H/sup ∞/-optimal tracking control techniques for nonlinear underactuated systems

Toussaint, Gregory J.; Başar, Tamer; Bullo, Francesco

doi:10.1109/cdc.2000.914100

Cited by 115 publications

(77 citation statements)

References 2 publications

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“…The stability properties of the propulsion system are proven through Lyapunov analysis. First, it is shown that H-infinity tracking performance criterion is satisfied, which signifies elevated robustness against model uncertainty and external disturbances [18]. Next, conditions for the global asymptotic stability of the control scheme are provided.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain

et al. 2018

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Abstract.A nonlinear optimal (H-infinity) control method is proposed for an electric ship's propulsion system that consists of an induction motor, a drivetrain and a propeller. The control method relies on approximate linearization of the propulsion system's dynamic model using Taylor-series expansion and on the computation of the state-space description's Jacobian matrices. The linearization takes place around a temporary equilibrium which is recomputed at each time-step of the control method. For the approximately linearized model of the ship's propulsion system, an H-infinity (optimal) feedback controller is developed. For the computation of the controller's gains an algebraic Riccati equation is solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis,

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Section: Introductionmentioning

confidence: 99%

Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain

et al. 2018

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“…Most controllers for this underactuated problem ( [4], [6], [16]) are derived using a B matrix of the form…”

Section: Marine Vehicle Kinematicsmentioning

confidence: 99%

“…However, the desired trajectory is limited to straight lines and circles. In [4], still considering the same type of underactuation as in [3], the authors derive a controller that uses a state estimator to handle uncertainties on state measurement.…”

Section: Introductionmentioning

confidence: 99%

Adaptive nonlinear tracking control of an underactuated nonminimum phase model of a marine vehicle using ultimate boundedness

Morel

Leonessa

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475)

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Abstract-In this paper, an adaptive nonlinear tracking controller for an underactuated nonminimum phase model of a marine vehicle is derived. The result is kept flexible enough, throughout its derivation, to be applicable to a large variety of marine vehicles. The characteristics of the dynamic model are such that solving the tracking problem is non-trivial. Specifically, we consider a propulsion system composed of either a thruster and a rudder, or a vectored thruster, which provides two independent control commands and three degrees of freedom, with an overall unstable zero-dynamics. The tracking problem dealt with in this paper is solved using a backstepping approach, as well as a technique derived from dynamic surface control theory and the notion of ultimate boundedness. The tracking problem is first solved assuming full knowledge of the geometric and hydrodynamic coefficients appearing in the vehicle's model. The control law is then modified into an adaptive one. Computer simulations are presented to illustrate the performances of the final control algorithm.

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“…However, the desired trajectory is limited to straight lines and circles. The same type of underactuation is considered in [17], where the authors derive a controller that uses a state estimator to handle state measurement uncertainties.…”

mentioning

confidence: 99%

“…Many tracking controllers are available in the literature (see, for example, [2,3,4,7,9,17,18]). In [18], the case of a surface ship equipped with a pair of propellers is considered.…”

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confidence: 99%

Neural Network Model Reference Adaptive Control of Marine Vehicles

Leonessa

VanZwieten

Morel

Systems and Control: Foundations &Amp; Applications

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Summary.A neural network model reference adaptive controller for trajectory tracking of nonlinear systems is developed. The proposed control algorithm uses a single layer neural network that bypasses the need for information about the system's dynamic structure and characteristics and provides portability. Numerical simulations are performed using nonlinear dynamic models of marine vehicles. Results are presented for two separate vehicle models, an autonomous surface vehicle and an autonomous underwater vehicle, to demonstrate the controller performance in terms of tuning, robustness, and tracking.

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H/sup ∞/-optimal tracking control techniques for nonlinear underactuated systems

Cited by 115 publications

References 2 publications

Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain

Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain

Adaptive nonlinear tracking control of an underactuated nonminimum phase model of a marine vehicle using ultimate boundedness

Neural Network Model Reference Adaptive Control of Marine Vehicles

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