Abstract
We present a decentralized optimization method for solving the coordination problem of interconnected nonlinear discrete-time dynamic systems with multiple decision makers. The optimization framework embeds the inherent structure in which each decision maker has a mathematical model that captures only the local dynamics and the associated interconnecting global constraints. A globally convergent algorithm based on sequential local optimizations is presented. Under assumptions of differentiability and linear independence constraint qualification, we show that the method results in global convergence to ε-feasible Nash solutions that satisfy the Karush-Kuhn-Tucker necessary conditions for Pareto-optimality. We apply this methodology to a multiple unmanned air vehicle system, with kinematic aircraft models, coordinating in a common airspace with separation requirements between the aircraft.
| Original language | English |
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| Pages (from-to) | 1147-1155 |
| Number of pages | 9 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Volume | 1 |
| Publication status | Published - 2002 |
| Externally published | Yes |
| Event | 41st IEEE Conference on Decision and Control - Las Vegas, NV, United States Duration: 10 Dec 2002 → 13 Dec 2002 |