Shirantha Welikala

Stevens Institute of Technology · Department of Electrical & Computer Engineering

This paper proposes a novel Non-Intrusive Load Monitoring (NILM) method which incorporates appliance usage patterns (AUPs) to improve performance of active load identification and forecasting. In the first stage, the AUPs of a given residence were learnt using a spectral decomposition based standard NILM algorithm. Then, learnt AUPs were utilized t...

This paper proposes a computationally efficient, novel and superior nonlinear controller to the existing trajectory and orientation (T&O) control problem of an omnidirectional robot (ODR). Here first, the position and orientation (pose) estimation of the robot were obtained utilizing kinematic relationships of the ODR and multi-sensor fusion technique...

In this paper trajectory and orientation control is addressed for an Omni directional robot (ODR). Here ODR is modeled in a state space representation using its dynamics and the kinematics incorporating correction for motor imbalance problem. Then for that nonlinear state space, novel tracking based state feedback linearizing strategy is introduced...

In this paper design and implementation of an accurate positioning system in indoor environments for an Omni directional Robot and a stereo vision based depth estimation system is discussed. The positioning system which is robust for wheel slip and jerky motion was implemented fusing odometry, Inertial Navigation System (INS) and magnetic compass b...

This paper considers the problem of decentralized analysis and control synthesis to verify and enforce properties like stability and dissipativity of large-scale networked systems comprised of linear subsystems interconnected in an arbitrary topology. In particular, we design systematic networked system analysis and control synthesis processes that...

Symbolic control problems aim to synthesize control policies for dynamical systems under complex temporal specifications. For such problems, Signal Temporal Logic (STL) is increasingly used as the formal specification language due to its rich expressiveness. Moreover, the degree of satisfaction of STL specifications can be evaluated using ``STL rob...

In this paper, we consider networked systems comprised of interconnected sets of linear subsystems and propose a decentralized and compositional approach to stabilize or dissipativate such linear networked systems via optimally modifying some existing interconnections and/or creating entirely new interconnections. We also extend this interconnectio...

We investigate the problem of optimally observing a finite set of targets using a mobile agent over an infinite time horizon. The agent is tasked to move in a network-constrained structure to gather information so as to minimize the worst-case uncertainty about the internal states of the targets. To do this, the agent has to decide its sequence of...

Several important problems in multi-agent systems, machine learning, data mining, scheduling and others, may be formulated as set function maximization problems subject to cardinality constraints. In such problems, the set (objective) functions of interest often have monotonicity and submodularity properties. Hence, the class of monotone submodular...

Networked systems comprised of interconnected sets of non-linear subsystems appear in many real-world scenarios such as in robotics, communication networks and biochemical processes. In this paper, we develop centralized and decentralized techniques for analyzing and synthesizing such networked systems only using dissipativity properties of individ...

We consider the problem of distributed analysis and control synthesis to verify and ensure properties like stability and dissipativity of a large-scale networked system comprised of linear subsystems interconnected in an arbitrary topology. In particular, we design systematic networked system analysis and control synthesis processes that can be exe...

We consider the problem of on-line evaluation of critical characteristic parameters such as the L_2-gain (L2G), input feedforward passivity index (IFP) and output feedback passivity index (OFP) of non-linear systems using their input-output data. Typically, having an accurate measure of such "system indices" enables the application of systematic co...

Piecewise affine (PWA) systems are widely applied in many practical cases such as the control of nonlinear systems and hybrid dynamics. However, most of the existing PWA control methods have poor scalability with respect to the number of modes and system dimensions and may not be robust to the disturbances in performance. In this paper, we present...

We investigate the problem of optimally observing a finite set of targets using a mobile agent over an infinite time horizon. The agent is tasked to move in a network-constrained structure to gather information so as to minimize the worst-case uncertainty about the internal states of the targets. To do this, the agent has to decide its sequence of...

We consider the problem of estimating the states of a distributed network of nodes (targets) through a team of cooperating agents (sensors) persistently visiting the nodes so that an overall measure of estimation error covariance evaluated over a finite period is minimized. We formulate this as a multi-agent persistent monitoring problem where the...

This paper considers the optimal multi-agent persistent monitoring problem defined for a team of agents on a set of nodes (targets) interconnected according to a fixed network topology. The aim is to control this team so as to minimize a measure of overall node state uncertainty evaluated over a finite time interval. A class of distributed threshol...

We address the multi-agent persistent monitoring problem defined on a set of nodes (targets) interconnected over a network topology. A measure of mean overall node state uncertainty evaluated over a finite period is to be minimized by controlling the motion of a cooperating team of agents. To address this problem, we propose an event-driven recedin...

This paper addresses the persistent monitoring problem defined on a network where a set of nodes (targets) needs to be monitored by a team of dynamic energy-aware agents. The objective is to control the agents' motion to jointly optimize the overall agent energy consumption and a measure of overall node state uncertainty, evaluated over a finite pe...

We address the problem of multiple local optima arising due to non-convex objective functions in cooperative multi-agent optimization problems. To escape such local optima, we propose a systematic approach based on the concept of boosting functions. The underlying idea is to temporarily transform the gradient at a local optimum into a boosted gradi...

This paper considers the multi-agent persistent monitoring problem defined on a network (graph) of nodes (targets) with uncertain states. The agent team's goal is to persistently observe the target states so that an overall measure of estimation error covariance evaluated over a finite period is minimized. Each agent's trajectory is fully defined b...

We consider the problem of determining the optimal composition of a heterogeneous multi-agent team for coverage problems by including costs associated with different agents and subject to an upper bound on the maximal allowable number of agents. We formulate a resource allocation problem without introducing additional non-convexities to the origina...

We consider the optimal multi-agent persistent monitoring problem defined on a set of nodes (targets) interconnected through a fixed graph topology. The objective is to minimize a measure of mean overall node state uncertainty evaluated over a finite time interval by controlling the motion of a team of agents. Prior work has addressed this problem...

We consider the problem of determining the optimal composition of a heterogeneous multi-agent team for coverage problems by including costs associated with different agents and subject to an upper bound on the maximal allowable number of agents. We formulate a resource allocation problem without introducing additional non-convexities to the origina...

We consider the optimal multi-agent persistent monitoring problem defined for a team of agents on a set of nodes (targets) interconnected according to a fixed graph topology. The objective is to minimize a measure of mean overall node state uncertainty evaluated over a finite time interval. In prior work, a class of distributed threshold-based para...

We consider the optimal multi-agent persistent monitoring problem defined for a team of agents traversing on a set of nodes (targets) interconnected according to a fixed graph topology. The underlying objective is to minimize a measure of mean overall node state uncertainty evaluated over a finite interval. The solution to this problem involves eac...

The existence of multiple local optima is a common scenario in many cooperative multi-agent optimization problems whenever the associated objective function is non-linear and non-convex. We address this issue by systematically altering the actual gradient components (of the objective function) with a set of appropriately chosen boosted gradient com...

This paper addresses the control of the standard twin rotor multi-input-multi-output (MIMO) control system problem. First, nonlinear dynamic model of the system was derived using basic laws of physics. While it was possible to linearize some of the plant nonlinearities, some of them were not, such as squared input. In the conventional approach, thi...

In this paper we address the pitch axis control of the standard twin rotor multi-input-multi-output (MIMO) control system problem. Dynamic model of the pitch control system is derived using basic laws of physics, which results in a nonlinear plant model. Some of the plant nonlinearities are able to linearize, while some, such as squared input, are...

This paper presents a complete real-time implementation of a Non-Intrusive Appliance Load Monitoring (NIALM) system that, is robust under residential voltage level fluctuations. Existing NIALM techniques rely on multiple measurements taken at high sampling rates, but, only have been proven in simulated environments without even considering the effe...

In most robotics and automation applications, DC motors play a pivotal role as they have proven to be one of the easiest to control. Implementing feedback helps precise control with improved noise performance and robustness against parameter variations. DC motors with feedback control can be used for position, speed, or torque used for control. For...

This paper proposes a methodology for precise localization and indoor navigation by fusing Odometric measurements, inertial navigation system (INS) together with magnetometer measurements. The Kalman filter which was used to fuse the measurements obtained by the sensors is modified to obtain precise measurements by improving the strengths of each s...