The PID controller optimisation module using Fuzzy Self-Tuning PSO for Air Handling Unit in continuous operation. (January 2023)

• Record Type: Journal Article
• Authors: Ambroziak, Arkadiusz; Chojecki, Adrian
• Is Part Of: Engineering applications of artificial intelligence. Volume 117:Part A(2023)
• Publication Date: 2023-01
• Subjects: PID tuning -- PSO -- Fuzzy logic -- HVAC control -- FST-PSO -- NARMAX modelling; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105485
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The current development of modern computational methods makes it possible to improve the performance of classical components and systems. The work provides a method for optimising the settings of a proportional–integral–derivative (PID) controller for an Air Handling Unit (AHU) equipped with many actuators with different parameters. The optimisation has been divided into two components: an offline optimiser consisting of Non-linear Autoregressive Modelling with Moving Average and Exogenous Input (NARMAX) and a Fuzzy Self-Tuning Particle Swarm optimisation (FST-PSO) metaheuristic algorithm and auxiliary module that automatically sends the optimised values to the controller based on information about the actuators currently operating. The solution has proven successful, making optimisation without AHU downtime and without interfering with the existing, factory-fitted control system and is implemented as one of the Building Management System (BMS) part in a real building. The described method reduced the oscillations that led to actuator failures and the need for parameter adjustments by the operator. No further failures occurred after module deployment, and the quality of control as measured by integral quality factors improved by an average of 64%. An application is possible in new and existing AHUs increasing their energy efficiency and fault-free operation time. Graphical abstract: