Citation

Sarker, Md. Tanjil and Mansor, Sarina and Al Farid, Fahmid and Abdul Karim, Hezerul and Ramasamy, Gobbi (2023) Investigation of Optimal Perturbation Signals for Multivariable System Under Model Predictive Control. In: 2023 IEEE 11th Conference on Systems, Process & Control (ICSPC), 16-16 December 2023, Malacca, Malaysia.

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Abstract

Model Predictive Control (MPC) is a widely used control strategy for multivariable systems due to its ability to handle complex dynamics and constraints. The design of perturbation signals that can improve MPC’s performance. This research investigates the selection of optimal perturbation signals for multivariable systems under MPC to enhance control effectiveness. Three dissimilar methods to shape of the amplitude spectra has been tasted with three different signal-tonoise ratios (SNRs). The scenarios with and without constraints in the closed loop setting are also studied for multivariable system. The findings offer valuable guidance for practitioners seeking to enhance the performance of MPC-based control systems in various applications, including industrial processes and advanced robotics.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	System identification
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	27 Mar 2024 02:19
Last Modified:	27 Mar 2024 02:20
URII:	http://shdl.mmu.edu.my/id/eprint/12201

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