Daniel Burbano

Rutgers, The State University of New Jersey | Rutgers · Department of Electrical and Computer Engineering

Animal navigation has been an invaluable source of inspiration for designing different engineering solutions ranging from optimization strategies to control solutions for complex systems. Recent results indicate that zebrafish larvae could exploit local inhomogeneities from the background flow to orient and navigate against a flowing current, a beh...

Collective behavior is ubiquitous among fish, yet, its how's and why's are yet to be completely elucidated. It is known that several environmental factors can dramatically influence collective behavior, by eliciting behavioral adaptations in the individuals and altering physical pathways of social interactions in the group. Yet, empirical research...

The emergency generated by the current COVID-19 pandemic has claimed millions of lives worldwide. There have been multiple waves across the globe that emerged as a result of new variants, due to arising from unavoidable mutations. The existing network toolbox to study epidemic spreading cannot be readily adapted to the study of multiple, coexisting...

Freshwater ecosystems are among the most biodiverse ecosystems on the planet and constitute key natural resources for human economies. These ecosystems, however, are endangered due to persistent human activities, ranging from temperature changes to water pollution. Here, we develop an online serious game to educate youth regarding human impact on f...

Shimmy is a dangerous phenomenon that occurs when aircraft's nose landing gears oscillate in a rapid and uncontrollable fashion. In this paper, we propose the use of two nonlinear control approaches (zero average control and model reference adaptive control based on minimal control synthesis) as simple yet effective strategies to suppress undesired...

Seeking to match our emotional state with one of those around us is known as emotional contagion-a fundamental biological process that underlies social behavior across several species and taxa. While emotional contagion has been traditionally considered to be a prerogative of mammals and birds, recent findings are demonstrating otherwise. Here, we...

Developing mathematical models of the feedback control process underlying animal behavior is of critical importance to understand their interactions with the environment and emotional responses. For instance, fish geotaxis (the tendency to swim at the bottom of the tank) is known to be a highly sensitive measure of anxiety, but how and why animals...

Understanding how animals navigate complex environments is a fundamental challenge in biology and a source of inspiration for the design of autonomous systems in engineering. Animal orientation and navigation is a complex process that integrates multiple senses, whose function and contribution are yet to be fully clarified. Here, we propose a data-...

A large body of work has offered compelling evidence of the influence of social context on individual decision-making, but the reasons why individuals tend to cooperate with others remain elusive. The prisoner’s dilemma constitutes a powerful, yet elementary, social game to study the drivers underlying cooperation. Here, we empirically examined a p...

Social groups such as schools of fish or flocks of birds display collective dynamics that can be modulated by group leaders, which facilitate decision-making toward a consensus state beneficial to the entire group. For instance, leaders could alert the group about attacking predators or the presence of food sources. Motivated by biological insight...

In many natural and man-made networks, nodes communicate with each other through different types of interconnection links giving rise to so-called multiplex networks. In this paper, we study the interplay between synchronous steady state solutions and the topology of multiplex networks of Chua's circuits. In particular, we consider all circuits to...

Over the last thirty years, we have witnessed a dramatic rise in the use of zebrafish in preclinical research. Every year, more than 5,000 technical papers are published about zebrafish, many of them seeking to explain the underpinnings of anxiety through animal testing. In-silico experiments could significantly contribute to zebrafish research and...

Behind any complex system in nature or engineering, there is an intricate network of interconnections that is often unknown. Using a control-theoretical approach, we study the problem of network reconstruction (NR): inferring both the network structure and the coupling weights based on measurements of each node’s activity. We derive two new methods...

In wireless sensor networks, estimating a global parameter from locally obtained measurements via local interactions is known as the distributed parameter estimation problem. Solving these problems often require the deployment of distributed optimization algorithms that rely on a constant exchange of information among the sensor nodes. This makes s...

Many natural and engineered systems can be modeled as a set of nonlinear units interacting with each other over a network of interconnections. Often such interactions occur through different types of functions giving rise to so-called multiplex networks. As an example, two masses can interact through both a spring and a damper. In many practical ap...

Shimmy is a dangerous phenomenon that occurs when aircraft’s nose landing gears oscillate in a rapid and uncontrollable fashion. In this paper, we propose the use of two nonlinear control approaches (zero average control and model reference adaptive control based on minimal control synthesis) as simple yet effective strategies to suppress undesired...

The ability of a network of nonlinear systems to synchronize onto the desired reference trajectory in the presence of one or more leader nodes is known as the pinning controllability problem. This paper studies the pinning controllability of multi-agent networks subject to three different types of noise diffusion processes; namely, noise affecting...

In this paper we study the problem of real-time topology identification of networks with diffusive couplings and unknown linear terms. Inspired by adaptive observer theory, we propose two different strategies based on full or partial measurements of each node activity. Sufficient conditions guaranteeing convergence to the precise value of coupling...

In this paper we study the pinning controllability of networks when noise affects either the node dynamics, or the communication links or the connections through which pinning control itself is being exerted. By using appropriate Lyapunov functions and the notion of almost sure exponential stability, we provide simple algebraic conditions depending...

In this paper, we address the problem of achieving synchronization in networks of nonlinear units coupled by dynamic diffusive terms. We present two types of couplings consisting of a static linear term, corresponding to the diffusive coupling, and a dynamic term which can be either the integral or the derivative of the sum of the mismatches betwee...

In this paper, we present a distributed Proportional-Integral (PI) strategy with self-tuning adaptive gains for reaching asymptotic consensus in networks of non-identical linear agents under constant disturbances. Alternative adaptive strategies are presented, based on global or local measures of the agents' disagreement. The proposed approaches ar...

In this paper, we propose a multiplex proportional–integral approach, for solving consensus problems in networks of heterogeneous nodes dynamics affected by constant disturbances. The proportional and integral actions are deployed on two different layers across the network, each with its own topology. Sufficient conditions for convergence are deriv...

A distributed proportional-integral multilayer strategy is proposed, to achieve consensus in networks of heterogeneous first-order linear systems. The closed-loop network can be seen as an instance of so-called multiplex networks currently studied in network science. The strategy is able to guarantee consensus, even in the presence of constant dist...

we propose an adaptive ramp control strategy with self-tuning offset and amplitude, as a simple yet effective solution for controlling DC-DC power converters despite load and input voltage variations. It is shown that our control technique is able to suppress chaos and sub-harmonic oscillations for a wide range of input voltage and loads. Furthermo...

We investigate the use of distributed Proportional-Integral-Derivative (PID) actions to achieve consensus and synchronization in networks of homogeneous and heterogeneous agents. We �first analyze the case of distributed PID control, on networks with heterogeneous nodes described by �first-order linear systems. Convergence of the strategy is proved...

In this chapter, a methodology to compute chaos controllers based on bifurcation diagrams is proposed and applied to PWM-controlled power converters. The technique is based on an adaptive control where the offset of the T-periodic sawtooth signal is modified. Basically, the sawtooth is redefined as a function of the output and reference voltages. T...

We investigate the use of distributed PID actions to achieve consensus in networks of homogeneous and heterogeneous linear systems. Convergence of the strategy is proved for both cases using appropriate state transformations and Lyapunov functions. The effectiveness of the theoretical results is illustrated via the representative example of a power...

In this paper we investigate the use of distributed PI actions to achieve consensus and synchronization in complex networks. We show that by extending the classical linear diffusive coupling with an integral action it is possible to achieve better performance and steady-state behavior than with more traditional strategies. After briefly summarizing...

This paper reports an extended version of GZAD technique for controlling DC-DC power converters with completely uncertain, but bounded time-varying loads. GZAD technique has been recently proposed as generalized version of Zero Average Dynamics strategy (ZAD) for controlling DC-DC buck power converter with known and fixed loads. However several app...

The quantization effect in transitions to chaos and periodic orbits is analyzed in this paper through a specific application, the zero-average-dynamics- (ZAD-) controlled buck power converter. Several papers have studied the quantization effects in the one periodic orbit and some authors have given guidelines to design digitally controlled power co...

Zero Average Dynamics (ZAD) strategy has been reported in the last decade as an alternative control technique for power converters, and a lot of work has been devoted to analyze it. From a theoretical point of view, this technique has the advantage that it guarantees fixed switching frequency, low output error and robustness, however, no high corre...

ZAD strategy has been widely analyzed in the last decade to control buck power converters. The first models were ideals; as consequence of these numerical and experimental results did not agree. The discrepancy between both of the results is probably due to the sensitivity of the ZAD strategy to compute the duty cycle. In the present work the induc...