PSO BASED TAKAGI-SUGENO FUZZY PID CONTROLLER DESIGN FOR SPEED CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR

A permanent magnet synchronous motor (PMSM) is one kind of popular motor. They are utilized in industrial applications because their abilities included operation at a constant speed, no need for an excitation current, no rotor losses, and small size. In the following paper, a fuzzy evolutionary algorithm is combined with a proportional-integral-derivative (PID) controller to control the speed of a PMSM. In this structure, to overcome the PMSM challenges, including nonlinear nature, cross-coupling, air gap flux, and cogging torque in operation, a Takagi-Sugeno fuzzy logic-PID (TSFL-PID) controller is designed. Additionally, the particle swarm optimization (PSO) algorithm is developed to optimize the membership functions' parameters and rule bases of the fuzzy logic PID controller. For evaluating the proposed controller's performance, the genetic algorithm (GA), as another evolutionary algorithm, is incorporated into the fuzzy PID controller. The results of the speed control of PMSM are compared. The obtained results demonstrate that although both controllers have excellent performance; however, the PSO based TSFL-PID controller indicates more superiority

Performance degradation of surface PMSMs with demagnetization defect under predictive current control

To control the current of a surface mounted permanent magnet synchronous machine fed by a two-level voltage source inverter, a large variety of control algorithms exists. Each of these controllers performs differently concerning dynamic performance and control- and voltage quality, but also concerning sensitivity to demagnetization faults. Therefore, this paper investigates the performance degradation of three advanced predictive controllers under a partial demagnetization fault. The three predictive controllers are: finite-set model based predictive control, deadbeat control, and a combination of both previous algorithms. To achieve this goal, the three predictive controllers are first compared under healthy conditions, and afterwards under a partial demagnetization fault. A PI controller is added to the comparison in order to provide a model-independent benchmark. Key performance indicators, obtained from both simulations and experimental results on a 4 kW axial flux permanent magnet synchronous machine with yokeless and segmented armature topology, are introduced to enable a quantification of the performance degradation of the controllers under a demagnetization fault. A general conclusion is that the deadbeat controller shows superior control quality, even under partial demagnetization

Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes