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        <title>Frontiers in Control Engineering | Networked Control section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/control-engineering/sections/networked-control</link>
        <description>RSS Feed for Networked Control section in the Frontiers in Control Engineering journal | New and Recent Articles</description>
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        <pubDate>2026-04-21T00:12:32.39+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1380005</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1380005</link>
        <title><![CDATA[Editorial: Cooperative control and team behaviors in adversarial environments]]></title>
        <pubdate>2024-02-21T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Daigo Shishika</author><author>Michael Dorothy</author><author>Douglas G. Macharet</author><author>Jason R. Marden</author><author>Panagiotis Tsiotras</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1279454</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1279454</link>
        <title><![CDATA[Teaming behavior in adversarial scenarios]]></title>
        <pubdate>2023-11-02T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Daigo Shishika</author><author>Michael Dorothy</author><author>Douglas G. Macharet</author>
        <description><![CDATA[Interesting and effective team behaviors arise when a group of agents contend with adversaries. Examples range from animal group behaviors observed in nature to strategies used in team sports. This mini review goes over literature in multiagent systems that study group control in adversarial scenarios. We identify different ways of formulating adversaries and discuss various types of teaming behavior that arise. Specifically from the perspective of multiagent task assignment, the types of tasks and the nature of assignments brought by the adversary are categorized. The frontiers of the current literature and the direction for future research are discussed at the end.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1188846</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1188846</link>
        <title><![CDATA[Editorial: Model-based methods for human–machine cooperative and shared control systems]]></title>
        <pubdate>2023-04-11T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Jairo Inga</author><author>Simon Rothfuß</author><author>Yuichi Saito</author><author>Chouki Sentouh</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.989232</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.989232</link>
        <title><![CDATA[Communication-free shepherding navigation with multiple steering agents]]></title>
        <pubdate>2023-03-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aiyi Li</author><author>Masaki Ogura</author><author>Naoki Wakamiya</author>
        <description><![CDATA[Flocking guidance addresses a challenging problem considering the navigation and control of a group of passive agents. To solve this problem, shepherding offers a bio-inspired technique for navigating such a group of agents using external steering agents with appropriately designed movement law. Although most shepherding research is mainly based on the availability of centralized instructions, these assumptions are not realistic enough to solve some emerging application problems. Therefore, this paper presents a decentralized shepherding method where each steering agent makes movements based on its own observation without any inter-agent communication. Our numerical simulations confirm the effectiveness of the proposed method by showing its high success rate and low costs in various placement patterns. These advantages particularly improve with the increase in the number of steering agents. We also confirm the robustness and resilience properties of the proposed method via numerical simulations.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1128597</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1128597</link>
        <title><![CDATA[Competitive perimeter defense with a turret and a mobile vehicle]]></title>
        <pubdate>2023-02-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shivam Bajaj</author><author>Shaunak D. Bopardikar</author><author>Alexander Von Moll</author><author>Eric Torng</author><author>David W. Casbeer</author>
        <description><![CDATA[We consider perimeter defense problem in a planar conical environment with two cooperative heterogeneous defenders, i.e., a turret and a mobile vehicle, that seek to defend a concentric perimeter against mobile intruders. Arbitrary numbers of intruders are released at the circumference of the environment at arbitrary time instants and locations. Upon release, they move radially inwards with fixed speed towards the perimeter. The defenders are heterogeneous in terms of their motion and capture capabilities. Specifically, the turret has a finite engagement range and can only turn (clockwise or anti-clockwise) in the environment with fixed angular rate whereas, the vehicle has a finite capture radius and can move in any direction with unit speed. We present a competitive analysis approach to this perimeter defense problem by measuring the performance of multiple cooperative online algorithms for the defenders against arbitrary inputs, relative to an optimal offline algorithm that has information about the entire input sequence in advance. Specifically, we establish necessary conditions on the parameter space to guarantee finite competitiveness of any online algorithm. We then design and analyze four cooperative online algorithms and characterize parameter regimes in which they have finite competitive ratios. In particular, our first two algorithms are 1-competitive in specific parameter regimes, our third algorithm exhibits different competitive ratios in different regimes of problem parameters, and our fourth algorithm is 1.5-competitive in specific parameter regimes. Finally, we provide multiple numerical plots in the parameter space to reveal additional insights into the relative performance of our algorithms.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1058802</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1058802</link>
        <title><![CDATA[Model-based shared control approach for a power wheelchair driving assistance system using a force feedback joystick]]></title>
        <pubdate>2023-02-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Viet Thuan Nguyen</author><author>Chouki Sentouh</author><author>Philippe Pudlo</author><author>Jean-Christophe Popieul</author>
        <description><![CDATA[This paper presents a haptic-based assistance system (AS) for power wheelchair users designed using the model-based shared control approach. The idea is to combine robust control with a high-level driving supervisor in order to successfully share control authority between the wheelchair user and the assistance system. This shared control strategy is composed of two parts, namely an operational part and a tactical part. Through the haptic joystick interface, this assistance system aims to reduce user’s effort when manipulating the joystick, guide the user to avoid any potential collisions, and maintain the active participation of the user in driving the wheelchair. In the operational part, an optimal Takagi-Sugeno fuzzy control approach is proposed to deal with the time-varying user’s intention represented by his desired longitudinal and angular position errors and velocities and hand torques. The control design is formulated as an LMI optimization problem which can be easily solved with numerical solvers. Two unknown input observers for Takagi-Sugeno fuzzy model have been designed to estimate the user’s intention in order to generate an assistance torque via a haptic force feedback joystick. The control supervisor in the tactical part, aims to provide a decision-making signal which allows for the conflict management based on the user hand torque estimation. A specific algorithm has been developed to solve the conflict between the user’s desired actions and the suggestions from the assistance system to ensure the user remains the final decision-maker. Experimental results show the effectiveness and the validity of the proposed assistance system.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1058923</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1058923</link>
        <title><![CDATA[A review of shared control in automated vehicles: System evaluation]]></title>
        <pubdate>2023-02-03T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Joseba Sarabia</author><author>Mauricio Marcano</author><author>Joshué Pérez</author><author>Asier Zubizarreta</author><author>Sergio Diaz</author>
        <description><![CDATA[Shared control has gained considerable attention in the automated vehicle field in recent years, both from a theoretical point of view and also with multiple applications. The development of shared control systems was discussed in a previous review, which presented a taxonomy focused on control algorithms. However, it is still necessary to understand how these systems should be assessed in terms of system performance, driver behavior, cooperation, and road safety. This paper aims to review and classify evaluation methods used in recent studies with real drivers. Results of the present review showed that shared control continues to be of interest to researchers of automated vehicles. The methodology for system evaluation has evolved, with more participants, better testing platforms, and a greater number of comparison baselines. To guide the path toward implementing shared control features in commercial vehicles, this review aims to help researchers to perform relevant evaluation studies in future developments.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1104745</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1104745</link>
        <title><![CDATA[Graph neural networks for decentralized multi-agent perimeter defense]]></title>
        <pubdate>2023-01-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Elijah S. Lee</author><author>Lifeng Zhou</author><author>Alejandro Ribeiro</author><author>Vijay Kumar</author>
        <description><![CDATA[In this work, we study the problem of decentralized multi-agent perimeter defense that asks for computing actions for defenders with local perceptions and communications to maximize the capture of intruders. One major challenge for practical implementations is to make perimeter defense strategies scalable for large-scale problem instances. To this end, we leverage graph neural networks (GNNs) to develop an imitation learning framework that learns a mapping from defenders’ local perceptions and their communication graph to their actions. The proposed GNN-based learning network is trained by imitating a centralized expert algorithm such that the learned actions are close to that generated by the expert algorithm. We demonstrate that our proposed network performs closer to the expert algorithm and is superior to other baseline algorithms by capturing more intruders. Our GNN-based network is trained at a small scale and can be generalized to large-scale cases. We run perimeter defense games in scenarios with different team sizes and configurations to demonstrate the performance of the learned network.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1093186</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1093186</link>
        <title><![CDATA[Multiplayer reach-avoid differential games with simple motions: A review]]></title>
        <pubdate>2023-01-10T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Rui Yan</author><author>Ruiliang Deng</author><author>Xiaoming Duan</author><author>Zongying Shi</author><author>Yisheng Zhong</author>
        <description><![CDATA[This paper reviews the recent works on multiplayer reach-avoid (M-RA) differential games between two adversarial teams in a game region which is split into a goal region and a play region. The pursuit team aims to protect the goal region from the evasion team by cooperatively capturing the evaders which start from the play region and strive to enter the goal region. We provide a selective overview of algorithms and theoretical results for multiplayer reach-avoid differential games. Specifically, we focus on point mass holonomic players that can move freely in the game region and have simple motions as Rufus Isaacs states. We describe how the challenges due to high-dimensional continuous joint action and state spaces, as well as complex cooperations and competitions among players, can be properly resolved by a combination of qualitative and quantitative analysis of small-scale games and optimal task allocation. We finally point out the limitations of the current works and identify fruitful future research directions on theoretical studies of multiplayer reach-avoid differential games.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1056937</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1056937</link>
        <title><![CDATA[Cooperative path-following control of a remotely operated underwater vehicle for human visual inspection task]]></title>
        <pubdate>2022-12-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Eito Sato</author><author>Hailong Liu</author><author>Yasuaki Orita</author><author>Norimitsu Sakagami</author><author>Takahiro Wada</author>
        <description><![CDATA[In recent years, significant attention has been paid to remotely operated underwater vehicles (ROVs) in the performance of underwater tasks, such as the inspection and maintenance of the underwater infrastructure. The workload of ROV operators tends to be high, even for the skilled operators. Therefore, assistance methods for the operators are desired. This study focuses on a task in which a human operator controls an underwater robot to follow a certain path while visually inspecting objects in the vicinity of the path. In such a task, it is desirable to achieve the speed of trajectory control manually because the visual inspection is performed by a human operator. However, to allocate resources to visual inspection, it is desirable to minimize the workload on the path-following by assisting with the automatic control. Therefore, the objective of this study is to develop a cooperative path-following control method that achieves the above-mentioned task by expanding a robust path-following control law of non-holonomic wheeled vehicles. To simplify this problem, we considered a path-following and visual objects recognition task in a two-dimensional plane. We conducted an experiment with participants (n = 16) who completed the task using the proposed method and manual control. We compared results in terms of object recognition success rate, tracking error, completion time, attention distribution, and workload. The results showed that both the path-following errors and workload of the participants were significantly smaller with the proposed method than with manual control. In addition, subjective responses demonstrated that operator attention tended to be allocated to object recognition rather than robot operation tasks with the proposed method. These results demonstrate the effectiveness of the proposed cooperative path-following control method.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1046764</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1046764</link>
        <title><![CDATA[Brain modeling for control: A review]]></title>
        <pubdate>2022-12-02T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Gagan Acharya</author><author>Sebastian F. Ruf</author><author>Erfan Nozari</author>
        <description><![CDATA[Neurostimulation technologies have seen a recent surge in interest from the neuroscience and controls communities alike due to their proven potential to treat conditions such as epilepsy, Parkinson’s Disease, and depression. The provided stimulation can be of different types, such as electric, magnetic, and optogenetic, and is generally applied to a specific region of the brain in order to drive the local and/or global neural dynamics to a desired state of (in)activity. For most neurostimulation techniques, however, an underlying theoretical understanding of their efficacy is still lacking. From a control-theoretic perspective, it is important to understand how each stimulus modality interacts with the inherent complex network dynamics of the brain in order to assess the controllability of the system and develop neurophysiologically relevant computational models that can be used to design the stimulation profile systematically and in closed loop. In this paper, we review the computational modeling studies of 1) deep brain stimulation, 2) transcranial magnetic stimulation, 3) direct current stimulation, 4) transcranial electrical stimulation, and 5) optogenetics as five of the most popular and commonly used neurostimulation technologies in research and clinical settings. For each technology, we split the reviewed studies into 1) theory-driven biophysical models capturing the low-level physics of the interactions between the stimulation source and neuronal tissue, 2) data-driven stimulus-response models which capture the end-to-end effects of stimulation on various biomarkers of interest, and 3) data-driven dynamical system models that extract the precise dynamics of the brain’s response to neurostimulation from neural data. While our focus is particularly on the latter category due to their greater utility in control design, we review key works in the former two categories as the basis and context in which dynamical system models have been and will be developed. In all cases, we highlight the strength and weaknesses of the reviewed works and conclude the review with discussions on outstanding challenges and critical avenues for future work.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1058980</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1058980</link>
        <title><![CDATA[Negotiation-based cooperative planning of local trajectories]]></title>
        <pubdate>2022-11-29T00:00:00Z</pubdate>
        <category>Technology Report</category>
        <author>Julian Schneider</author><author>Simon Rothfuß</author><author>Sören Hohmann</author>
        <description><![CDATA[In this work, a cooperative local trajectory planner based on negotiation theory for human‐robot interaction is developed. It is implemented on a robot, which accompanies patients to examination rooms as part of the HoLLiECares project. For this purpose, an existing human–machine cooperation model for decision-making in one-time conflict cases is applied to a time-repeated negotiation of motion primitives. In negotiation theory, time pressure in the form of deadlines is classically used to achieve agreements. Since deadlines do not naturally exist in all technical applications and their artificial insertion would create an unintuitive system behavior for an involved human, a reciprocal tit-for-tat strategy for the automation is applied in the present work to achieve agreements. This leads to a system behavior that is able to dynamically change between human-in-the-lead behavior or automation-in-the-lead behavior and everything in between depending on the concession of the human and thus on human’s desire. The cooperative negotiation-based local trajectory planner is tested simulatively.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.1055915</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.1055915</link>
        <title><![CDATA[Online driver model parameter identification using the Lyapunov approach based shared control]]></title>
        <pubdate>2022-11-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mohamed Radjeb Oudainia</author><author>Chouki Sentouh</author><author>Anh-Tu Nguyen</author><author>Jean-Christophe Popieul</author>
        <description><![CDATA[The work described in this paper proposes a new conflict minimisation strategy in shared driving control for lane keeping systems (LKS) in intelligent vehicles. This strategy takes into account a dynamic driver model, where the driver’s parameters are identified online using the Lyapunov approach. The design of an adaptive shared controller is based on the dynamic parameters of the driver model which changes according to the driver and the situation encountered. Based on Lyapunov stability arguments, the overall asymptotic stability of the closed-loop control system with the adaptive driver model and the variation of the vehicle speed is proved and an LMI optimization is used to formulate the control design. The simulation results, conducted with the SHERPA dynamic car simulator under real-world driving situations, show the importance of integrating a dynamic driver model in the controller design in order to decrease the conflict between the driver and the lane keeping system and to ensure the safety of the vehicle as well as to increase the confidence and acceptability of the driver.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2021.797362</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2021.797362</link>
        <title><![CDATA[Distributed Control of Discrete-Time Linear Multi-Agent Systems With Optimal Energy Performance]]></title>
        <pubdate>2022-04-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Guan Huang</author><author>Zhuo Zhang</author><author>Weisheng Yan</author>
        <description><![CDATA[This paper investigates the leader-based distributed optimal control problem of discrete-time linear multi-agent systems (MASs) on directed communication topologies. In particular, the communication topology under consideration consists of only one directed spanning tree. A distributed consensus control protocol depending on the information between agents and their neighbors is designed to guarantee the consensus of MASs. In addition, the optimization of energy cost performance can be obtained using the proposed protocol. Subsequently, a numerical example is provided to demonstrate the effectiveness of the presented protocol.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.861055</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.861055</link>
        <title><![CDATA[Power Allocation for Remote Estimation Over Known and Unknown Gilbert-Elliott Channels]]></title>
        <pubdate>2022-04-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tahmoores Farjam</author><author>Themistoklis Charalambous</author>
        <description><![CDATA[In this paper, we consider the problem of power scheduling of a sensor that transmits over a (possibly) unknown Gilbert-Elliott (GE) channel for remote state estimation. The sensor supports two power modes, namely low power, and high power. The scheduling policy determines when to use low power or high power for data transmission over a fading channel with temporal correlation while satisfying the energy constraints. Although error-free acknowledgement/negative-acknowledgement (ACK/NACK) signals are provided by the remote estimator, they only provide meaningful information about the underlying channel state when low power is utilized. This leads to a partially observable Markov decision process (POMDP) problem and we derive conditions that preserve the optimality of a stationary schedule derived for its fully observable counterpart. However, implementing this schedule requires knowledge of the parameters of the GE model which are not available in practice. To address this, we adopt a Bayesian framework to learn these parameters online and propose an algorithm that is shown to satisfy the energy constraint while achieving near-optimal performance via simulation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.806558</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.806558</link>
        <title><![CDATA[Signal-to-Noise Ratio Based Fault Detection and Identification]]></title>
        <pubdate>2022-03-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Alejandro J. Rojas</author><author>Hugo O. Garcés</author>
        <description><![CDATA[In this work, we introduce signal-to-noise ratio (SNR) based fault detection and identification mechanisms for a networked control system feedback loop, where the network component is represented by an additive white noise (AWN) channel. The SNR approach is known to be a steady-state analysis and design tool, thus we first introduce a finite time approximation for the estimated AWN channel SNR. We then consider the case of a general linear time-invariant plant model with one unstable pole. The potential faults that we discuss here cover simultaneously the plant model gain and/or the unstable pole. The fault detection is performed relative to the estimated AWN channel SNR. The fault identification is performed using recursive least squares ideas and then further validated with the observed SNR value, when a fault has been previously detected. We show that the proposed SNR-based fault mechanism (fault detection plus fault identification) is capable of processing the proposed faults. We conclude discussing future research based on the contributions exposed in the present work.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.836720</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.836720</link>
        <title><![CDATA[Aerial Survey Robotics in Extreme Environments: Mapping Volcanic CO2 Emissions With Flocking UAVs]]></title>
        <pubdate>2022-03-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>John Ericksen</author><author>G. Matthew Fricke</author><author>Scott Nowicki</author><author>Tobias P. Fischer</author><author>Julie C. Hayes</author><author>Karissa Rosenberger</author><author>Samantha R. Wolf</author><author>Rafael Fierro</author><author>Melanie E. Moses</author>
        <description><![CDATA[We present methods for autonomous collaborative surveying of volcanic CO2 emissions using aerial robots. CO2 is a useful predictor of volcanic eruptions and an influential greenhouse gas. However, current CO2 mapping methods are hazardous and inefficient, as a result, only a small fraction of CO2 emitting volcanoes have been surveyed. We develop algorithms and a platform to measure volcanic CO2 emissions. The Dragonfly Unpiloted Aerial Vehicle (UAV) platform is capable of long-duration CO2 collection flights in harsh environments. We implement two survey algorithms on teams of Dragonfly robots and demonstrate that they effectively map gas emissions and locate the highest gas concentrations. Our experiments culminate in a successful field test of collaborative rasterization and gradient descent algorithms in a challenging real-world environment at the edge of the Valles Caldera supervolcano. Both algorithms treat multiple flocking UAVs as a distributed flexible instrument. Simultaneous sensing in multiple UAVs gives scientists greater confidence in estimates of gas concentrations and the locations of sources of those emissions. These methods are also applicable to a range of other airborne concentration mapping tasks, such as pipeline leak detection and contaminant localization.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.835052</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.835052</link>
        <title><![CDATA[Self-Triggered Control of Multi-Agent Systems With External Disturbances]]></title>
        <pubdate>2022-02-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiang Li</author><author>Jing Zhu</author>
        <description><![CDATA[This paper investigates the consensus of multi-agent systems (MASs) by virtue of event-triggered mechanism. Considering the existence of external disturbances, we use a disturbance observer to estimate the disturbance signals and eliminate the corresponding effects by using estimators to compensate the input control terms. The self-triggered condition is designed and proved that there is no Zeno behavior. We show that the proposed disturbance observer can estimate the external disturbance signals well under the self-triggered condition. Finally, simulation examples are presented to verify the theoretical results.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2022.803468</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.803468</link>
        <title><![CDATA[Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions]]></title>
        <pubdate>2022-02-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Myungjin Jung </author><author>Kai Chuen Tan </author><author>Ran Dai</author>
        <description><![CDATA[This paper demonstrates an innovative group of robots, consisting of jumping rovers and a charging station, improved traversability and extended energy endurance when traveling to multiple target locations. By employing different jumping rovers with distinct energy consumption characteristics and jumping capabilities, we focus on searching for the most energy-efficient path of each jumping rover in a multi-waypoints visiting mission with obstacles. As jumping rovers can jump onto or over some obstacles without navigating around them, they have the potential to save energy by generating alternative paths to overcome obstacles. Moreover, due to the energy demands for the multi-waypoints mission and the limited battery capacity, a charging station is considered to provide extra energy for enhanced endurance during the mission. We first apply a refined rapidly-exploring random tree star (RRT∗) algorithm to find energy-efficient paths between any two target locations. Then, the genetic algorithm (GA) is applied to select the most profitable combination of paths to visit all targets with energy constraints. Finally, we verify the improved mobility and energy efficiency in both virtual simulation and experimental tests using a group of customized jumping rovers with a charging station and the proposed path planning and task allocation method.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2021.771857</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2021.771857</link>
        <title><![CDATA[Proportional Predictive Control of Networked Linear Switched Reluctance Machine System With Time-Varying Delay]]></title>
        <pubdate>2022-01-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Li Qiu</author><author>Tao Deng</author><author>Xiaomei Yang</author><author>Marzieh Najariyan</author><author>Jianfei Pan</author><author>Chengxiang Liu</author>
        <description><![CDATA[In this article, a proportional predictive (PP) control strategy is proposed and a high-precision position tracking controller is designed for the networked linear switched reluctance machine system (NLSRMS) with time-varying delay. The closed-loop system model of the NLSRMS is constructed based on the PP control strategy. The stability conditions of the system are proposed by combining the optimal control value calculated by the cost function. The controller of the closed-loop NLSRMS is designed by using continuously updated predictive output equation information based on calculation. The comparative study of the proposed PP and PID control methods is presented by tracking several types of signals. The maximum steady errors of PP and PID control strategies are 0.2 mm and 2 mm under the sinusoidal signal, respectively. The maximum steady errors of PP and PID control strategies are 0.07 mm and 0.7 mm under the square signal, respectively. The simulation results show the effectiveness of the proposed PP control strategy.]]></description>
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