Model Free Adaptive Control Of Multi-Agent Systems And It’s Applications To Coordinated Signal Control Of Intersections

Multi-agent systems and model free adaptive control (MFAC) scheme have been gotten more and more attentions nowadays. The former is an important branch of distributed artificial intelligence, the latter is the typical data-driven control. They all have the advantages in solving problems related to complex systems. This thesis is to combine both techniques and apply to the coordinated control of intersections. The main research contents are as follows:Firstly, the methods of multi-agent systems’ coordination matrix are built, and based on multiple-input-multiple-output discrete-time systems’model free adaptive control theory, the model free adaptive coordinated control (MFACC) scheme is designed for multi-agent systems. The simulation results show that the proposed model free adaptive coordinated control scheme can complete the control task of the Multi-agent systems’ single tracking, coordinated tracking or the combination.Secondly, for the signal coordinated control of multiple intersections, which is the main research subject of the road traffic control, the importance and feasibility of combining multi-agent systems and road traffic control are discussed. Then, according to the idea of equilibrium queue length, the traditional model free adaptive control and the proposed model free adaptive coordinated control are applied to design the intersections’ queue length balanced signal controller. The simulation results show that both schemes can achieve the target of vehicle queuing length balanced-control, and model free adaptive coordinated control not only can meet the target of queuing length balanced-control for single intersection, but also can make the equilibrium of the queuing length of the intersections, that is, multi-agent systems’ coordination.Finally, considering the mutual influence among multi-agent systems can impact the multi-agent systems’ coordination effect, taking the intersection multi-agent systems for example, aiming to improve the multi-agent systems’ model, and the improved store-and-forward modeling and the queue length model of adjacent signal intersections which is based on traffic-wave theory have been presented. Using the complex systems’ model free adaptive control scheme to compose of the systems, so that we can develop decentralized control based on decentralized estimation of multi-agent systems faced to intersections. The simulation results show that the improved multi-agent models faced to intersections are more closely with the practical traffic conditions, especially when the main road traffic density is very large, decentralized control based on decentralized estimation MFAC strategy improves balanced-control performance greatly.