Position‐heading quadrotor control using LPV techniques

Trapiello, Carlos; Puig, Vicenç; Morcego, Bernardo

doi:10.1049/iet-cta.2018.6147

Cited by 27 publications

(16 citation statements)

References 35 publications

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“…During the last decades, linear parameter varying (LPV) techniques have received a great deal of attention due to their practical applications in a wide range of areas, such as air–fuel ratio in vehicle engines [1], water tank system [2], quadrotor [3], vehicle motion [4, 5], and process system [6]. In most of the works published in the literature, it is supposed that scheduling parameters are exactly known in real‐time.…”

Section: Introductionmentioning

confidence: 99%

Inexact induced L2 observer‐based control of polytopic LPV systems: application to clutchless automated manual transmission of pure electric vehicles

Abbasghorbani

Asemani

Vafamand

et al. 2020

IET Control Theory & Appl

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A novel method for observer‐based control of disturbed polytopic linear parameter varying (LPV) systems with inexactly measured scheduling parameters is investigated in this study. Despite the imperfect scheduling parameters knowledge, the proposed control method ensures the closed‐loop induced L2‐norm performance criterion. Unlike the previous methods, the inexact scheduling parameters are not assumed to be proportional to the original scheduling parameters of the LPV system. Employing both cases of parameter‐dependent and parameter‐independent Lyapunov functions, sufficient design conditions in terms of linear matrix inequalities are provided using Finsler's lemma. Numerical examples are included to demonstrate the efficiency of the proposed method and its superiority over the previous techniques. Moreover, a practical case study, i.e. clutchless automated manual transmission system is considered and controlled by the developed approach numerically.

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Section: Introductionmentioning

confidence: 99%

Inexact induced L2 observer‐based control of polytopic LPV systems: application to clutchless automated manual transmission of pure electric vehicles

Abbasghorbani

Asemani

Vafamand

et al. 2020

IET Control Theory & Appl

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“…In [36], the quadrotor model is not only divided into fully actuated and underactuated subsystems, but also included the propeller subsystem to tackle the actuator faults. In [37], a linear parameter varying controller and feedback linearization controller were designed for the attitude and the position of a quadrotor respectively. In [38], an active disturbance rejection control (ADRC) and backstepping SMC have been constructed for the quadrotor attitude and the position respectively.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed control strategy is divided into into three subcontrollers: ADIFTSMC for altitude control, RBFNNBC for horizontal position control, and FDOBNFTSMC for rotational angle control. The main contributions of the proposed method are presented as follows 1) Contrary to [37]- [43], [45] where the quadrotor control design is divided into two subcontrollers, we divided the proposed control scheme into three subcontrollers: the altitude, the horizontal position and the attitude controllers. 2) Unlike the adaptive NFTSMC [33], ADRC [38], backstepping FTSMC [40], RISE [44], backstepping SMC [45] implemented for the attitude control, in this paper, a backstepping is combined with NFTSMC and FDO (FDONFTSMC) to control the attitude angles.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Multilevel Control of a Quadrotor

Mahmoud

Maaruf

2020

IEEE Access

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This study proposes a new multilevel control of a quadrotor with dynamic uncertainties and time-varying external disturbances. The quadrotor model is partitioned into three subsystems: the vertical position, the horizontal position and the rotational subsystems. First, a double loop integral fast terminal sliding mode control with an adaptive estimator for disturbances' upper-bounds (ADIFTSMC) is proposed for the altitude subsystem to ensure that the quadrotor reaches the desired height. Secondly, a radial basis function neural network backstepping controller (RBFNNBC) is applied to the horizontal subsystem. Finally, by combining a finite time exact disturbance observer with backstepping nonsingular fast terminal sliding mode control (FDOBNFTSMC), the rotational angles converge to the reference angles in the presence of the time-varying disturbances. Furthermore, a Lyapunov stability analysis is used to prove that the tracking errors converge to a small neighborhood of the origin. Numerical simulations illustrate the feasibility of the compound control structure.

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“…Atualmente, apenas alguns trabalhos discutem a formulação LMI do controlador LQR com ganho escalonado, os quais se dividem na escolha da classe da função de Lyapunov no cálculo da matriz de realimentação de estados, i.e. : (a) função de Lyapu-nov quadrática comum (do inglês, Common Quadratic Lyapunov Function -CQLF) (Alcala et al (2017(Alcala et al ( , 2018(Alcala et al ( , 2019; Trapiello et al (2019)) e (b) função de Lyapunov dependente de parâmetros (Parameter-Dependent Lyapunov Function -PDLF) (Aktas et al (2016); Liu et al (2017)). É importante ressaltar que na proposição (b) o ganho de realimentação de estados depende da inversão da matriz de Lyapunov queé literal.…”

Section: Introductionunclassified

Controladores LQR-gain scheduling para sistemas LPV com incertezas politópicas

Caun

Assunção

Teixeira

2020

Anais Do Congresso Brasileiro De Automática 2020

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Neste trabalho é investigado a ação de incertezas paramétricas variantes no tempo em todas as matrizes de um sistema linear contı́nuo no tempo e, portanto, um ganho de realimentação de estados linear variante com parâmetros (LPV) e quadraticamente estabilizante é proposto. O método é baseado no regulador linear quadrático (LQR) e pode ser visto como uma alternativa de projeto mais simples que outras abordagens convencionais da literatura via funções de Lyapunov dependentes de parâmetros (PDLF), pois a matriz de ganhos não depende da inversão de uma matriz literal. O algoritmo é baseado em formulações LMIs relaxadas do problema LPV baseado no LQR, afim de reduzir o conservadorismo da função de Lyapunov quadrática comum (CQLF). Finalmente, análises práticas em uma suspensão ativa ilustram a eficiência das propostas na presença de falhas variantes no tempo em atuadores.

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Position‐heading quadrotor control using LPV techniques

Cited by 27 publications

References 35 publications

Inexact induced L2 observer‐based control of polytopic LPV systems: application to clutchless automated manual transmission of pure electric vehicles

Inexact induced L2 observer‐based control of polytopic LPV systems: application to clutchless automated manual transmission of pure electric vehicles

Robust Adaptive Multilevel Control of a Quadrotor

Controladores LQR-gain scheduling para sistemas LPV com incertezas politópicas

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