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In this paper we propose a new parameter estimator that ensures global exponential convergence of linear regression models requiring only the necessary assumption of identifiability of the regression equation, which we show is equivalent to interval excitation of the regressor vector. An extension to – separable and monotonic – nonlinear parameterisations is also given. The estimators are shown to be robust to additive measurement noise and – not necessarily slow-parameter variations. Moreover, a version of the estimator that is robust with respect to sinusoidal disturbances with unknown internal model is given. Simulation results that illustrate the performance of the estimator compared with other algorithms are given. [ABSTRACT FROM AUTHOR]

This note presents a continuous adaptive velocity observer for mechanical systems whose dynamic model motion does not allow for the cancellation of gyroscopic forces after coordinates transformation. Its design consists of three components: (i) for a class of systems, we propose a decomposition to render its model in cascade form; (ii) we give necessary and sufficient conditions to include unknown external disturbances and unknown friction parameters in the design, as parameter friction generates complications as it creates products of unknown terms, parameters and states; and (iii) we formulate an adaptive velocity observer based on the Immersion and Invariance (I&I) technique, which ensures velocity estimation while parameter estimators remain bounded. Finally, we analytically study several examples with more than two degrees of freedom and present simulations for a four-degree Scara manipulator. [ABSTRACT FROM AUTHOR]

A gradient descent-based nonlinear observer for surface-mount permanent magnet synchronous motors with remarkable stability properties was recently proposed. A key assumption for the derivation of the observer is the knowledge of the electrical parameters, which are usually uncertain. In the present paper, we propose a robust adaptive flux observer adding immersion and invariance parameter adaptation algorithms to estimate the stator resistance. Global boundedness of all signals and convergence to a residual set of the flux estimation error is guaranteed. The performance of the new adaptive observer is assessed with realistic simulations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A globally exponentially stable speed observer for mechanical systems was recently reported in the literature, under the assumptions of known (or no) Coulomb friction and no disturbances. In this note we propose and adaptive version of this observer, which is robust vis–à–vis constant disturbances. Moreover, we propose a new globally convergent speed observer that, besides rejecting the disturbances, estimates some unknown friction coefficients for a class of mechanical systems that contains several practical examples. [ABSTRACT FROM AUTHOR]

In this brief, we address the robust force regulation problem of mechanical systems in physical interaction with compliant environments. The control method that we present is entirely derived under the energy shaping framework. Note that for compliant interactions, standard energy shaping methods (i.e., potential shaping controls using static-state feedback actions) cannot guarantee asymptotic stability since they are not robust to unmodeled forces. To cope with this issue, in this brief, we integrate force sensory feedback with a robust energy shaping design. This methodology allows us to incorporate integral force controls while preserving in closed loop the port-Hamiltonian structure, something that is not possible with traditional force regulators. We discuss the practical implementation of our method and provide simple numerical algorithms to compute in real time some of its control terms. To validate our approach, we report an experimental study with an open architecture robot manipulator. [ABSTRACT FROM PUBLISHER]

We propose a solution to the problem of adaptive speed observer for a class of mechanical systems containing cross terms in the velocity (momenta). We focused our attention on mechanical systems with unknown constant input disturbances and Coulomb friction matrix, which generate products of unmeasurable velocities and unknown friction parameters. The adaptive speed observer proposed is based on the well-known Immersion and Invariance technique. We ensure global convergence of the speed observer, while the friction parameters estimation remain bounded. Our approach is validated through simulations and experimental results. [ABSTRACT FROM AUTHOR]