Multivariable controller tuning for non square systems by genetic algorithm

The inverted decoupling-based controllers for a time delay multivariable non-square systems is a challenging task. In this case study, a controller is designed on the basis of the inverted decoupling structure for a highly interactive lab scale batch distillation process. The centralized inverted decoupling controller is divided into two sub sections, one on the forward path and the other in the feedback path. The main objective is to achieve a decoupled dynamic behavior characteristic of each loop. The square distillation column model in literature generally uses the heater current and reflux as the two manipulated variables, in the modified lab scale distillation column, the authors have considered the third manipulated variable for the restriction of coolant flow rate to the condenser. The mathematical model used in the simulation study is process with three inputs and two outputs is considered for parameter estimation and simulation studies followed by the validation of control algorithms on a lab scale distillation unit to show the effectiveness of the proposed control algorithm.

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“…The centralized controller elements𝐺 𝑠 , 𝐺 𝑠 are determined as follows. Let consider 𝐺 𝑠 be an (m*n) matrix and 𝐺 𝑠 be an (n*m) matrix [4].…”

Section: Controller Methodologymentioning

confidence: 99%

Simulation studies of inverted decoupling control algorithm on a non-square pilot plant distillation column

Janani¹,

Yadav²,

Thirunavukkarasu³

2022

Robotics, Automation and Non-Destructive Evaluation

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“…A system is called non -minimum phase system when it has one or more right half plane (RHP) transmission zeros. These RHP zeros impose limitations on stability and controllability of the system (1,2) . Design of controller for the system with positive https://www.indjst.org/ zeros is a major task because it will affect both the amplitude and phase angle.…”

Section: Introductionmentioning

confidence: 99%

Design of centralized controller for multivariable process using MOPSO algorithm

Sivagurunathan¹

2021

IJST

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Objective: To estimate centralized PID controller parameters for 4 outputs and 5 inputs crude distillation non-square system with RHP zeros process. Methods/Analysis: The Multi-Objective Particle Swam Optimization (MOPSO) algorithm is applied to determine the PID controller parameters for the considered distillation column process. Findings: The performance of the proposed controller is compared with two centralized controller schemes, Davison's and Tanttu and Lieslehto methods. The Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral of Time Absolute Error (ITAE) are chosen as performance indices. The simulation results prove that MOPSO tuned centralized controller gives the best performance when compared to other analytical techniques for both set point tracking and in disturbance rejection environment. Novelty: In practice, conventional PID controllers are tuned using classical methods, which require complex numerical calculations. In this paper, an attempt is made to fine tune the PID controller for a MIMO process using Multi Objective optimization technique and obtained challenging results as compared to conventional methods.

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“…Methods based in the step response, the frequency response and other uses the closed loop steady state response for multivariable systems [2]. In the last years, multivariable controllers has been tuned by using heuristic optimization methods such as genetic algorithms and swarm particles, as described in [3], [4] and [5].…”

Section: Introductionmentioning

confidence: 99%

Multivariable controller tuning using genetic algorithms for an induction motor

Albarracin-Avila

Giraldo

2014

2014 IEEE 5th Colombian Workshop on Circuits and Systems (CWCAS)

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A methodology for tuning multivariable controllers in state space by using genetic algorithms is proposed. The multivariable controller is designed in discrete time by using an extended state space feedback with integral action. The feedback gain is computed by using a linear quadratic regulator. Optimal constraints are tuned by genetic algorithms according to a cost function. As a result a robust multivariable controller is obtained by using state space feedback. This tuning procedure avoids the knowledge of the exact parameters of the system, and has the advantage that reduces the tracking error and decrease the rise time based on a performance index. Proposed methodology is applied over an induction motor in discrete time. The performance of the proposed methodology is compared against fixed controllers calculated by linear quadratic methods.

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Multivariable controller tuning for non square systems by genetic algorithm

Cited by 5 publications

References 6 publications

Simulation studies of inverted decoupling control algorithm on a non-square pilot plant distillation column

Simulation studies of inverted decoupling control algorithm on a non-square pilot plant distillation column

Design of centralized controller for multivariable process using MOPSO algorithm

Multivariable controller tuning using genetic algorithms for an induction motor

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