GPC strategies for the lateral control of a networked AGV

Romero, Miguel; Tejado, Inés; Suárez, José I.; Vinagre, Blas M.; Madrid, A.P. de

doi:10.1109/icmech.2009.4957115

Cited by 9 publications

(6 citation statements)

References 20 publications

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“…The goal is to highlight the beneficial characteristics of FGPC to compensate unmodeled dynamics and external disturbances using the proposed tuning method. These characteristics were shown up in [32], where the lateral control of an autonomous vehicle is carried out by FGPC in the presence of sensor noise and the effect of the communication network.…”

Section: Introductionmentioning

confidence: 96%

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Fractional-Order Generalized Predictive Control: Application for Low-Speed Control of Gasoline-Propelled Cars

Romero

Madrid

Mañoso

et al. 2013

Mathematical Problems in Engineering

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There is an increasing interest in using fractional calculus applied to control theory generalizingclassicalcontrol strategies as the PID controller and developing new ones with the intention of taking advantage of characteristics supplied by this mathematical tool for the controller definition. In this work, the fractional generalization of the successful and spread control strategy known as model predictive control is applied to drive autonomously a gasoline-propelled vehicle at low speeds. The vehicle is a Citroën C3 Pluriel that was modified to act over the throttle and brake pedals. Its highly nonlinear dynamics are an excellent test bed for applying beneficial characteristics of fractional predictive formulation to compensate unmodeled dynamics and external disturbances.

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Section: Introductionmentioning

confidence: 96%

“…Generalized predictive control (GPC) [29,30] is one of the most representative MPC formulations. Its fractionalorder counterpart, FGPC, uses a real-order fractional cost function to combine the characteristics of fractional calculus and predictive control into a versatile control strategy [31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Generalized Predictive Control: Application for Low-Speed Control of Gasoline-Propelled Cars

Romero

Madrid

Mañoso

et al. 2013

Mathematical Problems in Engineering

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“…A finite-dimensional approximation was introduced to arrive at a linear time-invariant system and cast the discrepancy between the real and the approximate system as an additive bounded uncertainty term. A worst-case MPC formulation was presented which leads to asymptotically stable behavior towards the origin in presence of state and input constraints, even when an approximate finite-history model is employed, unlike alternative approaches [27,24].…”

Section: Introductionmentioning

confidence: 99%

Model predictive control for offset-free reference tracking of fractional order systems

Ntouskas

Sarimveis

Sopasakis

2018

Control Engineering Practice

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In this paper an offset-free model predictive control scheme is presented for fractionalorder systems using the Grünwald-Letnikov derivative. The infinite-history fractionalorder system is approximated by a finite-dimensional state-space system and the modeling error is cast as a bounded disturbance term. Using a state observer, it is shown that the unknown disturbance at steady state can be reconstructed and modeling errors and other persistent disturbances can be attenuated. The effectiveness of the proposed controller-observer ensemble is demonstrated in the optimal administration of an anti-arrhythmic medicine with fractional-order pharmacokinetics.

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“…FGPC has also proved to be a versatile, valuable and alternative control strategy. So far, its practical applications include the control of a servomotor plant (Romero, et al, 2008b(Romero, et al, , 2010b, an autonomous Guided Vehicle (AGV) (Romero, et al, 2009), and a Smart Wheel in a Network environment (Tejado, et al, 2009).…”

Section: Introductionmentioning

confidence: 99%