Auto-Tuning of Multivariable PID Controllers Using Iterative Feedback Tuning

Sommer, Steffen; Kienle, Achim

doi:10.1524/auto.2012.0969

Cited by 4 publications

(1 citation statement)

References 14 publications

(16 reference statements)

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“…In contrast, the single input-output control system is denoted as SISO control. SISO PID control is available in most commercial controllers [3] and cited in many literatures as described in [4]. There are many tuning method proposed in the literatures.…”

Section: Introductionmentioning

confidence: 99%

Single and Multiple variables control using Tree Physiology Optimization

Halim

Ismail

2017

MATEC Web Conf.

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Abstract. This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. The clustered diversification is referred as tree branch and leaves. The exploration is amplified from roots growth counterparts. In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). Results shown that TPO is able to find good PID parameters with lesser settling time for SISO and MIMO process. NMS is also able to find good PID parameters for SISO with lesser performance index, however not able to find better solution in MIMO control. PSO converged prematurely in SISO control and has high overshoot for MIMO control optimization.

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Section: Introductionmentioning

confidence: 99%