Genetic algorithm-based optimization PID controller is a M.Tech project topic for Electronics & Communication Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Genetic algorithm-based optimization PID controller Project Details
| Abstract |
This project designs, models, and tests an optimized PID controller for controlling the speed of a DC motor. A genetic algorithm (GA) is used to find the best controller settings, improving on classic methods like Ziegler‑Nichols. A detailed mathematical model of the DC motor is built in MATLAB. The model includes realistic changes in load and the motor’s operating limits. The GA is set up with the following parameters: – Crossover rate: 90 % – Mutation rate: 3 % – Population size: 20 individuals – Number of generations: 100 The algorithm minimizes a multi‑objective fitness function that combines total error, settling time, and overshoot. Simulation results show that the GA‑tuned
controller (Kp = 95.984, Ki = 0.250, Kd = 13.005) beats traditional tuning. Overshoot drops by 59 % while rise times stay fast. The controller also handles sudden load torque spikes of 10 N·m and 20 N·m without losing stability. The work offers a clear step‑by‑step method for advanced control‑system design, useful for both research projects and real‑world motor‑drive applications.
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| Reference Paper |
Genetic algorithm-based optimization of PID controller parameters for DC motor speed control |
| Domain |
Electronics & Communication Engineering |
| Sub-Domain |
VLSI & Embedded Systems / Embedded Systems / Motor Control |
| PDF Download |
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| Get Help |
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