H&lt;inf&gt;2&lt;/inf&gt; gain scheduling control for rational LPV systems using the descriptor framework

Bouali, A.; Yagoubi, Mohamed; Chevrel, P.

doi:10.1109/cdc.2008.4738689

Cited by 10 publications

(13 citation statements)

References 14 publications

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“…Although these results are good, they give no stability guarantee when the speed V varies with time. For this reason, we complete the analysis by using the results in [31]. Based on the transformation of any rational LPV state-space realization to an affine descriptor one to simplify the parametric dependency, the proposed algorithm enables the evaluation of a guaranteed H 2 norm bound, using LMI formulation and semi-definite programming.…”

Section: B a Posteriori Robustness Analysismentioning

confidence: 99%

Direct and Steering Tilt Robust Control of Narrow Vehicles

Mourad¹,

Claveau

Chevrel

2014

IEEE Trans. Intell. Transport. Syst.

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International audienceNarrow Tilting Vehicles (NTVs) are the convergence of a car and a motorcycle. They are expected to be the new generation of city cars considering their practical dimensions and lower energy consumption. However, due to their height to breadth ratio, in order to maintain lateral stability, NTVs should tilt when cornering. Unlike the motorcycle, where the driver tilts the vehicle himself, the tilting of an NTV should be automatic. Two tilting systems are available; Direct and Steering Tilt Control, the combined action of these two systems being certainly the key to improve considerably NTV dynamic performances. In this paper, multivariable control tools (H2 methodology) are used to design, in a systematic way, lateral assistance controllers driving DTC, STC or both DTC/STC systems. A three degrees of freedom model of the vehicle is used, as well as a model of the steering signal, leading to a two degrees of freedom low order controller with an efficient feedforward anticipative part. Taking advantage of all the available measurements on NTVs, the lateral acceleration is directly regulated. Finally, a gain-scheduling solution is provided to make the DTC, STC, and DTC/STC controllers robust to longitudinal speed variations

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Section: B a Posteriori Robustness Analysismentioning

confidence: 99%

Direct and Steering Tilt Robust Control of Narrow Vehicles

Mourad¹,

Claveau

Chevrel

2014

IEEE Trans. Intell. Transport. Syst.

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“…The controller is applied to two-link robotic manipulator. Natural two-link robotic manipulator model has not any singular matrices, but it and similar mechanical systems can be converted to singular form by LPV conversion methods as in [22,36,37], which is not in the focus of paper. Because of avoiding the complexity of rational LPV systems, the proposed controller can be applied to a robotic manipulator system or any non-singular LPV descriptor system without using rational LPV form.…”

Section: © Ijoctamentioning

confidence: 99%

“…Thus, we get the following inequality by also defining Remark: The inverse of   E  is a drastic case due to rational LPV form and there is no a formula for this, so an extra complexity occurs, and some assumptions or extra methods are needed as in [22,28,36,37]. For example, since…”

Section: T Qx T U T R U T Dt X T Px Tmentioning

confidence: 99%

“…Therefore, these systems have attracted attention for the past decade because many systems such as mechanical systems have this structure, and the systems have ability to describe many systems such as chemical processes, robotic systems, aircrafts, etc. Thus, many researchers have investigated in the literature, for instance, robust stability analysis and stabilisation [15][16][17], robust controllability/ observability analysis [18], H2/H∞ norm characterization and control [19][20][21][22][23][24][25][26][27], robust filtering [21], positive real analysis and control [22]. They have two types which are singular and nonsingular descriptor systems.…”

Section: Introductionmentioning

confidence: 99%

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Gain scheduling LQI controller design for LPV descriptor systems and motion control of two-link flexible joint robot manipulator

Altun

2018

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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This paper proposes a gain scheduling linear quadratic integral (LQI) servo controller design, which is derived from linear quadratic regulator (LQR) optimal control, for non-singular linear parameter varying (LPV) descriptor systems. It is assumed that state space matrices are non-singular since many mechanical systems do not have any non-singular matrices such as the natural state space forms of robotic manipulator, pendulum and suspension systems. A controller design is difficult for the systems due to rational LPV case. Therefore, the proposed gain scheduling controller is designed without the difficulty. Accordingly, the motion control design is implemented for two-link flexible joint robotic manipulator. Finally, the control system simulation is performed to prove the applicability and performance.

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“…In addition, the advantage of reducing the complexity of the parameter dependance makes the descriptor model a good mean for deriving efficient analysis and synthesis methods for LPV control (see for instance [4]) and in identification (see [5]). …”

Section: Introductionmentioning

confidence: 99%

Towards DAE methodology for the control of cable-driven parallel robots

Cvetanovic

Laroche

2014

2014 IEEE Conference on Control Applications (CCA)

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Models obtained from the laws of Physics are naturally written as differential-algebraic equations (DAE) also known as descriptor models. However, the usual methodology in control consists in reducing the model to a set of ordinary equations. Remaining in the DAE word has several advantages: the reduction step is not necessary any more and the parameter dependance might be simplified. This paper is a step forward towards a control methodology that would be entirely based on DAE models. Its goal is twofold. First, the tools and methods available for DAE models are reviewed. Second, a case taken form robotics is considered. The simulation being done with Maple, a linear model is derived and transferred to Matlab for synthesis. A H∞ controller is then synthesized and evaluated. The controlled system is then simulated with Maple.

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H<inf>2</inf> gain scheduling control for rational LPV systems using the descriptor framework

Cited by 10 publications

References 14 publications

Direct and Steering Tilt Robust Control of Narrow Vehicles

Direct and Steering Tilt Robust Control of Narrow Vehicles

Gain scheduling LQI controller design for LPV descriptor systems and motion control of two-link flexible joint robot manipulator

Towards DAE methodology for the control of cable-driven parallel robots

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