A hybrid state feedback controller design for two different dynamic systems

Aravind, P.; Veeramani, V.; Girirajkumar, S.M.

doi:10.1504/ijor.2021.117075

Cited by 2 publications

(1 citation statement)

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“…Sowmya et al proposed Genetic Algorithm Tuned Fuzzy Controller for a Nonlinear Process and this control algorithm different from numerical algorithms [33][34][35]. A Hybrid controller design was proposed [36] with State Feedback Controller Design for Two various Dynamic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Error Recursion Reduction Computational Technique Based Control System Design for a Multivariable Process

Venkataraman¹,

Veerapathran²,

Girirajkumar³

2020

I2M

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The optimization problem for multi-variable industrial high-efficiency control systems is to find the optimal parameters that could minimize the errors. In order to get such a stable control system, various control tuning methods were proposed by many researchers, but still, it is a challenge to get an effective controlled system. In this work, a method is proposed in order to attain a stable control system, called Error Recursion -Reduction Computational (ERRC) technique. Two processes, level, and flow are considered; their respective process models are identified and validated. The performance of the proposed technique has verified by implementing real-time transducers' interfaced experimental process. Results are compared with the conventional PID tuning technique and by optimization algorithms. The proposed experimental results show that better closed-loop performance can be achieved than other tuning techniques.

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