Last week saw the 19th World Congress of the International Federation of Automatic Control in Cape Town, South Africa. Three of my collaborators, Andrea Suardi, Stefano Longo and Eric Kerrigan, were there to present our joint paper Robust explicit MPC design under finite precision arithmetic.
The basic idea of this work is simple but interesting. Since we know we make mistakes, can we make decisions in a way that insures ourselves against our own faulty decision making? In a control system, we typically want to control a “real world thing” – an aircraft, a gas turbine, etc. Ourselves and others have proposed very sophisticated ways to do this, but since with each finite precision operation we might drift further away from the correct result, can we develop our algorithm in a way that provides a guaranteed behaviour?
We show that since control engineering provides tools to control systems with uncertain behaviour, it’s possible to incorporate the uncertainty of the control algorithm itself into the model of the system we’re controlling, to produce a kind of self-aware system design.
While the setting of this paper is in so-called explicit model predictive control, there’s no reason why this general philosophy should not extend to other decision making processes. It provides a rigorous way to think about the impact of decision quality on the overall behaviour of a system, since we can generally make decisions in any number of ways ranging from “quick and dirty” to “slow and thoughtful”, we could decide how to decide based on ideas like this.