Research
Cooperative Control of Multi-agent Systems
Cooperative control of the multi-agent system (MAS) is gaining interest in the research community due to its advantageous applications over a single agent system. The problem of cooperative control has been explored to achieve rendezvous, flocking, formation, attitude synchronization, containment, and target-capturing. In a cooperative mission, agents having different sensing and processing capabilities reach an agreement by interacting with the neighbors. Cooperative algorithms may have either centralized or distributed structures to arrive at the desired objective. My research work primarily focuses on the controller design to achieve common group objectives such as target tracking, consensus, formation, and containment. The aim is to design a controller using complete or incomplete state measurements to reduce the requirement of multiple sensors.
Cooperative Localization using Multiple Unicycles
A group of UAVs is used in different civilian and defense missions, such as fire monitoring, area coverage, search and rescue, and surveillance. During these operations, UAVs need to follow or orbit a specific location or target of their interest. In the case of an unknown target or location, it is essential to localize these unknown states from different measurements. A group of UAVs carrying different sensors can efficiently obtain the information of an unknown target using cooperative localization techniques. Efficacy of localization gets enhanced if the agents form an optimal formation geometry around the target. My research focuses on designing a unified framework of cooperative localization for a group of unicycles that maximizes the information of the target.
Distributed Average Tracking (DAT)
In a DAT problem, the objective is to track the average of multiple references that are possibly time-varying. Each of these references is accessible to only one agent. DAT algorithms have been applied in different distributed estimation methods, such as fusion of multiple sensors, distributed Kalman filter, and merging of feature-based maps. Moreover, such algorithms are also used for controller design, where agents’ physical states have to follow the time-varying references to achieve distributed convex optimization, region following formation, and distributed state coordination. Since a DAT algorithm addresses the convergence of multiple time-varying references, the consensus and distributed tracking algorithms can be considered special cases. My research objective is to develop novel DAT algorithms that work under communication and sensing constraints.
Attitude Tracking of a Helicopter
UAVs have been attracting research attention from industry, government, and academics owing to their extensive applications in surveillance, search and rescue missions, damage assessment, communication relays. Many of these applications require UAVs to have vertical landing/take-off, hovering capability, large payload capacity, and high maneuverability. A small-scale helicopter satisfies all the above requirements. It can also be considered in aggressive missions and hostile environments for patrolling and counter-drone activities. A helicopter's attitude-tracking problem becomes considerably different from the problem of a rigid body attitude-tracking. Our research aims to design globally defined robust attitude tracking controller in the presence of rotor disturbances and parametric uncertainty.