Showing papers by "Rogelio Lozano published in 1993"
TL;DR: It is proved that the (modified) estimate of the high frequency gain has a uniform positive lower bound and was solved by using the least squares covariance matrix properties to define an appropriate modification of the parameters estimates.
16 citations
TL;DR: A globally convergent adaptive control scheme for nonminimum phase systems is presented, based on a particular periodic pole-placement controller, and a lower bound on the estimated model controllability is ensured.
Abstract: A globally convergent adaptive control scheme for nonminimum phase systems is presented. The approach is based on a particular periodic pole-placement controller. An ad-hoc parameter estimate correction procedure is used to prevent any possible singularities in the control law computation. Furthermore, a lower bound on the estimated model controllability is ensured. The a priori knowledge on the system is reduced to the process order. >
15 citations
TL;DR: In this paper, it was shown that a Lyapunov-stable system can be analyzed as the feedback connection of two (strictly) passive subsystems, and that adaptive schemes for linear plants of any relative degree can be unified through a passivity point of view.
Abstract: In this paper we study new relationships between a class of Lyapunov functions and the passivity theorem. It is proved that under some (sufficient) conditions a Lyapunov-stable system can be analysed as the feedback connection of two (strictly) passive subsystems. It is also shown that very recent adaptive schemes for linear plants of any relative degree can in a certain sense be unified through a passivity point of view.
12 citations
15 Dec 1993
TL;DR: An adaptive regulator for general discrete-time linear systems knowing only an upper bound on its order is presented, based on a "lifted" representation of the plant and possible singularities are avoided by appropriately modifying the least squares parameter estimates.
Abstract: This paper presents an adaptive regulator for general discrete-time linear systems knowing only an upper bound on its order. The scheme is based on a "lifted" representation of the plant and possible singularities are avoided by appropriately modifying the least squares parameter estimates. The stability analysis does not reply on any arguments about excitation of the plant signals. >
2 citations
TL;DR: In this paper, an indirect, model reference adaptive control for minimum phase linear systems of arbitrary relative degree is presented and global stability of the closed-loop system is proved in spite of bounded disturbances and asympotic tracking is achieved in the ideal case.
Abstract: This work presents an indirect, model reference adaptive control for minimum phase linear systems of arbitrary relative degree. Global stability of the closed-loop system is proved in spite of bounded disturbances and asympotic tracking is achieved in the ideal case.
2 citations
TL;DR: In this paper, an alternative way to solve the problem of singularities in model reference adaptive control of linear MIMO systems using a parameter modification procedure based on the Least Squares covariance matrix inverse was proposed.
1 citations
15 Dec 1993
TL;DR: In this article, an indirect model reference adaptive control for minimum phase linear systems of arbitrary relative degree is presented, in spite of bounded disturbances and asympotic tracking is achieved in the ideal case.
Abstract: This work presents an indirect model reference adaptive control for minimum phase linear systems of arbitrary relative degree. Global stability of the closed loop system is proved in spite of bounded disturbances and asympotic tracking is achieved in the ideal case. >
1 citations
01 Jan 1993
TL;DR: In this paper, an adaptive control scheme for nonlinear systems of the form x˙= c*Tf(x) + b*u where c* is a constant vector and b* a constant scalar is presented.
Abstract: This paper presents an adaptive control scheme for nonlinear systems of the form x˙= c*Tf(x) + b*u where c* is a constant vector and b* a constant scalar. The control scheme achieves local asymptotic stability without a-priori knowledge of the b* coefficient. The singularity in the control law has been overcome through a suitable modification of the parameter estimates which is based on the inverse of the least squares covariance matrix.
01 Jan 1993
TL;DR: In this article, an adaptive control scheme was proposed to stabilize second order systems of the form y¨+a1*y˙+a2*y+a 2*y=b0*u˙ +b1*u which may possibly be non-minimum phase.
Abstract: This paper presents an adaptive control scheme to stabilize second order systems of the form y¨+a1*y˙+a2*y=b0*u˙+b1*u which may possibly be non-minimum phase. The adaptive control scheme achieves asymptotical stabilization through pole placement techniques without any a priori knowledge on the plant parameters. The adaptive control law is free from singularities in the sense that the plant estimated model is always controllable. The singulariTheties have been overcome by a suitable modification of the parameter estimates which is based upon standard Least Squares covariance matrix properties.