Cooperative control of a network of multi-vehicle unmanned systems

Development of unmanned systems network is currently among one of the most important areas of activity and research with implications in variety of disciplines, such as communications, controls, and multi-vehicle systems. The main motivation for this interest can be traced back to practical applications wherein direct human involvement may not be possible due to environmental hazards or the extraordinary complexity of the tasks. This thesis seeks to develop, design, and analyze techniques and solutions that would ensure and guarantee the fundamental stringent requirements that are envisaged for these dynamical networks. In this thesis, the problem of team cooperation is solved by using synthesis-based approaches. The consensus problem is defined and solved for a team of agents having a general linear dynamical model. Stability of the team is guaranteed by using modified consensus algorithms that are achieved by minimizing a set of individual cost functions. An alternative approach for obtaining an optimal consensus algorithm is obtained by invoking a state decomposition methodology and by transforming the consensus seeking problem into a stabilization problem. In another methodology, the game theory approach is used to formulate the consensus seeking problem in a "more" cooperative framework. For this purpose, a team cost function is defined and a min-max problem is solved to obtain a cooperative optimal solution. It is shown that the results obtained yield lower cost values when compared to those obtained by using the optimal control technique. In game theory and optimal control approaches that are developed based on state decomposition, linear matrix inequalities are used to impose simultaneously the decentralized nature of the problem as well as the consensus constraints on the designed controllers. Moreover, performance and stability properties of the designed cooperative team is analyzed in presence of actuator anomalies corresponding to three types of faults. Steady state behavior of the team members are analyzed under faulty scenarios. Adaptability of the team members to the above unanticipated circumstances is demonstrated and verified. Finally, the assumption of having a fixed and undirected network topology is relaxed to address and solve a more realistic and practical situation. It is shown that the stability and consensus achievement of the network with a switching structure and leader assignment can still be achieved. Moreover, by introducing additional criteria, the desirable performance specifications of the team can still be ensured and guaranteed

Reading in the Secondary School

High School Teachers and Research in Reading

Cooperative adaptive cruise control over unreliable networks: an observer-based approach to increase robustness to packet loss

International audienceCooperative Adaptive Cruise Control (CACC) is nowadays a promising technique to increase highway through-put, safety and comfort for vehicles. Enabled by wireless communication, CACC allows a platoon of vehicles to achieve better performance than Adaptive Cruise Control; however, since wireless is employed, problems related to unreliability arise. In this paper, we design a digital controller to achieve platoon stability, enhanced by an observer to increase robustness against packet losses. A preliminary set of simulation results is presented, which confirms the interest of using an observer in combination with a local and cooperative digital controller

Team Cooperation in a Network of Multi-Vehicle Unmanned Systems: Synthesis of Consensus Algorithms

Team Cooperation in a Network of Multi-Vehicle Unmanned Systems develops a framework for modeling and control of a network of multi-agent unmanned systems in a cooperative manner and with consideration of non-ideal and practical considerations. The main focus of this book is the development of “synthesis-based” algorithms rather than on conventional “analysis-based” approaches to the team cooperation, specifically the team consensus problems. The authors provide a set of modified “design-based” consensus algorithms whose optimality is verified through introduction of performance indices. This book also: Provides synthesis-based methodology for team cooperation Introduces a consensus-protocol optimized performance index  Offers comparisons for use of proper indices in measuring team performance Analyzes and predicts  performance of  previously designed consensus algorithms Analyses and predicts team behavior in the presence of non-ideal considerations such as actuator anomalies and faults as well as the evolutions in the structure of the information exchange Team Cooperation in a Network of Multi-Vehicle Unmanned Systems is an ideal book for researchers as well as graduate-level university students who desire to work in the area of networked unmanned systems

Decision making for connected and automated vehicles: a Max-Plus approach

In this paper, a method to model the decision making system of Connected and Automated Vehicles (CAVs) is discussed. The method is based on an algebra different from the conventional, the so-called Max-Plus algebra. First, a literature-review on the application of Max-Plus algebra in different sectors is presented. Then, the Max-Plus linear system theory is applied to a high-level decision making system used for the lane reduction scenario of Connected and Automated Vehicles. In the conclusion of this work, Max-Plus linear system theory has been found to be a suitable method to describe high-level decision making systems that are foreseen to be more and more deployed with the disruptive shift towards vehicle automation. In fact, the Max-Plus approach gives a quantitative description of the high-level decision maker, which could then be analyzed and controlled with mathematical tools from control system theory. These tools are similar to the methods available for continuous/discrete time linear systems in control theory

Decision making for connected and automated vehicles:a Max-Plus approach

In this paper, a method to model the decision making system of Connected and Automated Vehicles (CAVs) is discussed. The method is based on an algebra different from the conventional, the so-called Max-Plus algebra. First, a literature-review on the application of Max-Plus algebra in different sectors is presented. Then, the Max-Plus linear system theory is applied to a high-level decision making system used for the lane reduction scenario of Connected and Automated Vehicles. In the conclusion of this work, Max-Plus linear system theory has been found to be a suitable method to describe high-level decision making systems that are foreseen to be more and more deployed with the disruptive shift towards vehicle automation. In fact, the Max-Plus approach gives a quantitative description of the high-level decision maker, which could then be analyzed and controlled with mathematical tools from control system theory. These tools are similar to the methods available for continuous/discrete time linear systems in control theory

Multi-objective platoon maneuvering using artificial potential fields

\u3cp\u3eNowadays, there is an increasing societal demand for smart mobility solutions which can increase the throughput, comfort, and safety of driving on a road. As one of these solutions, vehicle following technologies like cooperative adaptive cruise control (CACC) are introduced. with the help of vehicle-to-vehicle (V2V) communication, CACC can reduce the safe minimal inter-vehicular distance. Additionally, sharing the vehicle intentions through V2V, enables multi-vehicle maneuvers to be cooperatively executable. In this paper, using the concept of artificial potential fields, a longitudinal control scheme for performing a cooperative merging maneuver will be suggested. Artificial potential fields are powerful enough for modeling and solving such a complex problem, where in addition to vehicle following other objectives such as merging should be addressed. The designed algorithms for vehicle cooperative maneuvering are verified through simulations.\u3c/p\u3