Intelligent Design for Real Time Networked Multi-Agent Systems

Past decade has witnessed an unprecedented growth in reasearch for Unmanned Aerial Vehicles (UAVs) both in military and nonmilitary fronts. They have become ubiquitous in almost every military operations which includes domestic and overseas missions. With rapidly advancing technology, open source nature of the flight controllers, and significantly lesser costs than before, companies around the world are delving into UAV market as one of the upcoming lucrative investments. Companies like Amazon Inc., Dominos Pizza Inc. have had some successful test runs which again solidifies the research opportunities. Delivery services and recreational uses seems to have increased in the past 3-4 years which has let the Federal Aviation Administration to update their rules and regulations. Mapping, Surveying and search/rescue mission are some of the applications of UAVs that are most appealing. Making these applications airborne cuts the time and cost at considerable and affordable levels. Using UAVs for operations has advantages in both response time and need of manpower compared to piloted aricrafts. Obtaining prior information of a person/people in distress can become a deciding factor for a successful mission. It can help in making critical decision as which location or type of helicopter / vehicle to be used for extraction, equipment to bring and how many crew members that are needed. The idea here is to make this system of UAVs automated to coordinate with each other without human intervention (other than high level commands like takeoff and land). Researchers and Military experts have recognized the use of drones for search and rescue missions to be of utmost importance. Year 2016 saw a first of its kind UAV search and rescue symposium held in Nevada. The objective was to give a platform for UAV enthusiasts and researchers and share their experiences and concerns while using UAVs as first responders. The biggest drawback of using an aerial vehicle for inspection/search/rescue mission is its airborne time. The batteries used are big and heavy which increases the weight and decreases the flight time. One can go about solving this issue by using a swarm of UAVs which would inspect/search a given area in less amount of time. This has advantage in both response time and need for lesser man power.The main challenges for Multiple Drone Control (MDC) includes 1) Address the periodic sampling frequency issue of information of assets so as to maintain stability; 2) Optimize the communication channel while providing minimum Quality of Service (QoS); 3) Optimal control strategy which includes non-linearity in state space model; 4) Optimal control in presence of uncertainties; 5) Admitting new agents for dynamic agents in the Networked Multi-Agent System (MAS) Scenario.This dissertation aims at building a hardware and a software platform for communication of multiple UAVs upon which additional control algorithms can be implementated. It starts with building a DJI S1000 octacopter from the ground up. The components used are specified in the following sections. The idea here is to make a drone that can autonomously travel to specified location with safety features like geofencing and land on emergency situations. The user has to provide the necessary commands like GPS locations and takeoff/land commands via a Radio Controller (RC) remote. At any point of the flight, the UAV should be able to receive new commands from the ground control stations (GCS). After successful implementation, the UAV would not be restricted to the range of RC remote. It would be able to travel greater distances given the GPS signal remains operational in the field. This is possible at a global scale with limitation of only the batteries and flight time

Resilient Autonomous Control of Distributed Multi-agent Systems in Contested Environments

An autonomous and resilient controller is proposed for leader-follower multi-agent systems under uncertainties and cyber-physical attacks. The leader is assumed non-autonomous with a nonzero control input, which allows changing the team behavior or mission in response to environmental changes. A resilient learning-based control protocol is presented to find optimal solutions to the synchronization problem in the presence of attacks and system dynamic uncertainties. An observer-based distributed H_infinity controller is first designed to prevent propagating the effects of attacks on sensors and actuators throughout the network, as well as to attenuate the effect of these attacks on the compromised agent itself. Non-homogeneous game algebraic Riccati equations are derived to solve the H_infinity optimal synchronization problem and off-policy reinforcement learning is utilized to learn their solution without requiring any knowledge of the agent's dynamics. A trust-confidence based distributed control protocol is then proposed to mitigate attacks that hijack the entire node and attacks on communication links. A confidence value is defined for each agent based solely on its local evidence. The proposed resilient reinforcement learning algorithm employs the confidence value of each agent to indicate the trustworthiness of its own information and broadcast it to its neighbors to put weights on the data they receive from it during and after learning. If the confidence value of an agent is low, it employs a trust mechanism to identify compromised agents and remove the data it receives from them from the learning process. Simulation results are provided to show the effectiveness of the proposed approach

Cooperative Strategies for Management of Power Quality Problems in Voltage-Source Converter-based Microgrids

The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by emerging wireless communications technology, machine learning techniques, and power electronics. While some possible applications of the cooperative control theory to microgrids have been described in the research literature, a comprehensive survey of this approach with respect to its limitations and wide-ranging potential applications has not yet been provided. In this regard, an important area of research into microgrids is developing intelligent cooperative operating strategies within and between microgrids which implement and allocate tasks at the local level, and do not rely on centralized command and control structures. Multi-agent techniques are one focus of this research, but have not been applied to the full range of power quality problems in microgrids. The ability for microgrid control systems to manage harmonics, unbalance, flicker, and black start capability are some examples of applications yet to be fully exploited. During islanded operation, the normal buffer against disturbances and power imbalances provided by the main grid coupling is removed, this together with the reduced inertia of the microgrid (MG), makes power quality (PQ) management a critical control function. This research will investigate new cooperative control techniques for solving power quality problems in voltage source converter (VSC)-based AC microgrids. A set of specific power quality problems have been selected for the application focus, based on a survey of relevant published literature, international standards, and electricity utility regulations. The control problems which will be addressed are voltage regulation, unbalance load sharing, and flicker mitigation. The thesis introduces novel approaches based on multi-agent consensus problems and differential games. It was decided to exclude the management of harmonics, which is a more challenging issue, and is the focus of future research. Rather than using model-based engineering design for optimization of controller parameters, the thesis describes a novel technique for controller synthesis using off-policy reinforcement learning. The thesis also addresses the topic of communication and control system co-design. In this regard, stability of secondary voltage control considering communication time-delays will be addressed, while a performance-oriented approach to rate allocation using a novel solution method is described based on convex optimization