PI-Fuzzy rule based controller for Analysis and performance evaluation of dc motor speed control

This paper presents the finding on designing the fuzzy logic controller and analysis of the step input test on the model and control design. The PI-type fuzzy logic controller (FLC) was designed to control the velocity of the rolling spherical robot. The spherical robot model was tested with step input signal to analysis the effectiveness of the designed Fuzzy logic controller with 25-membership rule being constructed in Fuzzy toolbox MATLAB using triangular membership function and combination of gaussian and sigmoidal membership function. The output scaling factor (output gain) of FLC was tuned using Response Optimization toolbox and Particle Swarm Optimization to improve the system performance. Optimization using Matlab toolbox is done by specified the desired step response characteristics while in PSO, minimizing the Integral Absolute Error (IAE) is used as on objective of the optimization. The combined membership function shows better performance with less 8% overshoot, rise time less than 2s and settle at less than 3s after the response optimization process. Meanwhile, the PSO manage to tune the gain to reduce the IAE but contain large overshoot and longer settling time.

show abstract

Sensor-less Brushed DC Motor Speed Control with Intelligent Controllers

Salmaninejad

Mayorga

2021

Wseas Transactions on Systems

View full text Add to dashboard Cite

A Direct Current (DC) Motor is usually supposed to be operated at a desired speed even if the load on the shaft is exposed to changes. One of its applications is in automatic door controllers like elevator automatic door drivers. Initially, to achieve this aim, a closed loop control can be applied. The speed feedback is usually prepared by a sensor (encoder or tachometer) coupled to the motor shaft. Most of these sensors do not always perform well, especially in elevator systems, where high levels of noise, physical tensions of the mobile car, and maintenance technicians walking on the car, make this environment too noisy. This Paper presents a new approach for precise closed loop control of the DC motor speed without a feedback sensor, while the output load is variable. The speed here is estimated by the Back EMF (BEMF) voltage obtained from the armature current. First, it is shown that a PID controller cannot control this process alone, and then intelligent controllers, Fuzzy Logic Controller (FLC) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), assisting PID are applied to control this process. Finally, these controllers’ performance subjected to a variable mechanical load on the motor shaft are compared.

show abstract

PI-Fuzzy rule based controller for Analysis and performance evaluation of dc motor speed control

Cited by 3 publications

References 8 publications

Comparative analysis among Pareto, Pareto — Fuzzy logic and Pareto — Fuzzy logic PI for distribution networks with the presence of DGs

Comparative analysis among Pareto, Pareto — Fuzzy logic and Pareto — Fuzzy logic PI for distribution networks with the presence of DGs

Velocity Control for Spherical Robot using PI-Fuzzy Logic

Sensor-less Brushed DC Motor Speed Control with Intelligent Controllers

Contact Info

Product

Resources

About