Document Type
Article
Abstract
Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum device. While one algorithm achieved this objective, another performed poorly, raising questions about the underlying reasons for their differing performance. This study explores how conventional control engineering techniques for handling nondeterminism (e.g., modifying sampling period lengths or applying only stabilizing control actions based on steady-state tracking) could enhance system response in the presence of noise. Utilizing IBM’s Qiskit, a quantum simulator was used to evaluate algorithmic and heuristic control strategies to improve the steady-state tracking performance of a P-control law under quantum noise. The objective here is to provide insight into the feasibility of near-term quantum devices to execute control actions with safety considerations.
Disciplines
Controls and Control Theory | Information Security | Process Control and Systems
Recommended Citation
K. K. Rangan and H. Durand, "Heuristic Strategies for Process Stabilization using Proportional Control Implemented by a Noisy Quantum Simulator," 2025 American Control Conference (ACC), Denver, CO, USA, 2025, pp. 4866-4871, doi: 10.23919/ACC63710.2025.11108045.
Included in
Controls and Control Theory Commons, Information Security Commons, Process Control and Systems Commons
Comments
© American Automatic Control Council (AACC) 2025. Peer Reviewed Conference Proceeding, 2025 American Control Conference (ACC), July 8-10, 2025, Denver, CO, USA. Originally published at https://doi.org/10.23919/ACC63710.2025.11108045. Financial support from the Air Force Office of Scientific Research (FA9550-19-1-0059), National Science Foundation (CNS-1932026, CBET- 1839675, CBET-2143469), Wayne State University Grants Boost funding, and Wayne State University is gratefully acknowledged.