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

Event-triggered robust distributed state estimation for sensor networks with state-dependent noises

This paper is concerned with the event-triggered distributed state estimation problem for a class of uncertain stochastic systems with state-dependent noises and randomly occurring uncertainties over sensor networks. An event-triggered communication scheme is proposed in order to determine whether the measurements on each sensor should be transmitted to the estimators or not. The norm-bounded uncertainty enters into the system in a random way. Through available output measurements from not only the individual sensor but also its neighbouring sensors, a sufficient condition is established for the desired distributed estimator to ensure that the estimation error dynamics are exponentially mean-square stable. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities, and then the explicit expression is given for the distributed estimator gains. Finally, a simulation example is provided to show the effectiveness of the proposed event-triggered distributed state estimation scheme.This work was supported in part by the Deanship of Scientific Research (DSR) at King Abdulaziz University of Saudi Arabia under Grant 16-135-35-HiCi, the National Natural Science Foundation of China under Grants 61374127 and 61329301, the Scientific and Technology Research Foundation of Heilongjiang Education Department of China under Grant 12541061 and 12511014, and the Alexander von Humboldt Foundation of Germany

Distributed Event-Triggered Control for Asymptotic Synchronization of Dynamical Networks

This paper studies synchronization of dynamical networks with event-based communication. Firstly, two estimators are introduced into each node, one to estimate its own state, and the other to estimate the average state of its neighbours. Then, with these two estimators, a distributed event-triggering rule (ETR) with a dwell time is designed such that the network achieves synchronization asymptotically with no Zeno behaviours. The designed ETR only depends on the information that each node can obtain, and thus can be implemented in a decentralized way.Comment: 8 pages, 2 figues, 1 tabl

On Resilient Control of Nonlinear Systems under Denial-of-Service

We analyze and design a control strategy for nonlinear systems under Denial-of-Service attacks. Based on an ISS-Lyapunov function analysis, we provide a characterization of the maximal percentage of time during which feedback information can be lost without resulting in the instability of the system. Motivated by the presence of a digital channel we consider event-based controllers for which a minimal inter-sampling time is explicitly characterized.Comment: 7 pages, 1 figur

Co-design of output feedback laws and event-triggering conditions for linear systems

We present a procedure to simultaneously design the output feedback law and the event-triggering condition to stabilize linear systems. The closed-loop system is shown to satisfy a global asymptotic stability property and the existence of a strictly positive minimum amount of time between two transmissions is guaranteed. The event-triggered controller is obtained by solving linear matrix inequalities (LMIs). We then exploit the flexibility of the method to maximize the guaranteed minimum amount of time between two transmissions. Finally, we provide a (heuristic) method to reduce the amount of transmissions, which is supported by numerical simulations