Receding horizon control and coordination of multi‐agent systems using polynomial expansion

Abstract

The present paper proposes a flexible and efficient methodology for constructing norm-bounded optimal receding horizon control laws for a group of agents, each one of which is described as a repeated integrator of an arbitrary order and with a common input delay. The goal of each agent is to track the given target, while simultaneously avoiding other agents in the group. Polynomial expansion, together with appropriate subspace projection, is utilized in order to derive receding control law in the closed form. Properties of this control law have been investigated, and its link to a well-known control strategy based on avoidance functions, which ensures collision avoidance in the case of first-order integrator agents, has been derived. K E Y W O R D Sexplicit control law, multi-agent systems (MASs), polynomial expansion, receding horizon control (RCH)

State‐dependent indirect hp‐pseudospectral method for rigid spacecraft attitude optimal control problem

“…Accordingly, the discrete TPBVP defined by ( 33) and ( 34) is algebraic equations in terms of the coefficients at CGL nodes, 𝜏 (k) l , and can be obtained by substituting (31) into (19) and (20).…”

“…In Liu et al [17], although the adaptive mesh criterion is used in indirect $$$ hp $$$‐pseudospectral method (IHPPM), the computational efficiency still needs to be improved. Besides, considering the uncertainties of external disturbances, model parameters, and initial states in practice, it is necessary to develop a closed‐loop control law using the receding horizon control (RHC) method [18–20]. The control framework can improve the robustness of system and solve the feedback control at each control cycle rapidly via SDIHP.…”