scispace - formally typeset
R

Richard H. Middleton

Researcher at University of Newcastle

Publications -  396
Citations -  13068

Richard H. Middleton is an academic researcher from University of Newcastle. The author has contributed to research in topics: Control theory & Linear system. The author has an hindex of 48, co-authored 393 publications receiving 12037 citations. Previous affiliations of Richard H. Middleton include Hamilton Institute & University of California.

Papers
More filters
Journal ArticleDOI

Fundamental limitations in control over a communication channel

TL;DR: A signal-to-noise ratio (SNR) approach is used to obtain a tight condition for the linear time invariant output feedback stabilisation of a continuous-time, unstable, non minimum phase (NMP) plant with time-delay over an additive Gaussian coloured noise communication channel.

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

TL;DR: In this article, the relationship between the continuous-time Riccati equation and the corresponding discrete-time equation with fast sampling has been explored and the interconnection is established by formulating the discrete case using delta operators.
Journal ArticleDOI

Convexity of the cost functional in an optimal control problem for a class of positive switched systems

TL;DR: Algorithms to find the optimal solution are presented and an example, taken from a simplified model for HIV mutation mitigation is discussed, showing that the cost is convex with respect to the control variables.
Proceedings ArticleDOI

A survey of inherent design limitations

TL;DR: The theory of inherent design limitations provides the basic scientific background for the field of linear feedback control, and all control engineers need to know the basic results from this area as mentioned in this paper, and such knowledge is useful much earlier in the engineering design cycle, in order to configure the plant and specify sensors and actuators so that the resulting feedback control problem is tractable.
Journal ArticleDOI

The class of all stable unbiased state estimators

TL;DR: In this article, the authors show that a similar result holds for the class of all stable unbiased state estimators, and this result is believed to have major implications for the design of robust estimators to deal with non-standard noise sources, modelling errors, etc.