Detection Minimization Time Delay Distributed is a M.Tech project topic for Electrical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Detection Minimization Time Delay Distributed Project Details
| Abstract |
Distributed Control Systems (DCS) suffer from Multi‑Source Communication Delays (MSCD), which hurt real‑time monitoring and make control loops unstable. This study looks at the latency problems found in a test setup for an industrial food‑paste plant. To tackle MSCD, we propose a Multi‑Aware Particle Swarm Optimisation (M‑PSO) method. M‑PSO finds communication delays by tuning two key network features: routing speed and bandwidth. The algorithm adds gradient‑descent steps and updates its learning rate on the fly, so it stays accurate even when network conditions change. We also introduce a Network Management Algorithm (NMA) that uses priority scheduling. NMA reallocates bandwidth to reduce latency. Tests against standard Quality of Service (QoS) metrics
show that the combination of M‑PSO and NMA makes the DCS network more reliable and efficient. For M‑Tech researchers, this framework offers a clear way to simulate and assess delay‑reduction strategies in industrial communication networks. The work relies on heuristic optimisation, so future research should combine it with adaptive machine‑learning models to cope with highly non‑linear, evolving network topologies.
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| Reference Paper |
Detection and Minimization of Time Delay in Distributed Control System |
| Domain |
Electrical Engineering |
| Sub-Domain |
Control Systems / Advanced Control / Neural Network Control |
| PDF Download |
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| Get Help |
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