Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.

Design of solar powered electric vehicle

With the increased trends of industrialization and global economic growth leading to the everchanging petrol prices and other price hikes, private transport system has become a costly affair. All these problems can be addressed with innovation. One of the most feasible solutions is turning towards renewable energies to solve the issues i.e., increasing the use of renewable energies like solar power in the place of fossil fuels. Everyone’s dream of owning a commercially viable solar vehicle is slowly becoming a reality. Electric vehicles are now available at an affordable price. This opportunity is taken towards the design of a Solar powered two-wheeler. Designing a solar vehicle is a multidisciplinary subject that covers the broad and complex aspects from various subjects. In the designed vehicle, solar panel is used as the power source and developed voltage, stored in the battery, is used to the drive the permanent magnet DC motor which drives the rear wheel of the vehicle.

Comparison between butterfly optimization algorithm and particle swarm optimization for tuning cascade PID control system of PMDC motor

In this paper, two optimization methods are used to adjust the gain values for the cascade PID controller. These algorithms are the butterfly optimization algorithm (BOA), which is a modern method based on tracking the movement of butterflies to the scent of a fragrance to reach the best position and the second method is particle swarm optimization (PSO). The PID controllers in this system are used to control the position, velocity, and current of a permanent magnet DC motor (PMDC) with an accurate tracking trajectory to reach the desired position. The simulation results using the Matlab environment showed that the butterfly optimization algorithm is better than the particle swarming optimization (PSO) in terms of performance and overshoot or any deviation in tracking the path to reach the desired position. While an overshoot of 2.557% was observed when using the PSO algorithm, and a position deviation of 7.82 degrees was observed from the reference position.