Showing papers by "Richard H. Middleton published in 1988"

Design issues in adaptive control

Abstract: An integrated approach to the design of practical adaptive control algorithms is presented. Many existing ideas are brought together, and the effect of various design parameters available to a user is explored. The theory is extended by showing how the problem of stabilizability of the estimated model can be overcome by running parallel estimators. It is shown how asymptotic tracking of deterministic set points can be achieved in the presence of unmodeled dynamics. >

Adaptive control of time-varying linear systems

Abstract: The authors present a global bounded-input-bounded-state stability theory for a class of continuously adapting controllers applied to time-varying linear systems. This gives theoretical support to the application of many of the algorithms used in practice. A key feature of the analysis is that no persistence of excitation requirement is needed. >

Modified least squares algorithm incorporating exponential resetting and forgetting

Abstract: In this paper we present the general analysis of a class of least squares algorithms with emphasis on their dynamic performance particularly in the presence of poor excitation. The analysis is carried out in a deterministic framework and stresses geometrical interpretations. The core of this paper is the proposal and analysis of a new algorithm which incorporates exponential forgetting and resetting to an unprejudiced treatment of data when excitation is poor. The algorithm is particularly suitable for tracking time-varying parameters and is similar in computational complexity to the standard recursive least squares algorithm. The superior performance of the algorithm is verified via simulation studies.

Connection between continuous and discrete Riccati equations with applications to kalman filtering

Abstract: The aim of the paper is to explore the relationship between the continuous-time Riccati equation and the corresponding discrete-time equation with fast sampling. The interconnection is established by formulating the discrete case using delta operators. The application of these results to the Kalman filtering problem highlights the importance of analogue prefiltering in the sampling process. A secondary benefit arising from the use of the delta operator is that improved numerical behaviour is obtained for solution algorithms, compared with that obtainable with the usual shift operator.

Hybrid adaptive control for robot manipulators

Abstract: An adaptive control scheme is proposed for rigid-link robots where the control signal computations are performed continuously and the control coefficient computations are performed discretely. A global boundedness result is established for the resulting hybrid scheme, independent of the sampling rate. It is also shown that the position, velocity and acceleration tracking errors are of the order of the sampling period. This study brings the analysis of adaptive robot control closer to practice, where a discrete control law implementation is invariably used. >

Indirect Adaptive Control: An Integrated Approach

Abstract: The aim of this paper is to present the basis of the adaptive control approach being pursued in the Centre for Industrial Control Science at the University of Newcastle. A key feature of this approach is the separate optimization of procedures for estimation and on-line control law synthesis. Regarding the estimation module, attention is given to such features as data filtering, the response of the estimator, techniques for handling unmodelled dynamics and the question of numerical accuracy. Regarding the control law synthesis module, attention is given to robustness to unstructured modelling errors, disturbance and set-point feedforward techniques and implementation issues. In the paper, these various aspects are illustrated by reference to a case study problem proposed by Mike Master and Herb Cohn from Texas Instruments.

A unified approach to adaptive control

Abstract: This chapter presents an integrated approach to the design of adaptive control systems. Emphasis will be given to the unification of analogue and sampled data adaptive controllers. This unification allows continuous time intuitions to be used in the discrete time case. It also gives confidence in the discrete time algorithms when implemented with rapid sampling. We adopt the view that a practical adaptive control algorithm should be considered as a combination of a robust parameter estimation scheme together with robust control synthesis. A key issue in the design of robust parameter estimators and robust control laws is the effect of unmodelled errors.