Bacteria-foraging based-control of high-performance railway level-crossing safety drives fed from photovoltaic array

In the past ten years, railway level-crossing accidents have noticeably escalated in an indisputably preposterous manner, this devastating snag opened the floodgates for the frustrating death of a numerous number of the third world's citizens, especially in Egypt. To tackle with this problem, a fully intelligent control system is required, which must be automated without human intervention. So, in this research, a new proposed level-crossing tracking system is designed and introduced. The system comprises a high-performance induction motor (IM) fed from photovoltaic (PV) array, the boom barrier (gate) with its mechanism - as a load - buck-boost converter, inverter, and two smart PI-controllers. The first one is designed to regulate the duty cycle of the converter to its optimum value required to balance between maximum power point tracking (MPPT) and keeping dc-link voltage of the inverter at a minimum level needed to maintain the motor internal torque at rated value. The second PI-controller is designed for speed control of indirect field-oriented vector-control (IFO-VC) IM. The proposed design problems of MPPT, dc-link voltage and speed controllers are solved as optimization problems by bacteria-foraging optimization (BFO) algorithm to search for the optimal PI-parameters. The simulation test results are acquired when using the battery-less PV-array with and without the proposed controllers. Also, results are obtained when applying several prescribed speed trajectories to test the robustness against PV-irradiance fluctuations and motor-dynamic disturbances. From these results, the proposed intelligent controllers are robust compared to classical Ziegler-Nichols (ZN) PI-controllers and also when the motor is directly fed from PV generator without converter.