Soumya Ranjan Sahoo

Rendezvous in space with minimal sensing and coarse actuation

In this paper, we propose a control law to achieve a rendezvous of autonomous vehicles moving in three-dimensional (3D) space, using minimal data sensing and quantized control. A pre-assigned graph uniquely assigns the pursuer-target pair in a cyclic manner. A quantized control law has been proposed which allows the vehicle to pitch and yaw simultaneously in the required direction and track its target agent. The only measurement required for the proposed control law is the quadrant from which the target vehicle moves out of the field-of-view of the pursuing vehicle. A Lyapunov function is chosen to find a domain for the field-of-view which guarantees rendezvous under the proposed control law. Computer simulations are presented to demonstrate the control law.

Target centric formation control with bounded input

In this paper, we present a distributive target-centric formation controller with saturated control action for multiple unmanned aerial vehicles (UAVs). The desired target-centric formation is maintained using consensus protocol. We show that if there exists at least one vehicle in the group of agents who has the complete target information and corresponding communication graph is connected, then a target-centric formation can be maintained around the around the target. A Lyapunov function is chosen to show the stability of the system under the saturated control law. The performance of the proposed controller is demonstrated by using computer simulations.

Cooperative Target-centric Formation Control without Relative Velocity Measurements under Heterogeneous Networks

This paper proposes distributed control laws for a group of unmanned aerial vehicles (UAVs) to make and maintain a circular formation around a maneuvering target. The work considers usage of heterogeneous communication networks to achieve the desired formation. Two different scenarios are considered on velocity information. In both scenarios, it is assumed that each UAV has its own position and velocity measurements available to itself. However, the team is unable to exchange velocity information among themselves. In the first scenario, each agent uses its own position and velocity information in the consensus algorithm. In the second scenario, agents need only position information for the consensus algorithm. For both the approaches, each agent calculates a virtual estimate of target’s velocity from the received information and exchanges the estimate with its neighbors. The control algorithms are developed using heterogeneous communication networks to satisfy a communication bandwidth constraint. Three different communication networks are used to circulate position information, virtual estimates, and its time derivatives. The graphs representing communication networks are undirected and connected. Further, it is considered that there is at least one UAV (agent) receiving position, velocity, and acceleration information of the target. The agent receiving target’s position need not be the same agent which receives velocity and/or acceleration information of the maneuvering target. However, the target does not receive any information from any agent. Using Barbalat’s lemma, the stability of the target-centric formation of a group of UAVs is analyzed. The performance of the proposed laws are illustrated through numerical simulations.

Trajectory tracking with input delay in multi-agent system: Double integrator case

Our objective is to design a consensus based control law for a multi-agent system to track a desired trajectory in the presence of a constant input delay. The agents of the multi-agent system are modeled as double integrator. The communication topology is represented by a fixed and weakly connected digraph. The controller works in conjugation with an estimator to help the agents track the desired trajectory. We present the design of two different estimators, each of which compensate for the delayed input. The first estimator model is designed as a double integrator. We find a condition on the estimator gain such that the controller can achieve trajectory tracking in the presence of constant input delay. The second estimator model is designed as a pair of single integrators. Here, we find conditions on the gains of the estimator model so as to achieve trajectory tracking in the presence of delay. The stability of the system is analysed using the frequency response approach. Simulation results illustrate the effectiveness of the proposed controller.

Cooperative formation control strategy in heterogeneous network with bounded acceleration

In this paper, a target-centric formation control law with acceleration bound is proposed for a group of unmanned aerial vehicles (UAVs) moving at a constant altitude. Three different communication networks are used to circulate the position, velocity, and acceleration information of the vehicles. These communication networks among agents excluding the target are represented by three different undirected and connected graphs. The position, velocity, and acceleration information of a maneuvering target are received by at least one vehicle (agent) in the system. The agent receiving the targets position needs not be the same agent which receives the velocity and/or acceleration information of the maneuvering target. The target does not receive any information from the agents. The stability of the formation of the UAVs around a maneuvering target is analyzed using Barbalats lemma. Under the proposed control law, acceleration of the agents are bounded around the acceleration of the target at every instant despite the large position and/or velocity errors. Numerical simulations are discussed to demonstrate the performance of the proposed control law.

A novel multi-agent formation control law with collision avoidance

In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed. It is assumed that the communication graph is undirected and connected. The proposed formation control law is a combination of the consensus term and the collision avoidance term U+0028 CAT U+0029. The first order consensus term is derived for the proposed model, while ensuring the Lyapunov stability. The consensus term creates and maintains the desired formation shape, while the CAT avoids the collision. During the collision avoidance, the potential function based CAT makes the agents repel from each other. This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance. Hence we have proposed a formation control law, which ensures this connectivity even during the collision avoidance. This is achieved by the proposed novel adaptive potential function. The potential function adapts itself, with the online tuning of the critical variable associated with it. The tuning has been done based on the lower bound of the critical variable, which is derived from the proposed connectivity property. The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.

Trajectory Tracking Control with Heterogeneous Input Delay in Multi-Agent System

In this paper we present a protocol to track a general trajectory for a multi-agent system in the presence of heterogeneous constant finite input delays. We consider two different multi-agent cases: agents with single-integrator and double-integrator dynamics. For the single-integrator case, we assume that the velocity along the desired trajectory is known to all agents for all time. Similar assumption is made only for the acceleration along the desired trajectory for the double-integrator case. It is assumed that at least one agent has the complete information about the desired trajectory for all time. The tracking strategy comprises of a consensus-based estimator and a simple independent tracking controller for each agent in the system. Only the state estimates are exchanged among the agents. The communication graph for the multi-agent system along with the desired trajectory has a rooted directed spanning tree with the desired trajectory being the root. The proposed tracking strategy ensures asymptotic convergence of the multi-agent system. The controller and estimator gains do not depend on the edge weights of the graph. The chosen controller gains of individual agent are bounded by their respective input delays. We present a particular form of control gains in order to achieve a desired possible exponential convergence rate and maximize the upper bound of the convergence rate for these selective gains. Finally, we present simulation results to substantiate the effectiveness of the proposed methodology. Comparison of the proposed strategy with the existing work in the literature show a better performance.

Trajectory tracking in heterogeneous multi-agent system without and with input delay

In this paper, we propose two different trajectory tracking consensus protocols for heterogeneous multi-agent system which comprises of heterogeneous agents. First, we propose a control law for achieving trajectory tracking in absence of time delay and analyze its stability using Lyapunov theory and Barbalats lemma. Second, we design a control law based on estimators for achieving trajectory tracking in presence of constant homogeneous input delay. We find conditions on the estimator gains such that the control laws can achieve trajectory tracking in the presence of the delay. The stability of the system is analyzed using the frequency response approach. The position and velocity information are exchanged by the agents over different communication networks. The communication network is heterogeneous. In addition to this, we assume that network sharing position and velocity information of desired trajectory among second-order agents are different and have a rooted directed spanning tree. Simulation results illustrate the performance of the proposed controllers.

Distributed secondary control with reduced communication in low-voltage DC microgrid

DC microgrid includes various sources and loads, interconnected to the dc system, using power electronic converters. Low voltage regulation and proportional load sharing are the important control objectives of dc microgrid. Distributed secondary controller with communication among these sources help in achieving the aforementioned control objectives. Most of the existing techniques utilize communication among all the converters. This increases communication infrastructure requirement. In this paper, a distributed control strategy based on cooperative control is proposed to attain low voltage regulation and proportional load sharing with less communication. Each source communicates only to its neighbors, thereby utilizing reduced number of communication links in the dc microgrid. The underlying communication topology is represented by a fixed, directed and balanced graph. Each source uses an average current estimator which estimates the average of per-unit currents of all the sources in the microgrid utilizing localised communication. These estimates are used by each source converter for regulating their respective voltages. The small signal model of the microgrid with the proposed control scheme is derived and discussed in this paper. Simulation results are presented which validate the performance of the microgrid with the proposed control scheme.

Target centric area coverage control using formation in a multi-agent system

In this paper, we propose a formation based area coverage algorithm for an annular region whose minimum and maximum radii are known. The agents used to cover the area are modeled as unicycles. The algorithm consists of a formation control and an area coverage algorithm. The formation control is based on a leader follower strategy where the follower tries to maintain its position with respect to its leader while moving along with the leader. Once a desired linear formation is achieved, the first agent is engaged in covering the designated area. The first agent covers the innermost area. The other agents under the leader-follower strategy follow the first agent and cover their designated areas. The results are illustrated through computer simulations.