Scheme For Multi-agent Systems Research Articles

Distributed MIMO MFAC-based consensus tracking strategy for multiagent systems with fixed and switching topologies

In this research, the MIMO model-free-adaptive-control-based (MFAC-based) consensus tracking scheme for multiagent systems (MASs) has been proposed. The unknown system model of each agent is constructed by the compact form dynamic linearisation (CFDL) technique. The agents can receive the information from their neighbours, and only some agents, not all agents, can obtain the reference trajectory. Firstly, the distributed MIMO MFAC-based consensus tracking strategy for each follower agent with fixed communication topology is proposed. The proof of tracking convergence for this control strategy indicates that each agent can follow the reference trajectory. Then, we prove the MFAC-based consensus tracking scheme can be also applied to the MASs with switching topologies. Compared with prior work, the main features of this paper are that the dynamic models of agents are built only using real-time input/output data, and the MFAC-based consensus strategy can be utilised for MIMO MASs with switching topologies. Finally, two numerical simulations are provided to verify the merits and feasibility of the consensus strategy for MASs with fixed and switching topologies, respectively.

Optimal Voltage Control Strategy for Voltage Regulators in Active Unbalanced Distribution Systems Using Multi-Agents

The rapid increase in the installation of renewable energy sources, particularly solar photovoltaic (PV) sources associated with unbalanced features of distribution systems (DS), disturbs the classic control strategy of voltage regulation devices and causes voltage violation problems. This paper proposes an effective control strategy for voltage regulators in the DS based on the voltage sensitivity using a multi-agent system (MAS) architecture. The features of the unbalanced distribution system (UDS) with the PV and different types and configurations of voltage regulators are considered in the proposed strategy. The novelty of the proposed method lies in realizing both the control optimality of minimizing voltage violations and the flexibility to accommodate changes in the DS topology using an MAS scheme. An advantageous feature of using the MAS scheme is the robust control performance in normal operation and against system failure. Simulation studies have been conducted using IEEE 34-node and 123-node distribution test feeders considering high PV penetration and different sun profiles. The results show that the proposed voltage control strategy can optimally and effectively manage the voltage regulators in the UDS, which decrease their operation stresses and minimize the overall voltage deviation.

Distributed Model Predictive Control of the Multi-Agent Systems with Improving Control Performance

This paper addresses a distributed model predictive control (DMPC) scheme for multiagent systems with improving control performance. In order to penalize the deviation of the computed state trajectory from the assumed state trajectory, the deviation punishment is involved in the local cost function of each agent. The closed-loop stability is guaranteed with a large weight for deviation punishment. However, this large weight leads to much loss of control performance. Hence, the time-varying compatibility constraints of each agent are designed to balance the closed-loop stability and the control performance, so that the closed-loop stability is achieved with a small weight for the deviation punishment. A numerical example is given to illustrate the effectiveness of the proposed scheme.

Distributed model predictive control for multiagent systems with improved consistency

This paper addresses an improved distributed model predictive control (DMPC) scheme for multiagent systems with an attempt to improving its consistency. The deviation between what an agent is actually doing and what its neighbors believe that agent is doing is penalized in the cost function of each agent. At each sampling instant the compatibility constraint of each agent is set tighter than the previous sampling instant. Like the traditional approach, the performance cost is utilized as the Lyapunov function to prove closed-looped stability. The closed-loop stability is guaranteed if the weight matrix for deviation in the cost function are sufficiently large. The proposed distributed control scheme is formulated as quadratic programming with quadratic constraints. A numerical example is given to illustrate the effectiveness of the proposed scheme.

Distributed model predictive control for multi-agent systems with coupling constraints

This paper proposes an improved distributed model predictive control (DMPC) scheme for multi-agent systems with coupling constraints by applying compatibility constraint and deviation penalisation. Firstly, a sufficient condition based on the compatibility constraint to satisfying cooperative coupling constraints is given, which enables control performance and coupling constraints dependent on the compatibility constraint. Then, in order to optimise the control trajectory and to improve the consistency of the actions between agents, the deviation between what an agent is actually doing and what its neighbours believe it is doing is penalised in the cost function. At each sampling instant, the compatibility constraint of each agent is set tighter than the previous sampling instant. The optimal control problem is formulated as quadratic programming with quadratic constraints. Finally, two simulation examples are given to illustrate the effectiveness of the proposed scheme.

Diesel engine variable-geometry turbine turbocharger controlled by a multi-agent-based algorithm

This paper provides an innovative technique for the control of a variable-geometry turbine in a turbocharged compression ignition engine. Such a control algorithm is based on a multi-agent System scheme. It is seldom that agents are considered as stand-alone systems; on the contrary, their main strength can be found in the interaction with other agents, constituting the so-called multi-agent System. An agent is a software or hardware entity that can receive signals from the environment and act upon that environment through output signals, trying to carry out an appropriate task. In the present paper, a fuzzy logic system has been employed for the agents' internal structure. In order to test the performance of the proposed control technique, a numerical model of the engine has been used, which employs a thermodynamic (zero-dimensional) approach. The paper will show that the proposed control technique is able to take into account the non-linearity of the controlled system.