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Tree physiology optimization on SISO and MIMO PID control tuning

  • A. Hanif Halim
  • I. Ismail
Original Article

Abstract

The tuning of proportional–integral–derivative (PID) controller is essential for any control application in order to ensure the best performance by step change or disturbance. This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). The basic principle of TM simplifies the plant growth into shoots and roots part. The plant shoots grow towards sunlight with the help of nutrients supplied by the root system in order to undergo photosynthesis process, a process of converting light photon into carbon. The carbon gain from the shoots extension will be supplied to the root system in order for the root to grow and search for water plus nutrients. As a result, the nutrients are supplied upwards towards shoot system for further extension. This concept runs iteratively in order to ensure optimum plant growth. The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. TPO also has a unique exploration strategy due to its multiple branches and shoots that can be defined by user. This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Ziegler–Nichols, Tyreus–Luyben and Chien–Hrones–Reswick methods. The results clearly exhibit the capability of TPO algorithm towards finding the optimum PID parameters for SISO and MIMO process with faster settling time and better performance with respect to other methods.

Keywords

Single-input single-output Multiple-input multiple-output Tree physiology optimization Particle swarm optimization Ziegler–Nichols Tyreus–Luyben Chien–Hrones–Reswick 

Notes

Compliance with ethical standard

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Electrical and Electronic Engineering DepartmentUniversiti Teknologi PETRONASTronohMalaysia

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