https://orcid.org/0000-0002-4602-2251
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Abstract
This paper proposed a multiple-node hormone regulation neuroendocrine-proportional-integration- differential (MnHR-NEPID) controller based on adaptive safe experimentation Dynamics (ASED) for nonlinear multi-input-multi-output (MIMO) systems. In the existing neuroendocrine-PID (NEPID) controller of the single-input-single-output (SISO) system, only a single node of hormone regulation is used due to a single control variable. Meanwhile, in the MIMO system, since having many control variables, it is worth introducing an MnHR-NEPID for better controller performance by prioritizing each node's control regulation from their level of error. In particular, instead of considering its own hormone regulation, each node's hormone regulation is also generated based on the change of error from other control variables or nodes if the error of that corresponding control variable exceeds the given error threshold. Here, the relation between hormone regulation and the change of error is adopted based on the normalized Gaussian function. As a result, better prioritize control regulation with heightened control accuracy can be subsequently achieved due to interactions between multiple nodes of hormones available for the nonlinear MIMO system. The performance error and control input for several nonlinear MIMO systems were further tracked to assess the proposed controller's performance. Standard PID, NEPID, and sigmoid-based secretion rate neuroendocrine-PID (SbSR-NEPID) controllers were also compared. Thus, this simulation work has acknowledged higher accuracy within the design of an MnHR-NEPID controller, with comparatively superior objective function and total norm of error resulted in better control performance.
Acknowledgements
The success of this research is bestowed by the support from Skim Latihan Akademik Bumiputra (SLAB) by the Malaysian Ministry of Higher Education (MOHE); and financial assistance provided through an internal university grant from the postgraduate research scheme (PGRS) (PGRS-180349), courtesy of Universiti Malaysia Pahang.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Funding
Notes on contributors
Mohd Riduwan Ghazali
Mohd Riduwan Ghazali BEng. in electrical-mechatronics in August 2007 and MEng. in (mechatronics & automatic control) at UTM Malaysia Mei 2010. Currently, he is lecturer at Universiti Malaysia Pahang, Malaysia. His research interest is in data-driven control, mechatronics system, robotics and control instrumentations.
Mohd Ashraf Ahmad
Mohd Ashraf Ahmad received BEng. in electrical-mechatronics June 2006, MEng. in (mechatronics & automatic control) at UTM Malaysia, and Doctor of Informatics (Systems Science), Kyoto University, Japan, March 2015. Currently, senior lecturer at Universiti Malaysia Pahang, Malaysia. His research interest is in model-free control, vibration control, control of mechatronics systems and identification of nonlinear systems. Email: [email protected]
Raja Mohd Taufika Raja Ismail
Raja Mohd Taufika Raja Ismail received BEng. in electrical eng., UTM Malaysia, 2004, MSc in mathematics, UTM Malaysia, 2006 and PhD in electrical engineering, University of Technology Sydney, Australia, 2015. Currently, he is senior lecturer at Universiti Malaysia Pahang, Malaysia. His research interest is in dynamics modeling and control, robust control and automation, robotics and automation in construction. Email: [email protected]