Fixed-Time Zero-Gradient-Sum Algorithm for Disturbed Linear Heterogeneous Multi-Agent Systems

Achieving more precise modeling and control of vehicle dynamics for multi-vehicle collaboration is pivotal in steering vehicles toward cleaner, smarter, and safer de-velopment. This paper proposes a novel zero-gradient-sum algorithm (ZGSA) based on disturbed linear heterogeneous multi-agent systems (MASs) to solve distributed optimization problems. Using integral sliding manifold and fixed-time control theory, the designed ZGSA is proven to obtain the exact optimal solution within a fixed time. Moreover, it circumvents the requirement on initial conditions, which is a common constraint in classical ZGSAs. Finally, a simulation substantiates the efficacy and robustness of the designed ZGSA.