Engineering topics

Keel, Lee H.

Publications and source records attributed to Keel, Lee H..

3 records

NASA NTRS1998

The Design of Stable Nonlinear Controllers for a Class of Nonlinear Plants Based on Neutral Networks

Extensive empirical evidence has been published in the literature to demonstrate the enormous potential of multilayer neural network controllers. In spite of these results, practical implementation of these control schemes has been held back by the lack of an analytical proof of the stability of the controlled system. The objective of this paper is to present a nonlinear control scheme based on multilayer neural networks for the control of a class of nonlinear plants. The stability of the closed loop system will be rigorously established.

Adetona, Olawale↗

NASA NTRS1998

Sufficient Conditions for the Stability of a Lur'e System With Two Nonzero Inputs Based on Lyapunovs Direct Method

The Lur'e problem is a famous problem in nonlinear control theory. The analysis of this system is usually restricted to Lur'e systems in which the external input is zero. One form of this problem involves the stability analysis of the Lur'e system with two nonzero inputs. The stability analysis of this type of system is traditionally performed based on L stability theory. The objective of this paper is to present sufficient conditions for the stability of this system based on Lyapunov's direct method. This is a conceptually simpler approach to the existing analysis based on L stability theory and it provides some additional information about the stability of the system.

Adetona, Olawale↗

NASA NTRS1993

Quantification of model error via an interval model with nonparametric error bound

The quantification of model uncertainty is becoming increasingly important as robust control is an important tool for control system design and analysis. This paper presents an algorithm that effectively characterizes the model uncertainty in terms of parametric and nonparametric uncertainties. The algorithm utilizes the frequency domain model error which is estimated from the spectra of output error and input data. The parametric uncertainty is represented as an interval transfer function while the nonparametric uncertainty is bounded by a designed error bound transfer function. Both discrete and continuous systems are discussed in this paper. The algorithm is applied to the Mini-Mast example, and the detail analysis is given.

Lew, Jiann-Shiun↗