Showing papers by "Rogelio Lozano published in 1997"
01 Jul 1997
TL;DR: In this paper, the robustness limitations of recursive identification algorithms are highlighted and a particular non-recursive identification algorithm is shown to improve robustness to bounded disturbances, noise and slowly time-varying parameters only at the expense of performing an online eigenvalue decomposition on a symmetric semidefinite positive matrix.
Abstract: In this paper, the robustness limitations of current recursive identification algorithms are highlighted. Then, it is shown how a particular nonrecursive identification algorithm dramatically improves the robustness to bounded disturbances, noise and slowly time-varying parameters. only at the expense of performing an on-line eigenvalue decomposition on a symmetric semidefinite positive matrix. Furthermore, this algorithm do not require any a priori knowledge of a bound on the disturbance and noise and of a bound on the parameter values.
14 citations
04 Jun 1997
TL;DR: In this paper, a PD controller for robot manipulators simultaneously considering joint flexibility, actuators dynamics as well as friction is presented, and global convergence to a desired fixed angular position is proved only using position and velocity measurements.
Abstract: This paper presents a PD controller for robot manipulators simultaneously considering joint flexibility, actuators dynamics as well as friction. The convergence analysis of the proposed PD controller is carried out using passivity. Global convergence to a desired fixed angular position is proved only using position and velocity measurements.
3 citations
01 Jul 1997
TL;DR: In this paper, an adaptive control law for PR plants is proposed, where the main feature is that the role of adaptation is not to stabilize the plant but to improve performance, and the plant estimates are constrained to a region in the parameter space corresponding to Positive Real Observable Controllable plants.
Abstract: An adaptive control law for PR plants is proposed. The main feature of this approach is that the role of adaptation is not to stabilize the plant but to improve performance. The plant is identified using a standard Least Squares algorithm and through a suitably defined parameter modification, the plant estimates are constrained to a region in the parameter space corresponding to Positive Real Observable Controllable plants. Using these estimates an LQG disipative controller is designed which trivialy stabilizes the plant. Simulation results are presented.
3 citations
01 Jul 1997
TL;DR: In this article, a brief review of the various definitions on passivity of nonlinear systems and positive real transfer functions is presented, and the stability of the feedback interconnection of passive systems to relax the assumptions on the plant to be controlled.
Abstract: In this paper, we present a brief review of the various definitions on passivity of nonlinear systems and positive real transfer functions. The relationships between the definitions are clarified and illustrated with examples. Furthermore we review the stability of the feedback interconnection of passive systems to relax the assumptions on the plant to be controlled. In particular we present a version of the passivity theorem that requires weaker conditions on the interconnected systems.
1 citations
10 Dec 1997
TL;DR: In this paper, a new indirect adaptive control method is presented, which is based on a lifted representation of the plant which can be stabilized using a simple periodic control scheme, and the controller parameter computation involves the inverse controllability/observability matrix.
Abstract: A new indirect adaptive control method is presented. This method is based on a lifted representation of the plant which can be stabilized using a simple periodic control scheme. The controller parameter computation involves the inverse controllability/observability matrix. Potential singularities of this matrix are avoided by means of an appropriate estimate modification. This estimate transformation is linked to the covariance matrix properties and hence it preserves the convergence properties of the original estimates. This modification involves the singular value decomposition of the controllability/observability matrix estimate. As compared to previous studies in the subject the controller proposed here does not require the frequent introduction of periodic n-length sequences of zero inputs. Thus with the new controller the system is almost always operating in a closed loop, which should lead to better performance characteristics.