Online Guaranteed Reachable Set Approximation for Systems with Changed Dynamics and Control Authority

TL;DR

This paper introduces an efficient method for approximating reachable sets of nonlinear control systems with changed dynamics and reduced control authority, leveraging prior nominal reachable set data for faster computation.

Contribution

The method provides a novel, computationally efficient way to approximate off-nominal reachable sets without requiring convexity, suitable for fault-tolerant control and failure recovery.

Findings

Applicable to systems with changed dynamics and control authority.

Does not require convexity of reachable sets.

Demonstrated on ship heading, triangular, and coupled linear systems.

Abstract

This work presents a method of efficiently computing inner and outer approximations of forward reachable sets for nonlinear control systems with changed dynamics and diminished control authority, given an a priori computed reachable set for the nominal system. The method functions by shrinking or inflating a precomputed reachable set based on prior knowledge of the system's trajectory deviation growth dynamics, depending on whether an inner approximation or outer approximation is desired. These dynamics determine an upper bound on the minimal deviation between two trajectories emanating from the same point that are generated on the nominal system using nominal control inputs, and by the impaired system based on the diminished set of control inputs, respectively. The dynamics depend on the given Hausdorff distance bound between the nominal set of admissible controls and the possibly unknown impaired space of admissible controls, as well as a bound on the rate change between the nominal and off-nominal dynamics. Because of its computational efficiency compared to direct computation of the off-nominal reachable set, this procedure can be applied to on-board fault-tolerant path planning and failure recovery. In addition, the proposed algorithm does not require convexity of the reachable sets unlike our previous work, thereby making it suitable for general use. We raise a number of implementational considerations for our algorithm, and we present three illustrative examples, namely an application to the heading dynamics of a ship, a lower triangular dynamical system, and a system of coupled linear subsystems.