Author(s)

Jiaxiangyi Liu ¹, Xinzhe Gao ²

Affiliation(s)

¹ School of Electronics and Information Engineering, Liaoning University of Science and Technology, Liaoning, China
² Artificial Intelligence Division, Beijing Vision Zhiyuan Technology Co., Ltd., Beijing, China

Corresponding Author

Xinzhe Gao

ABSTRACT

Intelligent optimisation algorithms face three obstacles when entering the control loops of wastewater treatment plants (WWTPs): the lack of a trustworthy evaluation environment, the absence of formally provable safety guarantees, and the year-by-year depreciation of once-delivered algorithms. This paper proposes a mechanism-constrained self-evolving optimisation system for wastewater treatment processes, organised as a one-core, two-engine, double closed-loop architecture. The offline evolution engine evolves optimisation strategies through a sample-generate-evaluate-select-archive loop, using a mechanistic model as the trustworthy evaluation field; the online execution engine forms a three-level closed loop with the mechanistic model, a physics-informed neural network (PINN) and model predictive control (MPC). An evolved algorithm may only be issued after passing five one-vote-veto safety gates, namely historical replay, PINN fast screening, high-fidelity mechanistic simulation, shadow-mode operation and graduated grey-release, and is further protected by three layers of formal safety mechanisms: a control barrier function filter, a runtime assurance architecture and uncertainty quantification. Upon any boundary violation the system fuses and rolls back to the gold-medal strategy within ten seconds. Verification shows that the three-level evaluation filtering reduces the evaluation cost by three orders of magnitude, that quantum-inspired search accelerates convergence by about one order of magnitude, and that the system reduces aeration energy consumption by 5%-15% and chemical consumption by 10%-30%, providing a feasible path for artificial intelligence to safely enter wastewater treatment control loops.

KEYWORDS

Wastewater treatment; Evolutionary computation; Model predictive control; Control barrier function; Runtime assurance

CITE THIS PAPER

Jiaxiangyi Liu, Xinzhe Gao. Mechanism-Constrained Self-Evolving Optimisation and Safe Trustworthy Closed-Loop Control for Wastewater Treatment Processes. Computing, Performance and Communication Systems (2026). Vol. 10, No. 1, 92-97. DOI: http://dx.doi.org/10.23977/cpcs.2026.100111.

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