Stability Implications of Process Control Strategies Using Quantum Computations for Next-Generation Manufacturing

To enhance process efficiency, evolving industrial setups necessitate increased data collection and processing. This increase in processing demand, as observed in multiple other fields, including process systems engineering, has piqued interest in quantum computations. From a process control perspective, however, the utility of quantum computing remains unclear. We hypothesize that, by implementing existing controllers on quantum computers, we will gain insights into the usefulness of quantum computation for process control.

With this motivation, we investigate the concept of quantum computing from a process control perspective by controlling a simple linear process using a proportional controller. We send process measurements to a quantum Fourier-based addition algorithm to determine an appropriate control input using IBM's quantum experience SDK, Qiskit. We will then compare the algorithm to an implementation of the same control strategy in the presence of quantum noise. Multiple algorithms will subsequently be used to determine the impact of noise on different algorithm structures, along with a variety of factors that influence the impact of quantum noise on process stability guaranteed by the proportional control strategy.