Control Ability with Time Attributy for Linear Continous-time Systems

TL;DR

This paper introduces a novel approach to analyze and optimize the control ability of linear continuous-time systems by defining the controllability region's volume and shape factors, with efficient algorithms and analytical formulas for finite and infinite time horizons.

Contribution

It proposes a relation theorem linking control ability, control strategy space, and closed-loop performance, along with recursive algorithms and analytical volume formulas for controllability regions.

Findings

Recursive volume-computing algorithms with low complexity.

Analytical volume formulas for systems with real eigenvalues.

Shape factors describing controllability region geometry.

Abstract

In this paper, the control ability with time attributy for the linear continuous-time (LCT) systems are defined and analyzed by the volume computing for the controllability region. Firstly, a relation theorem about the open-loop control ability, the control strategy space (\textit{i.e.}, the solution space of the input variable for control problems), and the some closed-loop performance for the LCT systems is purposed and proven. This theorem shows us the necessity to optimize the control ability for the practical engineering problems. Secondly, recurssive volume-computing algorithms with the low computing complexities for the finite-time controllability region are discussed. Finally, two analytical volume computations of the infinite-time controllability region for the systems with $n$ different and repeated real eigenvalues are deduced, and then by deconstructing the volume computing equations, 3 classes of the shape factors are constructed. These analytical volume and shape factors can describe accurately the size and shape of the controllability region. Because the time-attribute control ability for LCT systems is directly related to the controllability region with the unit input variables, based on these analytical expressions on the volume and shape factors, the time-attribute control ability can be computed and optimized conveniently.