Trajectory-tracking dynamic control of an omnidirectional mobile robot

Velasco-Villa, M.; Rodriguez-Cortes, H.; Estrada-Sanchez, I.; Sira‐Ramírez, Hebertt

doi:10.1109/iecon.2009.5415432

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…A dynamic model of the omnidirectional mobile robot has been derived in Velasco-Villa et al [15] using the EulerLagrange methodology for non-holonomically restricted systems. The dynamic model is of the following form:…”

Section: A Dynamic Modelmentioning

confidence: 99%

Real-time linear control of the omnidirectional mobile robot

Sira‐Ramírez

Lopez-Uribe

Velasco-Villa

2010

49th IEEE Conference on Decision and Control (CDC)

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This article describes the design of a linear observer-linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in an omnidirectional mobile robot. The unknown, possibly state-dependent, additive nonlinearity influencing the input-output tracking error dynamics, is modeled as an absolutely bounded, additive, unknown "time-varying disturbance" input signal. This procedure simplifies the system tracking error description to that of three independent chains of second order integrators with, known, position-dependent control gains, while additively being perturbed by the unknown, smooth, time-varying signal which is proven to be trivially observable. The total state-dependent uncertain input is assumed to be locally approximated by an arbitrary element of, a, fixed, sufficiently high degree family of Taylor polynomials for which a linear observer with a corresponding self-updating internal model may be readily designed. Generalized Proportional Integral (GPI) observers, which are the dual counterpart of GPI controllers (see [1]), are shown to naturally estimate, in a arbitrarily close manner, the unknown perturbation input of the simplified system and a certain number of its time derivatives, thanks to its embedded, internal time-polynomial model of the unknown, state-dependent, perturbation input. This information is used to advantage on the linear, observer-based, feedback controller design via a simple cancelation effort. The results are implemented on a laboratory prototype in a trajectory tracking problem.

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Section: A Dynamic Modelmentioning

confidence: 99%

Real-time linear control of the omnidirectional mobile robot

Sira‐Ramírez

Lopez-Uribe

Velasco-Villa

2010

49th IEEE Conference on Decision and Control (CDC)

Self Cite

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“…A dynamic model of the omnidirectional mobile robot has been derived in using the Euler‐Lagrange methodology for non‐holonomic systems. The dynamic model is of the following form:

M \ddot{q} + C (\dot{q}) \dot{q} = B (q) τ,

where, q = [ x y ϕ ] T .…”

Section: The Omnidirectional Mobile Robot Examplementioning

confidence: 99%

Linear Observer‐Based Active Disturbance Rejection Control of the Omnidirectional Mobile Robot

Sira‐Ramírez

Lopez-Uribe

Velasco-Villa

2012

Asian Journal of Control

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This article describes the design of a linear observer‐linear controller‐based robust output feedback scheme for output reference trajectory tracking tasks in an omnidirectional mobile robot. The unknown, possibly state‐dependent, additive nonlinearities influencing the input‐output tracking error dynamics are modeled as an absolutely bounded, additive, unknown “time‐varying disturbance” input signal. This procedure simplifies the system tracking error description to that of three independent chains of second order integrators with, known, position‐dependent control gains. These simplified systems are additively perturbed by the unknown, smooth, time‐varying signal which is proven to be trivially observable. Generalized proportional integral (GPI) observers, are shown to naturally estimate, in an arbitrarily close manner, the unknown perturbation input of the simplified system and a certain number of its time derivatives. This information is used to advantage on the linear, observer‐based, feedback controller design via a simple cancellation effort. The results are implemented on a laboratory prototype of an omnidirectional mobile robot.

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