In this article we present a method to generate safe sets for linear discrete-time systems subject to non-convex constraints that can be represented as a union of polytopes. It is then shown how a reference governor can be implemented for safe reference tracking tasks. A theoretical analysis of the safe set is presented and properties of the reference governor scheme are derived. The guarantees include safety at any time as well as finite-time convergence of the applied reference command to any strictly admissible reference command. For the proposed reference governor, online computational overhead is low. Moreover, it is shown that for specific instances of the complex constraint sets, the safe set can be computed efficiently. Extensive simulation results demonstrating the applicability of the method and online/offline computation times are reported.
Motion planning algorithms compute control sequences that drive autonomous robots to goal regions while avoiding unsafe states. Existing methods, from sampling-based planning to deep reinforcement learning, typically provide task-completion guarantees only with respect to a nomin…
In this paper, we aim to automate the adjustment of air handling unit (AHU) setpoints within heating, ventilation, and air conditioning (HVAC) systems to maintain indoor temperatures at user-specified levels. A key challenge lies in obtaining sufficient high-quality sensor data f…
Dynamic speed limit control has emerged as a promising strategy to improve freeway sustainability in mixed traffic environments with connected automated vehicles (CAVs). However, most existing approaches assume that the CAV penetration rate is deterministic and can be accurately…
Safe steerable catheter control is fundamentally a problem of interaction dynamics: the tip must follow a planned motion, remain compliant against moving tissue, reject friction and hysteresis, and respect a clinically meaningful never-exceed contact-force bound. We formulate cat…
Promoting cooperative behaviour amongst decision makers has key implications for the long term sustainability of social systems. Incentives can promote cooperation in situations where defection is more favourable. Previous research has identified optimal decentralised incentives…
Advanced control of heating and cooling systems can substantially reduce energy costs and pollution. However, real-world adoption of popular algorithms among researchers, such as model predictive control (MPC) and reinforcement learning (RL), remains limited due in part to their…