<?xml version="1.0" encoding="utf-8"?>
    <rss version="2.0">
      <channel xmlns:content="http://purl.org/rss/1.0/modules/content/">
        <title>Frontiers in Control Engineering | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/control-engineering</link>
        <description>RSS Feed for Frontiers in Control Engineering | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-04-24T04:56:39.561+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2025.1645918</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2025.1645918</link>
        <title><![CDATA[Conflict-based model predictive control for multi-agent path finding experimentally validated on a magnetic planar drive system]]></title>
        <pubdate>2025-07-31T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kai Janning</author><author>Abdalsalam Housin</author><author>Christopher Schulte</author><author>Frederik Erkens</author><author>Luca Frenken</author><author>Laura Herbst</author><author>Bastian Nießing</author><author>Robert H. Schmitt</author>
        <description><![CDATA[IntroductionThis work presents an approach to collision avoidance in multi-agent systems (MAS) by integrating Conflict-Based Search (CBS) with Model Predictive Control (MPC), referred to as Conflict-Based Model Predictive Control (CB-MPC).MethodsThe proposed method leverages the conflict-avoidance strengths of CBS to generate collision-free paths, which are then refined into dynamic reference trajectories using a minimum jerk trajectory optimizer and then used inside a MPC to follow the trajectories and to avoid collisions. This integration ensures real-time trajectory execution, preventing collisions and adapting to online changes. The approach is evaluated using a magnetic planar drive system for realistic multi-agent scenarios, demonstrating enhanced real-time responsiveness and adaptability. The focus is on the development of a motion planning algorithm and its validation in dynamic environments, which are becoming increasingly relevant in modern adaptive production sites.ResultsOn the MAS demonstrator with four active agents, ten different scenarios were created with varying degrees of complexity in terms of route planning. In addition, external disturbances that hinder the execution of the paths were simulated. All calculation and solution times were recorded and discussed. The result show that all scenarios could be successfully solved and executed., and the CB-MPC is therefore suitable for motion planning on the presented MAS demonstrator.DiscussionThe results show, that the CB-MPC is suitable for motion planning on the presented MAS demonstrator. The greatest limitation of the approach lies in scalability with regard to increasing the number of agents.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1459399</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1459399</link>
        <title><![CDATA[Workpiece temperature control in friction stir welding of Inconel 718 through integrated numerical analysis and process control]]></title>
        <pubdate>2024-10-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ahmed Abotaleb</author><author>Mohammed Al-Azba</author><author>Marwan Khraisheh</author><author>Yves Remond</author><author>Said Ahzi</author>
        <description><![CDATA[Friction stir welding (FSW) offers significant advantages over fusion welding, particularly for high-strength alloys like Inconel 718. However, achieving optimal surface quality in Inconel 718 FSW remains challenging due to its sensitivity to temperature fluctuations during welding. This study integrates finite element simulations, statistical analysis, and advanced control methodologies to enhance weld surface quality through adequate thermal management. High-fidelity simulations of the FSW process were conducted using a validated 3D transient COMSOL Multiphysics model, producing a comprehensive dataset correlating process parameters (rotational speed, axial force, and welding speed) with workpiece temperature. This dataset facilitated statistical analysis and parameter optimization through Analysis of variance (ANOVA) method, leading to a deeper understanding of process variables. A nonlinear state-space system model was subsequently developed using experimental data and the system identification toolbox in Matlab, incorporating domain-specific insights. This model was rigorously validated with an independent dataset to ensure predictive accuracy. Utilizing the validated model, tailored control strategies, including proportional-integral-derivative (PID) and model predictive control (MPC) in both single and multivariable configurations, were designed and evaluated. These control strategies excelled in maintaining welding temperatures within optimal ranges, demonstrating robustness in response times and disturbance handling. This precision in thermal management is poised to significantly refine the FSW process, enhancing both surface integrity and microstructural uniformity. The strategic implementation of these controls is anticipated to substantially improve the quality and consistency of welding outcomes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1402621</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1402621</link>
        <title><![CDATA[Using reinforcement learning to autonomously identify sources of error for agents in group missions]]></title>
        <pubdate>2024-10-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Keishu Utimula</author><author>Ken-taro Hayaschi</author><author>Trevor J. Bihl</author><author>Kenta Hongo</author><author>Ryo Maezono</author>
        <description><![CDATA[When deploying agents to execute a mission with collective behavior, it is common for accidental malfunctions to occur in some agents. It is challenging to distinguish whether these malfunctions are due to actuator failures or sensor issues based solely on interactions with the affected agent. However, we humans know that if we cause a group behavior where other agents collide with a suspected malfunctioning agent, we can monitor the presence or absence of a positional change and identify whether it is the actuator (position changed) or the sensor (position unchanged) that is broken. We have developed artificial intelligence that can autonomously deploy such “information acquisition strategies through collective behavior” using machine learning. In such problems, the goal is to plan collective actions that result in differences between the hypotheses for the state [e.g., actuator or sensor]. Only a few of the possible collective behavior patterns will lead to distinguishing between hypotheses. The evaluation function to maximize the difference between hypotheses is therefore sparse, with mostly flat values across most of the domain. Gradient-based optimization methods are ineffective for this, and reinforcement learning becomes a viable alternative. By handling this maximization problem, our reinforcement learning surprisingly gets the optimal solution, resulting in collective actions that involve collisions to differentiate the causes. Subsequent collective behaviors, reflecting this situation awareness, seemed to involve other agents assisting the malfunctioning agent.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1452442</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1452442</link>
        <title><![CDATA[State dependent vagus nerve stimulation for targeted plasticity therapy: challenges and considerations]]></title>
        <pubdate>2024-10-11T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Bharadwaj Nandakumar</author><author>Ramanamurthy V. Mylavarapu</author><author>Rivaldo Harris</author><author>Eric R. Albuquerque</author><author>Zihan Yan</author><author>Cameron Herter</author><author>David W. McMillan</author><author>Vivek V. Kanumuri</author><author>Patrick D. Ganzer</author>
        <description><![CDATA[Targeted plasticity therapy (TPT) utilizes vagus nerve stimulation (VNS) to promote improvements in function following neurological injury and disease. During TPT, a brief burst of VNS induces neuromodulator release, which when paired with relevant behavioral events can influence functionally relevant neuroplasticity. Functional improvements following TPT are therefore in part mediated by neuromodulator signaling. Unfortunately, comorbidities associated with neurological disease often result in altered cognitive states that can influence neuromodulator signaling, potentially impeding neuroplasticity induced by TPT. Aside from altered cognitive states, cardiorespiratory rhythms also affect neuromodulator signaling, due to the vagus nerve’s role in relaying visceral sensory information from the cardiovascular and respiratory systems. Moreover, precise VNS delivery during specific periods of the cardiorespiratory rhythms may further improve TPT. Ultimately, understanding the impact of patient-specific states on neuromodulator signaling may likely facilitate optimized VNS delivery, paving the way for personalized neuromodulation during TPT. Overall, this review explores challenges and considerations for developing advanced TPT paradigms, focusing on altered cognitive states and cardiorespiratory rhythms. We specifically discuss the possible impact of these cognitive states and autonomic rhythms on neuromodulator signaling and subsequent neuroplasticity. Altered cognitive states (arousal deficits or pain) could affect VNS intensity, while cardiorespiratory rhythms may further inform optimized timing of VNS. We propose that understanding these interactions will lead to the development of personalized state dependent VNS paradigms for TPT.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1394668</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1394668</link>
        <title><![CDATA[Reinforcement learning for path planning of free-floating space robotic manipulator with collision avoidance and observation noise]]></title>
        <pubdate>2024-05-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ahmad Al Ali</author><author>Zheng H. Zhu</author>
        <description><![CDATA[This study introduces a novel approach for the path planning of a 6-degree-of-freedom free-floating space robotic manipulator, focusing on collision and obstacle avoidance through reinforcement learning. It addresses the challenges of dynamic coupling between the spacecraft and the robotic manipulator, which significantly affects control and precision in the space environment. An innovative reward function is introduced in the reinforcement learning framework to ensure accurate alignment of the manipulator’s end effector with its target, despite disturbances from the spacecraft and the need for obstacle and collision avoidance. A key feature of this study is the use of quaternions for orientation representation to avoid the singularities associated with conventional Euler angles and enhance the training process’ efficiency. Furthermore, the reward function incorporates joint velocity constraints to refine the path planning for the manipulator joints, enabling efficient obstacle and collision avoidance. Another key feature of this study is the inclusion of observation noise in the training process to enhance the robustness of the agent. Results demonstrate that the proposed reward function enables effective exploration of the action space, leading to high precision in achieving the desired objectives. The study provides a solid theoretical foundation for the application of reinforcement learning in complex free-floating space robotic operations and offers insights for future space missions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2024.1343851</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2024.1343851</link>
        <title><![CDATA[Self-paced heart rate control during treadmill exercise for persons with gait impairment: a case study]]></title>
        <pubdate>2024-04-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hanjie Wang</author><author>Diana Guimaraes</author><author>Tobias Nef</author><author>Kenneth J. Hunt</author>
        <description><![CDATA[Introduction:A self-paced (SP) heart rate (HR) control system proposed in a previous study was found to be feasible for healthy participants. The aims of this work were to investigate whether the SP HR control system is feasible to achieve accurate HR control in a participant with gait impairments, and to assess its interaction with an existing motor-driven body weight support (BWS) system.Methods:One participant with cerebral palsy was recruited in this case study. Three preliminary tests were completed to determine the appropriate mean value and amplitude of the target heart rate curve, and to identify a customised heart rate response model. Two series of formal self-paced heart rate control tests were then conducted to investigate the influence of different heart rate compensators and the presence of the BWS system.Results:The customised heart rate controller achieved improved accuracy in heart rate control and reduced oscillation in the treadmill target speed: the root-mean-square heart rate tracking error (RMSE) was 2.38 beats per minute (bpm) vs. 3.91 bpm (customised controller vs. nominal controller), and the average power of changes in the treadmill target speed was 0.4 × 10−4 m2/s2 vs. 8.4 × 10−4 m2/s2. The BWS system resulted in improved HR tracking accuracy: RMSE on heart rate tracking was 3.02 bpm vs. 3.50 bpm (with BWS vs. without BWS). The BWS system had no influence on the automatic position control accuracy: RMSE on distance tracking was 0.0159 m vs. 0.0164 m.Conclusion:After customising the heart rate compensator, the self-paced heart rate control system is feasible to achieve accurate heart rate control in an individual with gait impairments, and it can correctly interact with the BWS system.]]></description>
      </item><item>
        <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.2023.1279811</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1279811</link>
        <title><![CDATA[Erratum: Global versus local Lyapunov approach used in disturbance observer-based wind turbine control]]></title>
        <pubdate>2023-11-03T00:00:00Z</pubdate>
        <category>Erratum</category>
        <author>Frontiers Production Office </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.2023.1237759</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1237759</link>
        <title><![CDATA[Data-driven non-parametric chance-constrained model predictive control for microgrids energy management using small data batches]]></title>
        <pubdate>2023-08-17T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Leon Babić</author><author>Marco Lauricella</author><author>Glenn Ceusters</author><author>Matthias Biskoping</author>
        <description><![CDATA[This paper presents a stochastic model predictive control approach combined with a time-series forecasting technique to tackle the problem of microgrid energy management in the face of uncertainty. The data-driven non-parametric chance constraint method is used to formulate chance constraints for stochastic model predictive control, while removing the dependency on probability density assumptions of uncertain variables and retaining the linear structure of the resulting optimization problem. The proposed approach is suitable for implementation on systems with limited computational power or limited memory storage, thanks to its simple linear structure and its ability to provide accurate results within pre-defined confidence levels, even when using small data batches. The proposed forecasting and stochastic model predictive control approaches are applied on a numerical example featuring a small grid-connected microgrid with PV generation, a battery storage system, and a non-controllable load, showing the ability to reduce costs by reducing the confidence level, and to satisfy pre-defined confidence levels.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1228462</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1228462</link>
        <title><![CDATA[Editorial: Insights in control and automation systems]]></title>
        <pubdate>2023-06-08T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Antonio Visioli</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1185502</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1185502</link>
        <title><![CDATA[A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant]]></title>
        <pubdate>2023-04-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Gengjin Shi</author><author>Miaomiao Ma</author><author>Donghai Li</author><author>Yanjun Ding</author><author>Kwang Y. Lee</author>
        <description><![CDATA[Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.]]></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.2023.1162318</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1162318</link>
        <title><![CDATA[Optimization design of crude oil distillation unit using bi-level surrogate model]]></title>
        <pubdate>2023-03-31T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yingjian Xiong</author><author>Xuhua Shi</author><author>Yongjian Ma</author><author>Yifan Chen</author>
        <description><![CDATA[Crude Oil Distillation Unit (CDU) is one of the most important separation installations in the petroleum refinery industries. In this work, a Bi-level Surrogate column model Aided Constrained Optimization Design (Bi-SACOD) is proposed for time-consuming objectives and constraints in the evolutionary optimization design of CDUs. The main components of Bi-SACOD include bi-level surrogate model construction (Bi-SMC), bi-level model management (Bi-MM), and particle swarm optimization (PSO) mixed-integer constrained evolutionary (PSO-MICE) search. Bi-SMC implements surrogate column model construction and feasible domain identification. Bi-MM combines surrogate column models with rigorous CDU simulations to perform model management, and PSO-MICE implements optimum search works. The optimization results of the CDUs indicate that Bi-SACOD outperforms the single-level surrogate column model approaches, and are more consistent with the rigorous CDU model optimization approach, whereas the evaluation numbers of the time-consuming rigorous models are significantly reduced.]]></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.2023.1135258</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1135258</link>
        <title><![CDATA[Obstacle-avoidance trajectory planning and sliding mode-based tracking control of an omnidirectional mobile robot]]></title>
        <pubdate>2023-03-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhe Sun</author><author>Shujie Hu</author><author>Xinan Miao</author><author>Bo Chen</author><author>Jinchuan Zheng</author><author>Zhihong Man</author><author>Tian Wang</author>
        <description><![CDATA[Trajectory planning and tracking control play a vital role in the development of autonomous mobile robots. To fulfill the tasks of trajectory planning and tracking control of a Mecanum-wheeled omnidirectional mobile robot, this paper proposes an artificial potential field-based trajectory-planning scheme and a discrete integral terminal sliding mode-based trajectory-tracking control strategy. This paper proposes a trajectory-planning scheme and a trajectory-tracking control strategy for a Mecanum-wheeled omnidirectional mobile robot by using artificial potential field and discrete integral terminal sliding mode, respectively. First, a discrete kinematic-and-dynamic model is established for the Mecanum-wheeled omnidirectional mobile robot. Then, according to the positions of the robot, target, and obstacles, a reference an obstacle-avoidance trajectory is planned and updated iteratively by utilizing artificial potential field functions. Afterward, a discrete integral terminal sliding mode control algorithm is designed for the omnidirectional mobile robot such that the robot can track the planned trajectory accurately. Meanwhile, the stability of the control system is analyzed and guaranteed proved in the sense of Lyapunov. Last, simulations are executed in the scenarios of static obstacles and dynamic obstacles. The simulation results demonstrate the effectiveness and merits of the presented methods.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcteg.2023.1158164</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2023.1158164</link>
        <title><![CDATA[Self-paced heart rate control for treadmill exercise]]></title>
        <pubdate>2023-03-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hanjie Wang</author><author>Kenneth J. Hunt</author>
        <description><![CDATA[Introduction: With conventional heart rate (HR) control systems, the exercising person is bound to walk or run at a pace determined by the feedback. This may be challenging for people with impairments that make it difficult for them to achieve a smooth, continuous pace. The aim of this work was to assess the technical feasibility of a novel self-paced heart rate control strategy and to compare its accuracy with conventional heart rate control.Methods: We propose a self-paced heart rate control system that embeds an automatic positioning controller within the heart rate control loop. The treadmill speed command is decoupled from the heart rate compensator, whereas speed is determined by the exerciser’s own volition: target speed is displayed visually to the person and, when they try to follow this target, the position controller sets the treadmill speed while keeping the person at a safe reference position on the track. A further novel contribution of this work is a new input-sensitivity-shaping, frequency-domain design strategy for feedback control of position.Results: Experimental evaluation with four participants showed that self-paced heart rate control is technically feasible: all participants were able to accurately follow the target running speed calculated by the HR compensator and presented to them visually; for all four participants, self-paced HR tracking accuracy was not substantially different from conventional HR control performance; on average, the self-paced heart rate controller gave slightly better performance than conventional HR control, with RMS tracking error of 2.98 beats per minute (bpm) vs 3.11 bpm and higher average control signal power.Conclusion: The proposed self-paced heart rate control strategy with embedded automatic position control is deemed feasible. This approach may be helpful for people with gait impairments or other limitations that make it difficult for them to follow an imposed treadmill speed.]]></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.2022.787530</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcteg.2022.787530</link>
        <title><![CDATA[Global Versus Local Lyapunov Approach Used in Disturbance Observer-Based Wind Turbine Control]]></title>
        <pubdate>2023-02-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Eckhard Gauterin</author><author>Florian Pöschke</author><author>Horst Schulte</author>
        <description><![CDATA[This contribution presents a Lyapunov-based controller and observer design method to achieve an effective design process for more dedicated closed-loop dynamics, i.e., a maximal flexibility in an observer-based controller design with a large consistency in desired and achieved closed-loop system dynamics is intended. The proposed, pragmatic approach enhances the scope for controller and observer design by using local instead of global Lyapunov functions, beneficial for systems with widely spaced pole locations. Within this contribution, the proposed design approach is applied to the complex control design task of wind turbine control. As the mechanical loads that affect the wind turbine components are very sensitive to the closed-loop system dynamic, a maximum flexibility in the control design is necessary for an appropriate wind turbine controller performance. Therefore, the implication of the local Lyapunov approach for an effective control design in the Takagi-Sugeno framework is discussed based on the sensitivity of the closed-loop pole locations and resulting mechanical loads to a variation of the design parameters.]]></description>
      </item>
      </channel>
    </rss>