In this paper, an efficient framework is proposed to the consensus and formation control of distributed multiagent systems with second-order dynamics and unknown time-varying parameters, by means of an adaptive iterative learning control approach. Under the assumption that the acceleration of the leader is unknown to any follower agents, a new adaptive auxiliary control and the distributed adaptive iterative learning protocols are designed. Then, all follower agents track the leader uniformly on OE0, T for consensus problem and keep the desired distance from the leader and achieve velocity consensus uniformly on OE0, T for the formation problem, respectively. The distributed multi-agent coordinations performance is analyzed based on the Lyapunov stability theory. Finally, simulation examples are given to illustrate the effectiveness of the proposed protocols in this paper.

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Rheological properties of starch are affected by swelling of the granules that is in turn controlled by the degree of crosslinking. A previously developed model for swelling of starch granules was extended to account for electrostatic interactions. Maize starch was crosslinked with sodium trimetaphosphate. Granule swelling of 8% suspension of crosslinked maize starch when subjected to heating to 70,75,80,85 and 90 °C was more pronounced at higher temperatures eventually approaching equilibrium with the swelling ratio decreasing with increase in extent of crosslink. The number of crosslinks in the starch network was inferred from equilibrium swelling and related to peak viscosity and zeta potential. Chemical potential profile as well as the temperature profile within the granule at different times were predicted which were then employed to evaluate the evolution of granule size. The proposed model is able to describe the effect of crosslinking on swelling behavior.