Distributed Feedback Optimization of Nonlinear Uncertain Systems Subject to Inequality Constraints

• 成果类型: Article
• 署名作者: Qin, Zhengyan; Liu, Tengfei; Liu, Tao; Jiang, Zhong-Ping; Chai, Tianyou
• 署名单位: Northeastern University - China; University of Hong Kong; University of Hong Kong; The University of Hong Kong Shenzhen Institute of Research & Innovation; New York University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3343346
• 发表日期: 2024
• 页码: 3989-3996
• 关键词: Optimization; Heuristic algorithms; Distributed feedback devices; linear programming; Multi-agent systems; Power system dynamics; uncertain systems; Distributed feedback optimization; inequality constraints; Nonlinear systems

摘要

This article studies the distributed feedback optimization problem for nonlinear uncertain multi-agent systems subject to inequality constraints. A new class of distributed optimization algorithms is proposed by extending the standard primal-dual dynamics and introducing two new inputs to deal with the couplings arising from feedback optimization. With each controlled agent satisfying a mild dissipation assumption, the proposed distributed feedback optimization algorithms, using only the output-dependent gradient value of each agent's corresponding local objective function and the information from its neighboring agents, can steer the outputs of the agents to a common set-point, which minimizes the total objective function while satisfying the inequality constraints. A composite Lyapunov function is constructed to prove global asymptotic stability of the closed-loop system at the equilibrium corresponding to the optimal point.