform and compared with existing methods. From this comparison, it is shown that the proposed approach provides less oscillation than the existing approach.
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