This paper addresses the distributed consensus controller design approaches for one-sided Lipschitz nonlinear multiagents by employing relative state feedback. A new treatment for one-sided Lipschitz nonlinearity is rendered from the consensus control point of view. By employing the quadratic inner-boundedness and the one-sided Lipschitz constraints, a sufficient condition for asymptotic consensus of nonlinear systems under strongly connected communication topologies is provided. Further, a robust consensus protocol design scheme for the nonlinear multiagents is derived by ensuring the L₂ stability of the consensus error system. Furthermore, a novel robust consensus control scheme against amplitude-bounded perturbations is developed that guarantees asymptotic convergence of the consensus error into a compact set. Extensions to the proposed methodologies for the leader-following consensus for a spanning tree communication topology with the leader as the root are addressed. In contrast to the conventional consensus control methodologies, this paper is less conservative and can be applied to a broader class of nonlinear multiagent systems. Moreover, the proposed consensus control approach is less conservative for robustness against disturbances owing to its ability to handle amplitude-bounded disturbances and due to the relaxation of a balanced communication topology. A numerical simulation study is provided for the consensus control of eight mobile agents.

Green transportation has become our top priority due to the depletion of the earth’s natural resources and rising pollutant emission levels. Plug-in electric vehicles (PEVs) are seen as a solution to the problem because they are more cost and environment friendly. Due to rapid industrialization and government incentives for zero-emission transportation, a significant challenge is also constituted in power grids by the self-interested nature of PEVs, with the asymmetry of information between the charging power demand and supply sides. In this paper, we propose an optimal strategy in industrial energy management system, based on evolutionary computing, to characterize different charging situations. The proposed approach considers stochastic, off-peak, peak, and electric power research institute charging scenarios for attaining the vehicle-to-grid capacity in terms of optimal cost and demand. An extensive scheduling of charging cases is studied in order to avoid power outages or scenarios in which there is a significant supply-demand mismatch. Furthermore, the proposed scheme model also reduces the greenhouse gases emission from generation side to build a sustainable generation infrastructure, which maximizes the utility of fuel-based energy production in the presence of certain nonlinear constraints. The simulation analysis demonstrates that PEVs can be charged and discharged in a systematic manner. The participation of transferable load through the proposed methodology can significantly reduce the economic costs, pollutant impacts, efficiency, and security of power grid operation.

This research aims to contribute in developing a mathematical model for the composite probabilistic energy emissions dispatch (CPEED) with renewable energy systems, and it proposes a novel framework, based on an existing astute black widow optimization (ABWO) algorithm. Renewable energy power generation technology has contributed to pollution reduction and sustainable development. Therefore, this research aims to explore the CPEED problem in the context of renewable energy generation systems to enhance the energy and climate benefits of the power systems. Five benchmark test systems, combined with conventional thermal power plants and renewable energy sources such as wind and solar, are considered herein to obtain the optimum solution for cost and pollutant emission by using the ABWO approach. The ascendancy is not limited to environmental impacts, but it also provides the diversification of energy supply and reduction of reliance on imported fuels. As a result, the research findings contribute in lowering the cost of fuel and pollutant emissions, correlated with electricity generation systems, while increasing the renewable energy usage and penetration. Finally, the performance and efficacy of the designed scheme have been fully validated by comprehensive experimental results and statistical analyses.

This paper addresses the leaderless consensus control for a network of multiagent systems with the one-sided Lipschitz and quadratic inner-boundedness nonlinear dynamics. A distributed dynamic consensus protocol as a function of relative state feedback of the neighboring agents with edge-based adaptive coupling weights is designed for an undirected communication graph to achieve asymptotic consensus among the nonlinear agents. Further, an extension of the proposed consensus protocol in the presence of external disturbance is devised to ensure the L₂ stability of the consensus error. This paper is less conservative and more general owing to its application to the systems with large Lipschitz constants and to a broad class of the nonlinear systems. In comparison to the previous consensus control schemes, the proposed approach can be employed to design consensus protocols for the one-sided Lipschitz systems with unknown communication topology. This feature enables the fully distributed consensus control as the communication graph information is not required for the consensus protocol design. Simulation results for a network of six mobile agents are provided to demonstrate the effectiveness of proposed consensus schemes in the absence or presence of an external disturbance.