Laguerre-based modelling and predictive control of multi-input multi-output systems applied to a communicating two-tank system (CTTS)

Mbarek, Abdelkader; Bouzrara, Kais; Garna, Tarek; Ragot, José; Messaoud, Hassani

doi:10.1177/0142331215613150

Cited by 15 publications

(11 citation statements)

References 31 publications

(41 reference statements)

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“…The ARX-Laguerre method for fault identification and system estimation is introduced in [10,11]. Here, the ARX-Laguerre method has been used for robot manipulator estimation [10] and bearing estimation [11]. However, these methods decrease the system performance in highly nonlinear systems.…”

Section: Related Workmentioning

confidence: 99%

“…In an attempt to solve this issue, the Laguerre filter has been used to reduce the effect of noise on the input and output [9]. As a result, the ARX-Laguerre method has been used for system identification in various applications including robot arms [10] and rolling bearing elements [11]. The primary drawback of this technique is system estimation in highly nonlinear and uncertain systems.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

Piltan¹,

TayebiHaghighi²,

Jowkar³

et al. 2019

IJISA

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In practical applications, modeling of real systems with unknown parameters such as distillation columns are typically complex. To address issues with distillation column estimation, the system is identified by a proposed intelligent, auto-regressive, exogenous-Laguerre (AI-ARX-Laguerre) technique. In this method, an intelligent technique is introduced for data-driven identification of the distillation column. The Laguerre method is used for the removal of input/output noise and decreases the system complexity. The fuzzy logic method is proposed to reduce the system's estimation error and to accurately optimize the ARX-Laguerre parameters. The proposed method outperforms the ARX and ARX-Laguerre technique by achieving average estimation accuracy improvements of 16% and 9%, respectively.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

Piltan¹,

TayebiHaghighi²,

Jowkar³

et al. 2019

IJISA

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“…By analogy to the development given by Mbarek et al [22] for the MIMO case and from relation (A.3) and (A.4) given in Appendix A, the MISO ARX-Laguerre multiple model can be described by the following recursive representation:…”

Section: Expansion Of Mimo Arx Multiple Models On Laguerre Orthonormamentioning

confidence: 99%

Fault Tolerant Control for MIMO Nonlinear Systems via MPC Based on MIMO ARX‐Laguerre Multiple Models

Mbarek

Bouzrara

2019

Mathematical Problems in Engineering

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In this article, we propose a fault tolerant control for multiple-input multiple-output (MIMO) nonlinear systems via model predictive control. The MIMO nonlinear systems are approximated by MIMO ARX-Laguerre multiple models. The latter is obtained by expanding a discrete-time MIMO ARX multiple model parameters on Laguerre orthonormal bases. The resulting model ensures an efficient complexity reduction with respect to the classical MIMO ARX multiple models. This parametric complexity reduction still subjects to an optimal choice of the Laguerre poles defining Laguerre bases. The parameter and structure identifications of the MIMO ARX-Laguerre multiple models are achieved by the recursive method and a metaheuristic algorithm, respectively. The proposed model is built from the system input/output observations and is used to synthesize a MIMO nonlinear fault tolerant control algorithm via MPC. So, we develop a fault detection and isolation (FDI) scheme based on the proposed model. The scheme of the fault detection is applied at every step of MPC control calculation, where we determine the actuator faults and we use it in the MPC optimization problem to determine the new control with respect to the actuator faults. The proposed strategy is tested on numerical simulation and validated on the real system.

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“…• n 1 = 0, n 2 = 0: From s n 1 n 2 uu (k) given in relation (17) we can write s 00 uu (k + 1) as (see (41)) From relations (15) and 25, we can write s 00 uu (k + 1) given by relation (41) as (see (42)) In relation (42), we replace ℓ 0 uu (i + 1, ξ uu ) and ℓ 0 uu ( j + 1, ξ uu ) by their expressions are given by (26) and for t = uu, we can write s 00 uu (k + 1) as…”

Section: Expansion Of the Narx Model Parameters On Laguerre Basesmentioning

confidence: 99%

“…This idea is based on the development of the ARX model (AutoRegressive model structure with an eXternal input) on two independent Laguerre orthonormal bases. This idea has proved its effectiveness in reducing the parametric complexity of linear systems [23], a class of non-linear system by expanding the bilinear model on Laguerre bases [24,25] and multiple-input multiple-output (MIMO) systems by expanding the ARX-MIMO model on Laguerre bases [26,27].…”

Section: Introductionmentioning

confidence: 99%

Non‐linear system modelling based on NARX model expansion on Laguerre orthonormal bases

Benabdelwahed

Mbarek

Bouzrara

et al. 2018

IET signal process.

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This study proposes a new representation of discrete Non-linear AutoRegressive with eXogenous inputs (NARX) model by developing its coefficients associated to the input, the output, the crossed product, the exogenous product and the autoregressive product on five independent Laguerre orthonormal bases. The resulting model, entitled NARX-Laguerre, ensures a significant parameter number reduction with respect to the NARX model. However, this reduction is still subject to an optimal choice of the Laguerre poles defining the five Laguerre bases. Therefore, the authors propose to use the genetic algorithm to optimise the NARX-Laguerre poles, based on the minimisation of the normalised mean square error. The performances of the resulting NARX-Laguerre model and the proposed optimisation algorithm are validated by numerical simulations and tested on the benchmark Continuous Stirred Tank Reactor.

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Laguerre-based modelling and predictive control of multi-input multi-output systems applied to a communicating two-tank system (CTTS)

Cited by 15 publications

References 31 publications

A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

Fault Tolerant Control for MIMO Nonlinear Systems via MPC Based on MIMO ARX‐Laguerre Multiple Models

Non‐linear system modelling based on NARX model expansion on Laguerre orthonormal bases

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