Robust performance analysis of cooperative control dynamics via integral quadratic constraints

We study cooperative control dynamics with gradient based forcing terms. As a specific example, we focus on source-seeking dynamics with vehicles embedded in an unknown scalar field with a subset of agents having gradient information. We consider time-invariant and uncertain interaction potentials common in formation control and flocking. We leverage the framework of α -integral quadratic constraints to obtain convergence rate estimates whenever exponential stability can be achieved. Sufficient conditions take the form of linear matrix inequalities independent of the size of network. A derivation (purely in time-domain) of the so-called hard Zames-Falb α -IQCs involving general non-causal higher order multipliers is given along with a suitably adapted parameterization of the multipliers to the α -IQC setting. Numerical examples illustrate the application of theoretical results.

Subjects

cooperative control

Costs

Formation control

Heuristic algorithms

linear matrix inequalities

Optimization

robust control

Trajectory

Vectors

Vehicle dynamics

DDC Class

004: Computer Sciences

510: Mathematics

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Robust performance analysis of cooperative control dynamics via integral quadratic constraints