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All Journal Journal of Power, Energy, and Control Applied Engineering, Innovation, and Technology
Issaka, Dienatu
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Control Strategy Assessment: PID and Fuzzy-PID for Compound DC Motor Systems Sam-Okyere, Yaw Amankrah; Osei-Kwame, Emmanuel; Issaka, Dienatu; Arkorful, Isaac Papa Kwesi
Journal of Power, Energy, and Control Vol. 2 No. 2 (2025)
Publisher : MSD Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62777/pec.v2i2.74

Abstract

Compound DC motors, prized for their high torque and speed in industrial applications, demand robust control under nonlinear conditions. This study advances the field of Adaptive Neuro-Fuzzy Interface (ANFIS) by comparing a Ziegler-Nichols-tuned Proportional-Integral-Derivative (PID) controller with a novel ANFIS-PID controller for a compound DC motor. Unlike prior work, the research focuses on the unique dynamics of compound motors for real-time applications. Using MATLAB Simulink simulations. Performance was assessed via overshoot, rise time, settling time, and steady-state error under no-load and full-load conditions. The PID controller yielded 11.789% overshoot, 1.140s rise time, and 2.251s settling time, while the ANFIS-PID achieved 6.989% overshoot, 0.951s rise time, and 1.962s settling time, with a 50% lower steady-state error. These results, validated across 10 runs (p < 0.05), highlight the ANFIS-PID’s superior adaptability to the motor’s series-shunt dynamics, offering a 40.7% overshoot reduction.
Internet of Things (IoT) Based Fire Detection and Suppression System Issaka, Dienatu; Sam-Okyere, Yaw Amankrah; Osei-Kwame, Emmanuel
Applied Engineering, Innovation, and Technology Vol. 2 No. 2 (2025)
Publisher : MSD Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62777/aeit.v2i2.70

Abstract

Fire incidents cause significant threats to life and property, particularly in critical infrastructure. This research presents the design and implementation of an Internet of Things (IoT)-based fire detection and suppression system featuring real-time monitoring and scalable sensor integration. The system integrates an ATmega328p microcontroller, RF transceivers, flame and smoke sensors, NodeMCU (ESP8266), solenoid valves, relays, a jockey pump, and water sprinklers. Sensor fusion ensures high detection accuracy, triggering suppression only upon simultaneous smoke and flame detection to minimize false positives. Communication between transceivers controls the pump operation, while the NodeMCU transmits sensor data to a remote web server via Wi-Fi for continuous monitoring. When a fire is detected by the sensors, the controller promptly activates the fire alarm system, which in turn triggers the jockey pump to discharge water through the sprinkler system at the affected locations.
Co-Authors Arkorful, Isaac Papa Kwesi Osei-Kwame, Emmanuel Sam-Okyere, Yaw Amankrah