Friday 9 November at 12:00
Lab 602, Maths & Physics Building, University of Malta Msida Campus
'Advanced nonlinear control methods for first-order freeway model' is the title of a seminar organised by the Department of Statistics & Operations Research. The seminar will be held on Friday 9 November at 12:00 in Lab 602, Maths & Physics Building, University of Malta Msida Campus.
Speaker: Dr Maria Kontorinaki
Lab 602, Maths & Physics Building, University of Malta Msida Campus
'Advanced nonlinear control methods for first-order freeway model' is the title of a seminar organised by the Department of Statistics & Operations Research. The seminar will be held on Friday 9 November at 12:00 in Lab 602, Maths & Physics Building, University of Malta Msida Campus.
Speaker: Dr Maria Kontorinaki
Abstract
The continuously increasing number of vehicles in industrial countries is a major problem, which triggers congestion phenomena having negative impacts such as increased travel times and fuel consumption as well as reduced safety. Useful tools for the investigation of the congestion problem are Traffic Flow Modeling and Traffic Control. Traffic Flow Modeling targets the accurate representation of the network and traffic flow characteristics, while Traffic Control aims at improving the traffic conditions of the network and mitigating the problem of traffic congestion.
Practical control design approaches are often based on simplified models of the system dynamics, leading to traffic systems with suboptimal performance; nevertheless, for complex control system applications, the use of more complex models is virtually unavoidable. The present work exploits recent advancements in the field of Nonlinear Systems and Control in order to provide control laws emanated from systematic and rigorous mathematical derivations, being therefore more accurate and robust with respect to potential field applications.
First, a general class of acyclic first-order traffic flow models has been developed, which can be used to represent a wide variety of traffic networks, such as freeways, interconnection of freeways, urban networks and more. The developed models are large-scale discrete space-time dynamical systems that are highly nonlinear and uncertain. The overall modeling framework is then utilised in order to develop a rigorous methodology that provides explicit feedback control laws for the robust global exponential stabilisation of any selected uncongested equilibrium point of the above networks.
The stabilisation is achieved by means of either vector or single Lyapunov Function criteria and Graph Theory tools and exploits several important properties of the network models. The achieved stabilisation is robust with respect to the overall uncertain nature of network models when congestion phenomena are present and the uncertainty stemming from the fundamental diagram selection. Potential applications of the developed control methodology include urban and peri-urban signal control, perimeter control, ramp metering and mainline metering. Finally, by exploiting tools from the Adaptive Control field, a general methodology for the development of generic adaptive control schemes has been developed, having limited requirements with respect to the knowledge of system parameters.
The application of the proposed control schemes guarantees the robust global exponential attractivity of the desired and unknown uncongested equilibrium point for the closed-loop freeway systems. The proposed adaptive control schemes are then tested with respect to their ability to be used as a real-time ramp-metering control strategy. Testing this strategy with sufficiently accurate traffic flow models, different than the ones used for its design, is deemed as an indispensable step towards potential application of the proposed methodology in the field. Appropriate realistic traffic control scenarios are constructed involving local and coordination control actions.
