An improved identification and control of 3 × 3 multi-input multi-output system using relay and subspace method

Kishore, D.; Rajan, Sethi Smruti; Kishore, K. Anand; Panda, Rames C.

doi:10.1080/00194506.2018.1486237

“…(30). For comparing the effectiveness of the proposed method, the PI controller parameters are also calculated using SIMC method [4] and Ziegler-Nicholas tuning formulas. The calculated controller setting for these methods are listed in Table 1.…”

Section: Case Study and Resultsmentioning

confidence: 99%

“…These two approaches are completely depends on the model of the processes. The model identification has been proposed by various researchers in different ways [4]. Yu and CC [5] have projected the system modeling by means of relay operating in sequential manner.…”

Section: Introductionmentioning

confidence: 99%

Control System Design for 3x3 Processes Based on Effective Transfer Function and Fractional Order Filter

2019

IJRTE

0

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Designing of PI/PID controller with fractional order set point filter is proposed to achieve the improved performance of 3x3 processes. But the design of controller for such higher dimensional multivariable processes is too difficult task because of interaction involved between the process variables. So interaction must be taken into design consideration. In this method of design determines the interaction between the variables using RGA and RNGA methods and uses it in converting the multivariable processes into multiple single loops. The interaction problems between the loops are overcome by incorporating the decouplers in the control loops. Then, the Effective Transfer Function (ETF) has obtained to design PI/PID controller for each individual element as in single input processes. The fractional order filter is also added to improve the servo response of the processes. Hence, the proposed system improves the overall performance by minimizing the interaction effects due to set point variations. This method is also validate by using a case study.

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“…The process/plant model is given by Eqn. ( For comparing the effectiveness of the proposed method, the PI controller parameters are also calculated using SIMC method [4] and Ziegler-Nicholas tuning formulas. The calculated controller setting for these methods are listed in Table 1.…”

Section: Resultsmentioning

confidence: 99%

Control System Design for 3x3 Processes Based on Effective Transfer Function and Fractional Order Filter

2019

ijeat

1

0

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Designing of PI/PID controller with fractional order set point filter is proposed to achieve the improved performance of 3x3 processes. But the design of controller for such higher dimensional multivariable processes is too difficult task because of interaction involved between the process variables. So interaction must be taken into design consideration. In this method of design determines the interaction between the variables using RGA and RNGA methods and uses it in converting the multivariable processes into multiple single loops. The interaction problems between the loops are overcome by incorporating the decouplers in the control loops. Then, the Effective Transfer Function (ETF) has obtained to design PI/PID controller for each individual element as in single input processes. The fractional order filter is also added to improve the servo response of the processes. Hence, the proposed system improves the overall performance by minimizing the interaction effects due to set point variations. This method is also validate by using a case study.

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“…In (De Simone and Guida, 2018), the N4SID method was used to obtain a dynamical model of the unmanned vehicle, while open-loop and closed-loop control algorithms were implemented on the ArduinoMega controller. In (Kishore et al, 2018), a closed-loop identification method for Multi-Input Multi-Output (MIMO) system has been proposed. The transfer function matrix of the dynamic system is identified in the form of state-space model using N4SID algorithm from the system.…”

Section: Introductionmentioning

confidence: 99%

Robust stabilization for discrete-time Takagi-Sugeno fuzzy system based on N4SID models

Jemmali¹,

Otis²,

Ellouze³

2019

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Nonlinear systems identification from experimental data without any prior knowledge of the system parameters is a challenge in control and process diagnostic. It determines mathematical model parameters that are able to reproduce the dynamic behavior of a system. This paper combines two fundamental research areas: MIMO state space system identification and nonlinear control system. This combination produces a technique that leads to robust stabilization of a nonlinear Takagi-Sugeno fuzzy system (T-S). Design/methodology/approach The first part of this paper describes the identification based on the Numerical algorithm for Subspace State Space System IDentification (N4SID). The second part, from the identified models of first part, explains how we use the interpolation of Linear Time Invariants (LTI) models to build a nonlinear multiple model system, T-S model. For demonstration purposes, conditions on stability and stabilization of discrete time, Takagi-Sugeno (T-S) model were discussed. Findings Stability analysis based on the quadratic Lyapunov function to simplify implementation was explained in this paper. The LMIs (Linear Matrix Inequalities) technique obtained from the linearization of the BMIs (Bilinear Matrix Inequalities) was computed. The suggested N4SID2 algorithm had the smallest error value compared to other algorithms for all estimated system matrices. Originality The stabilization of the closed-loop discrete time T-S system, using the improved PDC control law (Parallel Distributed Compensation), was discussed to reconstruct the state from nonlinear Luenberger observers.

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An improved identification and control of 3 × 3 multi-input multi-output system using relay and subspace method

Cited by 5 publications

References 7 publications

Control System Design for 3x3 Processes Based on Effective Transfer Function and Fractional Order Filter

Control System Design for 3x3 Processes Based on Effective Transfer Function and Fractional Order Filter

Control System Design for 3x3 Processes Based on Effective Transfer Function and Fractional Order Filter

Robust stabilization for discrete-time Takagi-Sugeno fuzzy system based on N4SID models

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