Active Current Sharing of a Parallel DC-DC Converters System Using Bat Algorithm Optimized Two-DOF PID Control

Abstract

This paper presents a current sharing method to actively balance the output currents of a parallel dc-dc converters' (PDCC) system regarding the demanded power. First, the operating principle of the PDCC system with parallel-connected bidirectional converters is studied. To regulate the output voltage in dc bus and share the output currents of the individual converters, a dual-loop control architecture comprising an outer voltage control loop and multiple inner current control loops is designed based on the automatic master-slave control scheme. Moreover, a feedback-type two-degree-of-freedom proportionalintegral-derivative (FB2PID) controller is introduced to obtain the pulse-width modulation control signals for the converters. In order to improve the dynamic response and robustness of the active current-sharing control performances of the FB2PID controlled PDCC system, a bat algorithm (BA)-optimized FB2PID control system is further proposed to concurrently and dynamically optimize the control parameters of the FB2PID controller in the current control loop. Thus, the output current of each converter can be controlled to share the demand power equally in the presence of uncertainties. Finally, the simulation and experimental results reveal that the proposed BA-optimized FB2PID control system outperforms the conventional PID and FB2PID control systems with regard to the voltage regulation and current sharing performances under the time-varying electric load condition. INDEX TERMS Bat algorithm, current sharing, parallel dc-dc converters system, optimization, two degreeof-freedom proportional-integral-derivative control.

Dynamic Modeling and Torque Feedforward based Optimal Fuzzy PD control of a High-Speed Parallel Manipulator

“…About the setting of the PD controller, base gains . In order to obtain a good optimization result, the parameters of bat algorithm can be set referenced to [32] for CTC), even if un-modeled uncertainty is existing. What's more, it can be seem in Fig.…”

“…From (32), obviously, the tracking error e can converge to zero in finite time by choose appropriate Kp and Kd. And the method of trial and error can be used in gains selection.…”

“…An excellent controller needs well parameter tuning. And a lot of metaheuristic parameter searching algorithm, such as particle swarm optimization (PSO) algorithm [31], bat algorithm (BA) [32], grey wolf optimization algorithm (GWO) [34], genetic algorithms (GA) [35][36] and cuckoo search (CS) algorithm [37] are adopted in optimization of parameter of controller for its powerful performance for tough optimization problems. T. M. Ahmed et al [16] used PSO to optimize the parameters of fractional-order PID controller.…”

Thirteen-Level UXE-Type Inverter With 12-Band Hysteresis Current Control Employing PSO Based PI Controller

“…These techniques also improve the response of steady-state and the dynamic response of the system [22]. Different optimization techniques like genetic algorithm [23], Particle swarm optimization (PSO) [24], Bee algorithm [25], BAT algorithm [26] and Differential evolution [27] are being employed in obtaining near-to-exact solutions. These techniques give a fast dynamic response within a few iterations and control the inverter more effectively.…”

Comparison of basic droop control with linear and nonlinear internal control of boost converters feeding resistive load

“…To overcome the error in current load sharing, some types of controls, such as active load sharing [19][20][21][22] and droop control [4,5,8,23] have been proposed in the literature. If the active load sharing method presents the advantages of being simple to implement with a good performance, its major drawbacks consist on the need of a large bandwidth communication link and its low flexibility and modularity.…”