Bridging Control System Education and Industrial Practice through a Real-Time Control System Architecture
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The limited accessibility, high cost, and low scalability of industrial control platforms constrain hands-on learning in automation education. This study presents a real-time control system architecture that bridges instructional requirements with industrial control principles through deterministic execution and structured logic representation. The system integrates ladder-based programming with cyclic scan execution and direct I/O mapping to ensure consistent real-time operation. A design and development methodology based on the adopted-ADDIE framework was employed to guide system realization and validation. The system was evaluated through expert-based assessment using a four-point Likert scale, followed by feasibility, content validity, and reliability analyses. Results indicate high technical feasibility, with technical quality reaching 83.04% and display quality 84.38% (very feasible), while instructional aspects range from 75.00% to 79.55% (feasible). Content validity achieved Aiken’s V values of 0.852 (very high) and 0.716 (high), with reliable expert agreement (Sig. > 0.05). These findings validate the proposed architecture as a scalable and reliable control system platform for automation learning.
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