IEEE/CAA Journal of Automatica Sinica
@JAutoSinica
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An academic journal of IEEE and CAA , publishes high-quality, far-reaching papers on original research and development globally in areas of automation
Joined June 2016
In 2022 #IEEECAA @JAutoSinica has reached #ImpactFactor 7.847, has #readership in 145+ countries, and is a community of #researchers in many fields of #automation from 520+ institutions in 50 countries. Choose #JAS, create impact. Know more here:
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New LP-RL mechanism for optimal decision-making in incomplete-information games combines #LinearProgramming for state prediction & #ReinforcementLearning for dynamic action selection. #GameTheory #AI . Check here:
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New framework for Validating Deep Reinforcement Learning uses #probabilistic automata to identify & correct #vulnerabilities, improving real-world performance. Check here: #IEEECAA #JournalofAutomaticaSinica:
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Researchers developed a general framework in Lyapunov stability theory for #NonlinearSystems, encompassing various stability types (asymptotic, finite-time, etc.) and applied it to time-varying convex optimization. Check here: #IEEECAA #JournalofAutomat
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According to a new #IEEECAA #JournalofAutomaticaSinica study, a novel #Safe #QLearning approach is suitable for #DataDriven nonlinear optimal control with asymmetric #StateConstraints. Learn more here:
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Scientists propose distributed fixed-time #Optimal #EnergyManagement for #Microgrids by utilizing a #DynamicEvent triggered mechanism in this #IEEECAA #JournalofAutomaticaSinica paper:
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In an innovative #IEEECAA #JournalofAutomaticaSinica article, scientists integrate #InventoryMonitoring and #CapacityChanges in #DynamicSupplyChains with bidirectional cascading propagation effects:
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Researchers remarkably achieve #DisturbanceRejection for systems with uncertainties by leveraging fixed-time #EquivalentInputDisturbance approach. Read more in #IEEECAA #JournalofAutomaticaSinica:
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It is now possible to efficiently and effectively perform #LevelCurveTracking of #UnmannedAerialVehicles via robust #ReinforcementLearning guided model predictive control . Check out this interesting #IEEECAA #JournalofAutomaticaSinica paper:
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The latest #IEEECAA #JournalofAutomaticaSinica review explores the definition, modeling, analysis, evaluation, and control for #FrequencyStability in #LowInertia #PowerSystems. For further details, visit:
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According to a new #IEEECAA #JournalofAutomaticaSinica paper, a novel and robust #Offline #ActorCritic with on-policy regularized #PolicyEvaluation significantly outperforms state-of-the-art alternatives:
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Researchers showcase an #Augmented #Dynamics approach through high-order control barrier function-based #SafetyControl of #Constrained #RoboticSystems in this intriguing #IEEECAA #JournalofAutomaticaSinica article:
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A new #IEEECAA #JournalofAutomaticaSinica paper demonstrates prediction-based #StateEstimation and #CompensationControl for #NetworkedSystems which have #CommunicationConstraints and #DenialOfService #Attacks:
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The latest #IEEECAA #JournalofAutomaticaSinica research study achieves multi--unmanned surface vehicle formation #CollisionAvoidance using #DeepReinforcementLearning and #InternationalRegulations for preventing collisions at #Sea:
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An innovative #Transfer Learning framework for deep #MultiAgent #ReinforcementLearning improves model #Performance and #Convergence. Learn more in this #IEEECAA #JournalofAutomaticaSinica paper:
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The recent #IEEECAA #JournalofAutomaticaSinica study demonstrates the #Controllability of #MultiRelational #Networks With #Heterogeneous #Dynamical #Nodes. For further information, check out this link:
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A novel #Human observation-inspired universal #ImageAcquisition paradigm integrates multi-objective #MotionPlanning with #Control for #Robotics in this groundbreaking #IEEECAA #JournalofAutomaticaSinica article:
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A recent #IEEECAA #JournalofAutomaticaSinica article proposes a distributed adaptive second-order #LatentFactor #Analysis model, solving the problem of high-dimensional and incomplete #DataRepresentation. Visit:
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According to the latest #IEEECAA #JournalofAutomaticaSinica article, a #LinearProgramming based #ReinforcementLearning mechanism is highly promising for #IncompleteInformation #Games. Learn more:
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A new #IEEECAA #JournalofAutomaticaSinica paper discusses a novel #Probabilistic #Automata based method to enhance the #Performance of #DeepReinforcementLearning systems. Explore the research further here:
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Researchers have recently explored #HighOrder #FullyActuated system models for #StrictFeedback systems with higher #Dimensions. Read more in #IEEECAA #JournalofAutomaticaSinica:
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