Extended Rauch-Tung-Striebel controller

Zima, Miroslav; Armesto, Leopoldo; Girbés, Vicent; Sala, Antonio; Šmı́dl, Václav

doi:10.1109/cdc.2013.6760324

Cited by 6 publications

(13 citation statements)

References 17 publications

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“…Under these assumptions, it can be proved that the optimal control problem (3) is dual to the problem of marginal prediction of the state [8], [12]; with general solution of the Bellman function…”

Section: A Duality Of Estimation and Controlmentioning

confidence: 99%

“…A preliminary conference version of this work appears in [12]. In the present paper, more detailed account of the root ideas is provided, and a deeper analysis and discussion with alternative options in literature is carried out.…”

Section: Problem Statementmentioning

confidence: 99%

“…Based on these ideas, this paper proposes the use of noniterative controllers based on the duality between optimal control and estimation under certain assumptions [8] for nonlinear systems, extending our preliminary conference version [12]. In this sense, this work proposes an Extended Rauch-TungStriebel (ERTS) controller for nonlinear systems, which is derived from the duality between optimal control and estimation as an extension of Todorov's work.…”

Section: Introductionmentioning

confidence: 99%

“…

…”

mentioning

confidence: 99%

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Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following

Armesto

Girbés

Sala

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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Leopoldo Armesto; Girbés, V.; Sala, A.; Miroslav Zima; Václav mídl (2015). Duality Abstract-This paper presents non-iterative linearization-based controllers for nonlinear unconstrained systems, coined as Extended Rauch-Tung-Striebel (ERTS) and Unscented RauchTung-Striebel (URTS) controllers, derived from the duality between optimal control and estimation. The proposed controllers use a Rauch-Tung-Striebel forward-backward smoother as an state estimator in order to compute the original optimal control problem. The new controllers are applied to trajectory-following problems of differential-drive mobile robots and compared with iterative iLQR controller, nonlinear model predictive control and approximate inference approaches. Simulations show that ERTS and URTS controllers produce almost-optimal solutions with a significantly lower computing time, avoiding initialization issues in the other algorithms (in fact, they can be used to initialize them). The paper validates ERTS controller with an experiment of a Pioneer 3DX mobile robot. I. INTRODUCTIONOptimal control is widely used in control practice due to its advantages regarding the individual tuning of actuator amplitudes and control goals for each output, with wellknown solutions for the linear case, both unconstrained (LQR) and constrained [1], [2]. However, it is limited to a narrow spectrum of applications because many systems in practice are inherently nonlinear. Nonlinear optimal control strategies are computationally more demanding, see [3]-[5] for some modelbased approaches to handling it.The goal of model-based optimal control is designing a stabilizing control while minimizing a given performance criterion, usually in a quadratic form, assuming a deterministic plant model is available. Closed-loop solutions can not be found analytically in a general nonlinear case since it involves obtaining the solution of the corresponding Hamilton JacobiBellman equations [6]. One approach to avoid this problem is the iterative solution of a finite-horizon optimal control problem for a given state with a receding horizon implementation; control approaches using this strategy are referred to as model predictive control (MPC,[1]) and nonlinear model predictive control (NMPC,[5]). These approaches can deal with the unconstrained and constrained problems, where both states and control inputs must satisfy particular conditions. MPC is restricted to quadratic cost functions, linear systems and linear constraints, while NMPC can optimize non-quadratic

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Section: A Duality Of Estimation and Controlmentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…

…”

mentioning

confidence: 99%

See 2 more Smart Citations

Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following

Armesto

Girbés

Sala

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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“…[Zima et al (2013), Armesto et al (2014)] demonstrates and solves the implementation for such an estimation problem, which is composed of an estimation/filtering structure, following the result in [Rauch et al (1965)]. Thus, the authors derive an optimal controller with the appropriate adjustment of the Kalman matrices.…”

Section: Image Based Visual Servoing With Reference Filteringmentioning

confidence: 99%

On improving robot image-based visual servoing based on dual-rate reference filtering control strategy

Solanes¹,

Muñoz-Benavent²,

Girbés³

et al. 2015

Robotica

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Cambridge University PressSolanes Galbis, JE.; Muñoz Benavent, P.; Girbés, V.; Armesto Ángel, L.; Tornero Montserrat, J. (2015). On improving robot image-based visual servoing based on dual-rate reference filtering control strategy. Robotica. May 13, 2015Abstract It is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a 6DOF industrial manipulator, a smart camera, and embedded hardware used as a high level controller.

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Generalization of reference filtering control strategy for 2D/3D visual feedback control of industrial robot manipulators

Solanes

Muñoz-Benavent

Armesto

et al. 2021

International Journal of Computer Integrated Manufacturing

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This paper develops the application of the Dual Rate Dual Sampling Reference Filtering Control Strategy to 2D and 3D visual feedback control. This strategy allows to overcome the problem of sensor latency and to address the problem of control task failure due to visual features leaving the camera field of view. In particular, a Dual Rate Kalman Filter is used to generate inter-sample estimations of the visual features to deal with the problem of vision sensor latency, whereas a Dual Rate Extended Kalman Filter Smoother is used to generate more convenient visual features trajectories in the image plane. Both 2D and 3D visual feedback control approaches are widely analyzed throughout the paper, as well as the overall system performance using different visual feedback controllers, providing a set of results that highlight the improvements in terms of solution reachability, robustness, and time domain response. The proposed control strategy has been validated on an industrial system with hard real-time limitations, consisting of a 6 DOF industrial manipulator, a 5 MP camera, and a PLC as controller.

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Extended Rauch-Tung-Striebel controller

Cited by 6 publications

References 17 publications

Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following

Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following

On improving robot image-based visual servoing based on dual-rate reference filtering control strategy

Generalization of reference filtering control strategy for 2D/3D visual feedback control of industrial robot manipulators

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