Eduardo Mojica-Nava

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• Ph.D.
• Professor (Full) at National University of Colombia

We illustrate the potential of applying population games in two key related problems in microgrids management: economic dispatch of active and reactive power, and demand response. For the dynamic economic dispatch problem, we present a hierarchical microgrid energy management algorithm able to dispatch active and reactive power dynamically. In the...

We present a leader-follower formation control algorithm based on replicator-mutator dynamics and complex Laplacian. The networked multi-agent system is composed by several multiple mobile autonomous agents keeping its formation. Replicator mutator dynamics are used to reach consensus of the formation, to assure a faster convergence time for a lead...

Recently, there has been an increasing interest in the control community in studying large-scale distributed systems. Several techniques have been developed to address the main challenges for these systems, such as the amount of information needed to guarantee the proper operation of the system, the economic costs associated with the required commu...

In the path to the future implementation of the smart grid, microgrids are presented as a cornerstone. An efficient and optimal microgrid operation is paramount. In this paper, we present a hierarchical microgrid management system using task sharing and an evolutionary game theory based dispatch strategy as a coordination algorithm to integrate the...

Voltage collapse is a type of failure with major influence in blackouts. Blackouts, although infrequent, are costly to society. For the Smart grid, integration of new technologies, new policies, and increasing power demand makes the power system becoming more disturbed, which increases the possibility of voltage collapses of all size. Hence, its co...

Multilayer networks provide a more advanced and comprehensive framework for modeling real-world systems compared to traditional single-layer and multiplex networks. Unlike single-layer models, multilayer networks have multiple interacting layers, each with unique topological features. In this paper, we generalize previously developed results for di...

We propose a robust adaptive online synchronization method for leader-follower networks of nonlinear heterogeneous agents with system uncertainties and input magnitude saturation. Synchronization is achieved using a Distributed input Magnitude Saturation Adaptive Control with Reinforcement Learning (DMSAC-RL), which improves the empirical performan...

Energy management systems (EMS) play a crucial role in ensuring efficient and reliable operation of networked microgrids (NMGs), which have gained significant attention as a means to integrate renewable energy resources and enhance grid resilience. This paper provides an overview of energy management systems in NMGs, encompassing various aspects in...

Multilayer networks provide a more comprehensive framework for exploring real-world and engineering systems than traditional single-layer networks consisting of multiple interacting networks. However, despite significant research on distributed optimization for single-layer networks, similar progress is lacking for multilayer systems. This paper pr...

Explore the application of Distributed Robust Optimization (DRO) in microgrids and networked microgrids with highly uncertain parameters. Microgrids are small-scale electrical systems with distributed generation, loads, and storage. Optimizing microgrid operation and design involves addressing uncertainties like power demand and renewable generatio...

This paper presents a data-driven control algorithm for voltage regulation in an MG. Using the V-Q decoupling model for microgrids, the voltage at each inverter is represented by a nonlinear equation, which depends on the inverter’s impedance and reactive power. The nonlinear model is represented as a linear one in the Koopman space or lifted space...

This work is about the absolute stability studies of closed-loop data-driven models with sector nonlinearities based on Koopman operator theory with data-dependent bounds of the estimation. This method leads to a class of stability analysis where the accuracy of the estimation depends on the non-asymptotic convergence of the error estimation based...

Motion imitation techniques offer a promising approach to the bipedal locomotion problem by leveraging human expertise. This survey provides an overview of the diverse methods employed for this task and introduces two taxonomies. The first one is based on motion transfer approaches for mapping expert motions to the learner, and the second one is ba...

The thesis introduces a comprehensive robot training framework that utilizes artificial learning techniques to optimize robot performance in complex tasks. Motivated by recent impressive achievements in machine learning, particularly in games and virtual scenarios, the project aims to explore the potential of these techniques for improving robot ca...

Intelligent transportation systems (ITSs) are at the forefront of advancements in transportation, offering enhanced efficiency, safety, and environmental friendliness. To enable ITSs, autonomous systems play a pivotal role, contributing to the development of autonomous driving, data-driven modeling, and multiagent control strategies to establish su...

Intelligent transportation systems (ITS) are at the forefront of advancements in transportation, offering enhanced efficiency, safety, and environmental friendliness. To enable ITS, autonomous systems play a pivotal role, leveraging breakthroughs in autonomous driving, data-driven modeling, and multiagent control strategies to establish sustainable...

La interacción entre los sistemas existe desde el mismo inicio de la ingeniería. Mientras que la aparición de los sistemas en red es la evolución natural de los dispositivos interconectados y sus principios fundamentales. Por otro lado, la descentralización de los sistemas de control emerge ante la necesidad de controlar elementos que pueden llegar...

Multilayer networks provide a more comprehensive framework for exploring real-world and engineering systems than traditional single-layer networks, consisting of multiple interacting networks. However, despite significant research in distributed optimization for single-layer networks, similar progress for multilayer systems is lacking. This paper p...

This paper provides the theoretical foundation for the approximation of the regions of attraction in hyperbolic and polynomial systems based on the eigenfunctions deduced from the data-driven approximation of the Koopman operator. In addition, it shows that the same method is suitable for analyzing higher-dimensional systems in which the state spac...

This paper presents a distributed data-driven control to regulate the voltage in an alternate current microgrid (MG). Following the hierarchical control frame for MGs, a secondary control for voltage is designed with a data-driven strategy using the Koopman operator. The Koopman operator approach represents the nonlinear behavior of voltage as a li...

A novel distributed real-time energy management strategy for inverter-based microgrids based on dynamic algorithms with a low computational burden and without the requirement of offline forecast or a central optimizer is presented in this paper. A dynamic economic dispatch problem is solved while a stability performance is guaranteed. The algorithm...

We consider the whole-body humanoid gait control model via reinforcement learning, where an initial predefined parametric gait policy is optimized by employing the augmented random search algorithm realizing most of the experiments in simulation and verifying the results onto the real robot. In our proposal, we take into account the reality gap pro...

This paper presents a data-driven control for a network of autonomous vehicles. The general scheme of cruise control is implemented for a set of vehicles defined by a nonlinear equation. Koopman operator allows representing the nonlinear system in the Koopman space (lifted space), suitable to get a linear observer that is used for distributed contr...

This paper considers a cooperative cruise control problem from a predictive control perspective. Online decision-making is used to be executed during the driving process based on the information obtained from the network. We formalize a synchronization problem approach from a predictive control theory using bargaining games to find an operating agr...

This paper proposes an original methodology to compute the regions of attraction in hyperbolic and polynomial nonlinear dynamical systems using the eigenfunctions of the discrete-time approximation of the Koopman operator given by the extended dynamic mode decomposition algorithm. The proposed method relies on the spectral decomposition of the Koop...

This paper presents a distributed data-driven control to regulate the voltage in an alternate current microgrid (MG). Following the hierarchical control frame for MGs, a secondary control for voltage is designed with a data-driven strategy using the Koopman operator. The Koopman operator approach represents the nonlinear behavior of voltage as a li...

This paper presents a model predictive control (MPC) designed to solve the optimal power flow (OPF) in grid-connected unbalanced microgrids. The controller considers the modeling of distributed renewable generators, storage units, unbalanced loads, voltage regulators, tap transformers and capacitor banks with tap controls. Active and reactive power...

Interconnected systems are widespread in modern technological systems. Designing a reliable control strategy requires modeling and analysis of the system, which can be a complicated, or even impossible, task in some cases. However, current technological developments in data sensing, processing, and storage make data-driven control techniques an app...

In this work, we propose a multi-agent learning framework to address the mobile sensor coverage problem in which the minimum mutual information between the agents (mobile sensors) and their environment defines the agent-strategy selection rule towards the system Nash equilibrium in a potential game setting. Initially, the agents infer the environme...

This article studies the problem of indirect adaptive state feedback control for a heterogeneous MIMO network with input and matched uncertainties. A mechanical network composed of two‐wheeled robots is proposed to validate the developed methodology. Within the network, a reference system is defined, and each robot has wireless communication betwee...

Distributed energy resources have become a key element towards a smarter grid. However, several significant challenges for real-time implementation have emerged, in particular control design and its integration with distribution systems. In this work, a fully distributed dynamic transactive control to coordinate distributed energy resources in a di...

This paper presents a data-driven control for a set of synchronous generators based on the improved swing equation model by using the Koopman operator. First, the nonlinear dynamic of the generators is represented by a linear model in lifted space using extended dynamic mode decomposition (EDMD). Then, a linear predictor is built and used for the d...

Hierarchical decision-making processes traditionally modeled as bilevel optimization problems are widespread in modern engineering and social systems. In this work, we deal with a leader with a population of followers in a hierarchical order of play. In general, this problem can be modeled as a leader–follower Stackelberg equilibrium problem using...

The growing consumption of electricity as well as the progressive development of new technologies implies that the power system is increasingly automated with the purpose of having a more efficient and economical operation. This development drives the system to a Smart Grid, a large-scale cyber-physical network covering different energy generation...

We discuss the Sherrington-Kirkpatrick mean-field version of a spin glass within the distributional zeta function method (DZFM). In the DZFM, since the dominant contribution to the average free energy is written as a series of moments of the partition function of the model, the spin-glass multivalley structure is obtained. Also, an exact expression...

Distributed energy resources are considered as a cornerstone in the path to a smarter grid. However, this evolution brings some important challenges for real-time implementation, especially those concerning control design and its integration with distribution systems. We propose a distributed transactive control algorithm based on population games...

We develop an event-triggered control strategy for a weighted-unbalanced directed homogeneous robot network to reach a dynamic consensus in this work. We present some guarantees for synchronizing a robot network when all robots have access to the reference and when a limited number of robots have access. The proposed event-triggered control can red...

We propose an online adaptive synchronization method for leader follower networks of heterogeneous agents. Synchronization is achieved using a distributed Model Reference Adaptive Control (DMRAC-RL) that enables the improved performance of Reinforcement Learning (RL)-trained policies on a reference model. The leader observes the performance of the...

We propose an online adaptive synchronization method for leader-follower networks of heterogeneous agents. Synchronization is achieved using a distributed Model Reference Adaptive Control (DMRAC-RL) that enables the improved performance of Reinforcement Learning (RL)-trained policies on a reference model. The leader observes the performance of the...

We discuss the Sherrington-Kirkpatrick mean-field version of a spin glass within the distributional zeta-function method (DZFM). In the DZFM, since the dominant contribution to the average free energy is written as a series of moments of the partition function of the model, the spin-glass multivalley structure is obtained. Also, an exact expression...

Nonlinear biochemical systems such as the anaerobic digestion process experience the problem of the multi-stability phenomena, and thus, the dynamic spectrum of the system has several undesired equilibrium states. As a result, the selection of initial conditions and operating parameters to avoid such states is of importance. In this work, we presen...

We tackle the problem of multiple quadrotors transporting a cable-suspended point-mass load. Treating the quadrotors as a virtual leader-follower algorithm, where a multi-layer graph encapsulates the communication and physical interaction. On the one hand, the communication stands for the approach of following the reference trajectory of a virtual...

The extended dynamic mode decomposition algorithm is a tool for accurately approximating the point spectrum of the Koopman operator. This algorithm provides an approximate linear expansion of non-linear discrete-time systems, which can be useful for system analysis and controller design. The accuracy of this algorithm depends heavily on the availab...

We discuss the Sherrington-Kirkpatrick mean-field version of a spin glass within the distributional zeta-function method (DZFM). In the DZFM, since the dominant contribution to the average free energy is written as a series of moments of the partition function of the model, the spin-glass multivalley structure is obtained. Also, an exact expression...

Multi-Agent Systems (MAS) have been used to solve several optimization problems in control systems. MAS allow understanding the interactions between agents and the complexity of the system, thus generating functional models that are closer to reality. However, these approaches assume that information between agents is always available, which means...

We propose a distributed victim-detection algorithm through visual information on quadrotors using convolutional neuronal networks (CNN) in a search and rescue environment. Describing the navigation algorithm, which allows quadrotors to avoid collisions. Secondly, when one quadrotor detects a possible victim, it causes its closest neighbors to disc...

This paper analyzes the stability of a direct current microgrid with a decentralized switched control using differential-algebraic equations and Lyapunov functions. The decentralized controllers regulate the voltage, achieve the power-sharing condition, and guaranty the non-Zeno condition. They also fulfill the droop-control condition for optimal p...

Currently, multi-agent mobile robotic testbeds are expensive, inaccessible, and restricted characteristics. Besides, the remotely accessible testbeds have limitations for specific tasks and limited time of implementation. For these reasons, we designed, produced, and implemented a testbed with excellent qualities for everybody. The ARGroHBotS is an...

The constant development of sensing applications using innovative and affordable measurement devices has increased the amount of data transmitted through networks, carrying in many cases, redundant information that requires more time to be analyzed or larger storage centers. This redundancy is mainly present because the network nodes do not recogni...

Adaptive synchronization protocols for heterogeneous multi-agent network are investigated. The interaction between each of the agents is carried out through a directed graph. We highlight the lack of communication between agents and the presence of uncertainties in each system among the conventional problems that can arise in cooperative networks....

This paper presents four centrality measurements applied to an alternating current (AC) microgrid (MG) modeled as a multiplex network. The MG secondary control is separated into a frequency and a power-sharing layers, each one with a different adjacency matrix. A physical layer is also considered with an admittance matrix representing the impedance...

We consider the model of cooperative learning via distributed non-Bayesian learning, where a network of agents tries to jointly agree on a hypothesis that best described a sequence of locally available observations. Building upon recently proposed weak communication network models, we propose a robust cooperative learning rule that allows asynchron...

Adaptive synchronization protocols for heterogeneous multi-agent network are investigated. The interaction between each of the agents is carried out through a directed graph. We highlight the lack of communication between agents and the presence of uncertainties in each system among the conventional problems that can arise in cooperative networks....

The proportional power sharing is essential to guarantee reliability on the operation of an islanded microgrid. However, inaccurate reactive power sharing in scenarios with line impedance mismatches, and slow transient response remains important limitations of most of the conventional power sharing controllers. In this work, a novel method for powe...

https://www.degruyter.com/view/journals/ijeeps/21/3/article-20190278.xml ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------...

The power system has gone through an evolutionary process towards a smart grid, this process is a challenge for the system operator, these challenges are related to implementation in real time, as well as problems with the control and stability of the system. We propose a distributed transactive control algorithm based on population games to dynami...

The identification of accurate models for the anaerobic digestion process is essential for the characterization of the region that guarantees the conservation of the bacteria population. Traditional techniques involve the identification of nonlinear models based on data from the system. In this paper, we introduce data-driven techniques that allow...

We propose the use of the Distributional Zeta-Function (DZF) for constructing a new set of Systemic Performance Measures (SPM). SPM have been proposed to investigate network synthesis problems such as the growing of linear consensus networks. The adoption of the DZF has shown interesting physical consequences that in the usual replica method are st...

A major concern of the power quality in distributed systems is related to the mitigation of voltage imbalances. This function can be implemented directly in the control system of the distributed generation power converters working simultaneously with the standard operation modes. This study presents a negative‐sequence voltage elimination technique...

In this work, we present a multi-agent learning model based on the maximum entropy (MAXEnt) and the rate distortion function to define, respectively, the environment of the agents and their understanding about it. The avoidance of redundant information under distortion conditions is used to define a distortion-based potential function that is minim...

In this paper, we study the vulnerability of the minimum cut-set (MCS) in power networks by assessing the effect of sequential attacks against the MCS and its corresponding effect on cascading failures triggering. Concepts of flow-networks and the DC power flow are integrated into the system model. Computational algorithms are developed to identify...

The cooperative control applied to vehicles allows the optimization of traffic on the roads. There are many aspects to consider in the case of the operation of autonomous vehicles on highways since there are different external parameters that can be involved in the analysis of a network. In this paper, we present the design and simulation of adapti...

https://ieeexplore.ieee.org/document/8943212 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ This paper aims to study the vulnerability of the network to sequential cascading failures attacks where the attack strategy integrates netwo...

This paper presents a distributed adaptive control law for large-scale systems with unknown interconnection parameters. An adaptive control law is designed to follow-up a model reference for a network through a controller that adjusts its parameters according to the dynamics of the reference, the neighborhood and the physical interconnection. This...

In cooperative systems, the presence of heterogeneous agents with input uncertainty hinders the operation of conventional control protocols. In the same way, by including unknown parameters, one of the best alternatives is to design an adaptive control protocol that adjusts the system under adverse conditions. In this work, we present a control str...

The development and the experimental validation of a novel dynamic model of an islanded three-phase Inverter-based Microgrid (IMG) is presented in this paper. The proposed model reproduces the relevant system dynamics without excessive complexity and enough accuracy. The dynamics of the IMG are captured with a compact and scalable dynamic model, co...

The modernization of the power system introduces technologies that may improve the system’s efficiency by enhancing the capabilities of users. Despite their potential benefits, such technologies can have a negative impact. This subject has widely analyzed, mostly considering for-profit electric utilities. However, the literature has a gap regarding...

The modernization of the power system introduces technologies that may improve the system's efficiency by enhancing the capabilities of users. Despite their potential benefits, such technologies can have a negative impact. This subject has widely analyzed, mostly considering for-profit electric utilities. However, the literature has a gap regarding...

Prediction of vulnerable lines during cascading failures is an important issue for power networks. The identification of key lines may enable the application of targeted countermeasures and reduce cascading failures effects. Based on topological information and line power transmission capacity, we propose the use of cut-sets (CS) to quantify the li...