shirantha welikala | University of Peradeniya (original) (raw)

Papers by shirantha welikala

2022 American Control Conference (ACC)

Piecewise affine (PWA) systems are widely applied in many practical cases such as the control of ... more 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 a robust approximate simulation based control method for PWA systems under bounded external disturbances. First, a lower-dimensional linear system (abstraction) and an associated interface are designed to enable the output of the PWA system (concrete system) to track the output of the abstraction. Then, a Lyapunov-like simulation function is designed to show the boundedness of the output errors between the two systems. Furthermore, the results obtained for linear abstraction are extended to the case that a simpler PWA system is the abstraction. To illustrate the effectiveness of the proposed approach, simulation results are provided for two design examples.

A cooperative multi-agent system is a collection of interacting agents deployed in a mission spac... more A cooperative multi-agent system is a collection of interacting agents deployed in a mission space where each agent is allowed to control its local state so that the fleet of agents collectively optimizes a common global objective. While optimization problems associated with multi-agent systems intend to determine the fixed set of globally optimal agent states, control problems aim to obtain the set of globally optimal agent controls. Associated non-convexities in these problems result in multiple local optima. This dissertation explores systematic techniques that can be deployed to either escape or avoid poor local optima while in search of provably better (still local) optima. First, for multi-agent optimization problems with iterative gradient-based solutions, a distributed approach to escape local optima is proposed based on the concept of boosting functions. These functions temporarily transform gradient components at a local optimum into a set of boosted non-zero gradient comp...

2022 30th Mediterranean Conference on Control and Automation (MED)

This paper considers the problem of decentralized analysis and control synthesis to verify and en... more This paper considers the problem of decentralized 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 executed in a decentralized manner at the subsystem level with minimal information sharing among the subsystems. Compared to our most recent work on the same topic, we consider a substantially more generalized problem setup in this paper and develop decentralized processes to verify and ensure a broader range of networked system properties. We show that for such decentralized processes: (1) optimizing the used subsystem indexing scheme can substantially reduce the required inter-subsystem informationsharing sessions, and (2) in some network topologies, information sharing among only neighboring subsystems is sufficient (hence, distributed!). Moreover, the proposed networked system analysis and control synthesis processes are compositional/resilient to subsystem removals, which enable them to conveniently and efficiently handle situations where new subsystems are being added/removed to/from an existing network. We also provide significant insights into our decentralized approach so that it can be quickly adopted to verify and ensure properties beyond the stability and dissipativity of networked systems. En route to developing such decentralized techniques, we have also derived new centralized solutions for dissipative observer and dynamic output feedback controller design problems. Subsequently, we also specialize all the derived results for discrete-time networked systems. We conclude this paper by providing several simulation results demonstrating the proposed novel decentralized analysis and control synthesis processes and dissipativity-based results.

Applied Energy, 2017

This paper proposes a novel Non-Intrusive Load Monitoring (NILM) method for a consumer premises w... more This paper proposes a novel Non-Intrusive Load Monitoring (NILM) method for a consumer premises with a residentially installed solar plant. This method simultaneously identifies the amount of solar power influx as well as the turned ON appliances, their operating modes, and power consumption levels. Further,

Control and Intelligent Systems, 2016

Cornell University - arXiv, Mar 31, 2022

We consider the problem of on-line evaluation of critical characteristic parameters such as the L... more We consider the problem of on-line evaluation of critical characteristic parameters such as the L2-gain (L2G), input feedforward passivity index (IFP) and output feedback passivity index (OFP) of non-linear systems using their inputoutput data. Typically, having an accurate measure of such system indices enables the application of systematic control design techniques. Moreover, if such system indices can efficiently be evaluated on-line, they can be exploited to device intelligent controller reconfiguration and fault-tolerant control techniques. However, the existing estimation methods of such system indices (i.e., L2G, IFP and OFP) are predominantly offline, computationally inefficient, and require a large amount of actual or synthetically generated input-output trajectory data under some specific initial/terminal conditions. On the other hand, the existing on-line estimation methods take an averagingbased approach, which may be sub-optimal, computationally inefficient and susceptible to estimate saturation. In this paper, to overcome these challenges (in the on-line estimation of system indices), we establish and exploit several interesting theoretical results on a particular class of fractional function optimization problems. For comparison purposes, the details of an existing averaging-based approach are provided for the same on-line estimation problem. Finally, several numerical examples are discussed to demonstrate the proposed on-line estimation approach and to highlight our contributions.

We investigate the problem of optimally observing a finite set of targets using a mobile agent ov... more 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 target-visits and the corresponding dwell-times at each visited target. For a given visiting sequence, we prove that in an optimal dwelling time allocation the peak uncertainty is the same among all the targets. This allows us to formulate the optimization of dwelling times as a resource allocation problem and to solve it using a novel efficient algorithm. Next, we optimize the visiting sequence using a greedy exploration process, using heuristics inspired by others developed in the context of the traveling salesman problem. Numerical results are included to illustrate the contributions.

This paper considers the optimal multi-agent persistent monitoring problem defined for a team of ... more 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 threshold-based parametric controllers has been proposed in prior work to control agent dwell times at nodes and next-node destinations by enforcing thresholds on the respective node states. Under such a Threshold Control Policy (TCP), an on-line gradient technique was used to determine optimal threshold values. However, due to the non-convexity of the problem, this approach often leads to a poor local optima highly dependent on the initial thresholds used. To overcome this initialization challenge, we develop a computationally efficient off-line greedy technique based on the asymptotic analysis of the network system. This analysis is then used to...

This paper considers the optimal multi-agent persistent monitoring problem defined on a set of no... more This paper considers the optimal multi-agent persistent monitoring problem defined on a set of nodes (targets) interconnected according to a fixed graph topology (PMG). The objective is to minimize a measure of mean overall node state uncertainty evaluated over a finite time interval via controlling the motion of the team of agents. A class of threshold-based parametric controllers has been proposed in a prior work as a distributed on-line solution to this PMG problem. However, this approach involves a lengthy and computationally intensive parameter tuning process, which can still result in low performing solutions. Recent works have focused on appending a centralized off-line stage to the aforementioned parameter tuning process so as to improve its performance. However, this comes at the cost of sacrificing the on-line distributed nature of the original solution while also increasing the associated computational cost. Moreover, such parametric control approaches are slow to react t...

2016 11th International Conference on Industrial and Information Systems (ICIIS), 2016

A complete real-time (RT) implementation of a NonIntrusive Load Monitoring (NILM) system based on... more A complete real-time (RT) implementation of a NonIntrusive Load Monitoring (NILM) system based on uncorrelated spectral components of the active power consumption signal is presented. Unlike existing NILM techniques that rely on multiple measurements taken at high sampling rates and, yet only proven in simulated environments, this proposed RT-NILM solution yield accurate results even with a single active power measurement taken at a low sampling rate from real-time hardware. An Active Power Meter (APM) was developed and constructed, then, used with the designed MATLAB™ Graphical User Interface (GUI) to break down the acquired active power signal of an appliance into subspace components (SCs) so as to construct a unique information rich appliance signature via the Karhunen Love expansion (KLE). Using the same GUI, signatures for all possible device combinations were constructed to form the appliance signature database. Then, a separate GUI was designed to identify the turned-on appli...

2017 IEEE International Conference on Industrial and Information Systems (ICIIS), 2017

This paper addresses the control of the standard twin rotor multi-input-multi-output (MIMO) contr... more 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, this problem has been solved by linearizing the possible nonlinearities, while neglecting the others, at the cost of reduced performance. Most importantly, the latter partially linearized approach demands linearized plant model at every operating point, which makes the controller implementation complicated when considering a wide dynamic operating range. In order to overcome limitations of the partially linearized approach, we derive a nonlinear controller. In that we use the tracking error dynamics to arrive at a compromise between the tracking performances of the pitch and yaw axes control and the smoothness of the actuator input. Furthermo...

2020 59th IEEE Conference on Decision and Control (CDC), 2020

We consider the optimal multi-agent persistent monitoring problem defined on a set of nodes (targ... more We consider the optimal multi-agent persistent monitoring problem defined on a set of nodes (targets) inter-connected 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 through on-line parametric controllers and gradient-based methods, often leading to low-performing local optima or through off-line computationally intensive centralized approaches. This paper proposes a computationally efficient event-driven receding horizon control approach providing a distributed on-line gradient-free solution to the persistent monitoring problem. A novel element in the controller, which also makes it parameter-free, is that it self-optimizes the planning horizon over which control actions are sequentially taken in event-driven fashion. Numerical results show significant improvements compared to state of the art distri...

2020 American Control Conference (ACC), 2020

We address the problem of multiple local optima arising in cooperative multi-agent optimization p... more We address the problem of multiple local optima arising in cooperative multi-agent optimization problems with non-convex objective functions. We propose a systematic approach to escape these local optima using boosting functions. These functions temporarily transform a gradient at a local optimum into a "boosted" non-zero gradient. Extending a prior centralized optimization approach, we develop a distributed framework for the use of boosted gradients and show that convergence of this distributed process can be attained by employing an optimal variable step size scheme for gradient-based algorithms. Numerical examples are included to show how the performance of a class of multi-agent optimization systems can be improved.

This paper addresses the persistent monitoring problem defined on a network where a set of nodes ... more 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 period of interest. To achieve these objectives, we extend an established event-driven Receding Horizon Control (RHC) solution by adding an optimal controller to account for agent motion dynamics and associated energy consumption. The resulting RHC solution is computationally efficient, distributed and on-line. Finally, numerical results are provided highlighting improvements compared to an existing RHC solution that uses energy-agnostic first-order agents.

We consider the optimal multi-agent persistent monitoring problem defined for a team of agents tr... more 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 each agent's trajectory defined both by the sequence of nodes to be visited and the amount of time to be spent at each node. In literature, for this problem, a class of distributed threshold-based parametric controllers has been proposed where agent transitions from one node to the next are controlled via enforcing thresholds on the respective node uncertainties. Under such a policy, the behavior of the agent-target system is a hybrid dynamic system, which enables the use of Infinitesimal Perturbation Analysis (IPA) to find the optimal threshold parameters in an on-line manner using gradient descent. However, due to the non-convexity of t...

2017 Seventeenth International Conference on Advances in ICT for Emerging Regions (ICTer), 2017

This paper presents a complete real-time implementation of a Non-Intrusive Appliance Load Monitor... more 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 effect of residential voltage level fluctuations — which is a severe problem in power systems of most developing countries like Sri Lanka. In contrast, through the NIALM method proposed in this paper, accurate load monitoring results were obtained in realtime using only smart meter measurements taken at a low sampling rate from a real appliance setup under residential voltage level fluctuations. In the proposed NIALM method, initially in the learning phase, a properly constructed MATLABTM Graphical User Interface (GUI) was used to acquire signals of each appliance active power consumption and voltage levels. Then, obtained active power measure...

A Non-Intrusive Load Monitoring (NILM) method, robust even in the presence of unlearned or unknow... more A Non-Intrusive Load Monitoring (NILM) method, robust even in the presence of unlearned or unknown appliances (UUAs) is presented in this paper. In the absence of such UUAs, this NILM algorithm is capable of accurately identifying each of the turned-ON appliances as well as their energy levels. However, when there is an UUA or set of UUAs are turned-ON during a particular time window, proposed NILM method detects their presence. This enables the operator to detect presence of anomalies or unlearned appliances in a household. This quality increases the reliability of the NILM strategy and makes it more robust compared to existing NILM methods. The proposed Robust NILM strategy (RNILM) works accurately with a single active power measurement taken at a low sampling rate as low as one sample per second. Here first, a unique set of features for each appliance was extracted through decomposing their active power signal traces into uncorrelated subspace components (SCs) via a high-resoluti...

IEEE Transactions on Automatic Control