Robust edge weight synthesis for LPV multi-agent systems with integral quadratic constraints

Abstract

This work implements a non-linear programming method to synthesize edge weights of an adjacency matrix for a linear parameter varying multi-agent system using bilinear matrix inequalities, which suffer uncertainties. First, convex–concave decompositions are used on the bilinear matrix inequality constraints for nominal H∞synthesis. Then this method is improved to consider uncertainties using integral quadratic constraints with time domain representations. Agents composing the multi-agent system are depicted as longitudinal dynamics of F16 Vista aircraft at different operating conditions, which share their output information to achieve consensus. Topology of the multi-agent system is predefined and edge weights are defined as functions of the decision variable.

Keywords

• Multi-agent systems
• Robust control
• Edge weight synthesis
• Integral quadratic constraints
• Nonlinear optimization
• Sequential optimization