Distributed Continuous-time Algorithm for Time-varying Quadratic Programming with Coupled Equality Constraint

This paper describes a distributed algorithm that employs the distributed average tracking approach to address time-varying quadratic programming problem. The problem involves time-varying coupled equality constraint and is based on continuous-time multi-agent system. The local objective functions' Hessian matrices are time-varying and different from one another. The basic purpose is to minimize the sum of time-varying objective functions through local interaction with each agent possessing knowledge of its own objective function. The dynamics of multi-agent system makes sure that the states of all agents will find and follow the optimal solutions. Finally, the efficacy of the proposed approach is successfully showcased through a numerical example with simulations.