Karl H. Johansson

Karl H. Johansson
KTH Royal Institute of Technology | KTH · EECS

Ph.D.

About

1,322
Publications
212,934
Reads
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46,600
Citations
Additional affiliations
January 2010 - present
Hong Kong University of Science and Technology
January 2007 - December 2009
California Institute of Technology
January 2007 - present
University of California, Berkeley

Publications

Publications (1,322)
Article
Full-text available
This paper proposes decentralized stability conditions for multi-converter systems based on the combination of the small gain theorem and the small phase theorem. Instead of directly computing the closed-loop dynamics, e.g., eigenvalues of the state-space matrix, or using the generalized Nyquist stability criterion, the proposed stability condition...
Article
The main purpose of this article is to elaborate on the limitations of using frequency-domain passivity theories in analyzing grid-inverter interactions within the low-frequency range. It primarily covers three levels of limitations: 1) the limitations and selection criteria of two kinds of passivity index, 2) potential conflicts between different...
Article
Full-text available
In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's loca...
Preprint
Full-text available
This paper studies community detection for a nonlinear opinion dynamics model from its equilibria. It is assumed that the underlying network is generated from a stochastic block model with two communities, where agents are assigned with community labels and edges are added independently based on these labels. Agents update their opinions following...
Preprint
We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelberg game model for incomplete information and then employ a hypergame reformulation to address asymmetric cognition. With the core con...
Preprint
This paper studies the formation of final opinions for the Friedkin-Johnsen (FJ) model with a community of partially stubborn agents. The underlying network of the FJ model is symmetric and generated from a random graph model, in which each link is added independently from a Bernoulli distribution. It is shown that the final opinions of the FJ mode...
Preprint
Full-text available
We introduce a real-time identification method for discrete-time state-dependent switching systems in both the input--output and state-space domains. In particular, we design a system of adaptive algorithms running in two timescales; a stochastic approximation algorithm implements an online deterministic annealing scheme at a slow timescale and est...
Preprint
Full-text available
A differential dynamic programming (DDP)-based framework for inverse reinforcement learning (IRL) is introduced to recover the parameters in the cost function, system dynamics, and constraints from demonstrations. Different from existing work, where DDP was used for the inner forward problem with inequality constraints, our proposed framework uses...
Conference Paper
Full-text available
Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial. As charging resources are limited, waiting times for some trucks can be prolonged at certain stations. To facilitate the efficient operation of electric trucks, we propose a distributed charging coordination frame...
Preprint
Full-text available
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities. Our goal is to reduce the trucks' waiting times at the stations while minimizing individual trucks' operational...
Preprint
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities. Our goal is to reduce the trucks' waiting times at the stations while minimizing individual trucks' operational...
Preprint
Full-text available
We consider a collaborative iterative algorithm with two agents and a fusion center for estimation of a real valued function (or ``model") on the set of real numbers. While the data collected by the agents is private, in every iteration of the algorithm, the models estimated by the agents are uploaded to the fusion center, fused, and, subsequently...
Preprint
Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multi-player non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal...
Preprint
This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms require that each agent broadcasts its decision to its neighbors at each iteration. To bet...
Article
The world faces some of the greatest challenges of modern times. How we address them will have a dramatic impact on society at large for generations to come. The field of control systems pertains to specific methods and principles to control dynamic systems and produce desired outcomes despite uncertainties in the system and in the environment. The...
Article
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
Preprint
Full-text available
In this work, we propose an approach for ensuring the safety of vehicles passing through an intelligent intersection. There are many proposals for the design of intelligent intersections that introduce central decision-makers to intersections for enhancing the efficiency and safety of the vehicles. To guarantee the safety of such designs, we develo...
Article
Full-text available
In this paper, we propose reachability analysis using constrained polynomial logical zonotopes. We perform reachability analysis to compute the set of states that could be reached. To do this, we utilize a recently introduced set representation called polynomial logical zonotopes for performing computationally efficient and exact reachability analy...
Article
Full-text available
We propose two distributed iterative algorithms that can be used to solve the distributed optimization problem for quadratic local cost functions over large-scale networks in finite time. The first algorithm exhibits synchronous operation whereas the second one exhibits asynchronous operation. Both algorithms operate exclusively with quantized valu...
Article
Signal temporal logic (STL) formulas have been widely used as a formal language to express complex robotic specifications, thanks to their rich expressiveness and explicit time semantics. Existing approaches for STL control synthesis suffer from limited scalability with respect to the task complexity and lack of robustness against the uncertainty,...
Conference Paper
Full-text available
A logical zonotope, which is a new set representation for binary vectors, is introduced in this paper. A logical zonotope is constructed by XORing a binary vector with a combination of other binary vectors called generators. Such a zonotope can represent up to 2^γ binary vectors using only γ generators. It is shown that logical operations over sets...
Article
Full-text available
Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dis...
Preprint
Full-text available
Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial. As charging resources are limited, waiting times for some trucks can be prolonged at certain stations. To facilitate the efficient operation of electric trucks, we propose a distributed charging coordination frame...
Article
Performance of control systems interacting over a shared communication network is tightly coupled with how the network provides services and distributes resources. Novel networking technology such as 5G is capable of providing tailored services for a variety of network demands. Stringent control requirements and their critical performance specifica...
Article
In the first part of this two-letter series, we proposed a cross-layer framework for joint optimal Quality-of-Control (QoC) and Quality-of-Service (QoS) co-design for networked control systems. In this second part, we employ this framework to perform optimal co-design for networked control systems comprising multiple Gauss-Markov systems. We analyt...
Article
Full-text available
This paper proposes a distributed design method of controllers with a glocal (global/local) information structure for large-scale network systems. The glocal controller of interest has a hierarchical structure, wherein a global subcontroller coordinates a set of disjoint local subcontrollers. The global subcontroller regulates inter-area oscillatio...
Preprint
Full-text available
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a sol...
Preprint
Full-text available
In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers f...
Chapter
This paper empirically evaluates two intrinsic Explainable Reinforcement Learning (XRL) algorithms on the Remote Electrical Tilt (RET) optimization problem. In RET optimization, where the electrical downtilt of the antennas in a cellular network is controlled to optimize coverage and capacity, explanations are necessary to understand the reasons be...
Preprint
Full-text available
This paper proposes decentralized stability conditions for multi-converter systems based on the combination of the small gain theorem and the small phase theorem. Instead of directly computing the closed-loop dynamics, e.g., eigenvalues of the state-space matrix, or using the generalized Nyquist stability criterion, the proposed stability condition...
Preprint
Full-text available
When a strategic adversary can attack multiple sensors of a system and freely choose a different set of sensors at different times, how can we ensure that the state estimate remains uncorrupted by the attacker? The existing literature addressing this problem mandates that the adversary can only corrupt less than half of the total number of sensors....
Preprint
Full-text available
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a sol...
Preprint
Full-text available
In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers f...
Preprint
This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents' historical actions and choose actions that best respond to other agents' previous actions; we call this a best response scheme. We start by analyzing the conv...
Preprint
The recent deployment of multi-agent systems in a wide range of scenarios has enabled the solution of learning problems in a distributed fashion. In this context, agents are tasked with collecting local data and then cooperatively train a model, without directly sharing the data. While distributed learning offers the advantage of preserving agents'...
Chapter
The emerging commercial rollout of heavy-duty vehicle platooning necessitates the development of efficient platoon coordination solutions. The commercial vehicle fleet consists of vehicles owned by different transportation companies with different objectives. To capture their strategic behavior, we study platoon coordination that aims to maximize p...
Preprint
Full-text available
In this paper, we present a data-driven approach for safely predicting the future state sets of pedestrians. Previous approaches to predicting the future state sets of pedestrians either do not provide safety guarantees or are overly conservative. Moreover, an additional challenge is the selection or identification of a model that sufficiently capt...
Preprint
Full-text available
Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dis...
Presentation
Full-text available
In this presentation, we focus on the unconstrained distributed optimization problem, where information exchange in the network is modeled using a directed graph topology, limiting communication between nodes to their neighbors. Additionally, due to limited bandwidth in the communication channels, quantized messages are used to alleviate this const...
Preprint
This paper considers online convex games involving multiple agents that aim to minimize their own cost functions using locally available feedback. A common assumption in the study of such games is that the agents are symmetric, meaning that they have access to the same type of information or feedback. Here we lift this assumption, which is often vi...
Preprint
Full-text available
Window-opening and window-closing behaviors play an important role in indoor environmental conditions and therefore have an impact on building energy efficiency. On the other hand, the same environmental conditions drive occupants to interact with windows. Understanding this mutual relationship of interaction between occupants and the residential b...
Preprint
In this paper we consider online distributed learning problems. Online distributed learning refers to the process of training learning models on distributed data sources. In our setting a set of agents need to cooperatively train a learning model from streaming data. Differently from federated learning, the proposed approach does not rely on a cent...
Article
We consider the multiobjective optimization problem for the resource allocation of the multiagent network, where each agent contains multiple conflicting local objective functions. The goal is to find compromise solutions minimizing all local objective functions subject to resource constraints as much as possible, i.e., the Pareto optimums. To this...
Preprint
Full-text available
We study joint learning of network topology and a mixed opinion dynamics, in which agents may have different update rules. Such a model captures the diversity of real individual interactions. We propose a learning algorithm based on multi-armed bandit algorithms to address the problem. The goal of the algorithm is to find each agent's update rule f...
Preprint
Full-text available
In this paper, we introduce a set representation called polynomial logical zonotopes for performing exact and computationally efficient reachability analysis on logical systems. Polynomial logical zonotopes are a generalization of logical zonotopes, which are able to represent up to 2^n binary vectors using only n generators. Due to their construct...
Presentation
Full-text available
Presentation for ECC 2023 for the paper: ''Distributed Computation of Exact Average Degree and Network Size in Finite Time under Quantized Communication''
Article
Full-text available
This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, wh...
Article
Full-text available
Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging...