Showing papers by "Rogelio Lozano published in 1998"
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15 Jan 1998
TL;DR: Adaptive control provides techniques for automatic adjustment in real-time of controller parameters to achieve or maintain a desired level of system performance when the process parameters are unknown or variable as mentioned in this paper. But adaptive control is not suitable for all applications.
Abstract: From the Publisher:
Adaptive Control provides techniques for automatic adjustment in real time of controller parameters to achieve or maintain a desired level of system performance when the process parameters are unknown or variable. The book deals coherently with many aspects of the field, starting with the problems posed and moving onto the presentation of the solutions and their practical significance. As well as presenting recent trends, the book also looks at: Synthesis and Analysis of Parameter Adaptation Algorithms, Recursive Plant Model Identification in Open and Close Loop, Robust Digital Control for Adaptive Control, Robust Parameter Adaptation Algorithms, Direct and Indirect Adaptive Control, and Practical Aspects and Applications. To reflect the importance of digital computers for the application of adaptive control techniques, discrete-time aspects are emphasized. To guide the reader, the book contains various applications of adaptive control techniques.
404 citations
TL;DR: A simple controller for balancing the inverted pendulum and rise it to its upper equilibrium position is proposed based on the passivity properties of the cart and pendulum system.
30 citations
01 Jan 1998
TL;DR: This chapter examines in detail the practical aspects related to the implementation of the various adaptive control schemes presented in the previous chapters.
Abstract: The objectives of this chapter are:
To examine in detail the practical aspects related to the implementation of the various adaptive control schemes presented in the previous chapters.
To present a number of cases where these adaptive control schemes are applied.
12 citations
16 Dec 1998
TL;DR: In this article, the adaptive control of a class of second-order nonlinear systems with a triangular structure and concave/convex parametrization is studied, and global boundedness and convergence to within a desired precision are established.
Abstract: This paper deals with adaptive control of a class of second-order nonlinear systems with a triangular structure and concave/convex parametrization. In the paper by Annaswamy et al. (1998), it was shown that nonlinearly parametrized systems that satisfy certain matching conditions can be adaptively controlled in a stable manner. In this paper, we relax these matching conditions and include additional dynamics between the nonlinearities and the control input. Global boundedness and convergence to within a desired precision /spl epsiv/ is established. No over-parametrization of the adaptive controller is required.
9 citations
TL;DR: In this paper, a modified version of the standard LS algorithm is proposed, where a series of convergence properties on the identification error, the parameter estimates and the covariance matrix are established.
4 citations
01 Jan 1998
TL;DR: In this article, the adaptive control of a class of second-order nonlinear systems with a triangular structure and concave-konvex parameterization was studied and global boundedness and convergence to within a desired precision was established.
Abstract: This paper deals with adaptive control of a class of second-order nonlinear systems with a triangular structure and concavekonvex parameterization. In [I] it was shown that nonlinearly parameterized systems that satisfy certain matching conditions can be adaptively controlled in a stable manner. In this paper, we relax these matching conditions and include additional dynamics between the nonlinearities and the control input. Global boundedness and convergence to within a desired precision E is established. No overparametrization of the adaptive controller is required.
16 Dec 1998
TL;DR: The problem of on-line identification of continuous time, time-varying systems is considered via the minimization of a least squares criterion with a forgetting function.
Abstract: The problem of on-line identification of continuous time, time-varying systems is considered via the minimization of a least squares criterion with a forgetting function. The forgetting function used depends on two time-varying parameters which play crucial roles in the stability analysis of the method.