subject

cs.SY

cs.SY: explore 409 source-linked works published from 2017 to 2026, with original documents and citations.

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Includes records with this source-supplied label or an explicit phrase match in their metadata. Matches indicate a mention, not proof that a paper uses a method or tests a material. Source versions are consolidated by DOI.

Sources: arxiv. Collection updated 2026-09-16. Counts describe this index, not the complete source archives.

arXiv2026

Angle diversity receiver as a key enabler for reliable ORIS-based Visible Light Communication

Visible Light Communication (VLC) offers a promising solution to satisfy the increasing demand for wireless data. However, link blockages remain a significant challenge. This paper addresses this issue by investigating the combined use of angle diversity receivers (ADRs) and optical reconfigurable intelligent surfaces (ORISs) in multiuser VLC systems. We consider ORIS elements as small movable mirrors. We demonstrate the complementarity of ADR and ORIS in mitigating link blockages, as well as the advantages of using a larger number of ORIS elements due to the increased field-of-view (FoV) at the receiver enabled by the ADR. An optimization algorithm is proposed to maximize the minimum signal-to-noise power ratio (SNR) to deploy a fair communication network. Numerical results show that integrating ADR and ORIS significantly enhances VLC communication performance, achieving an SNR gain of up to 30 dB compared to a system without ORIS, and mitigating communication outages produced by link blockages or out-of-FoV received signals. We also prove that an ADR with a single tier of photodiodes is sufficient to complement ORIS-assisted VLC.

eess.SP↗

arXiv2026

Toward Interaction Dynamics: A Predictive Framework for Safe Physical Human Robot Interaction

Physical human-robot interaction requires yielding transiently to contact yet recovering the commanded reference under sustained load. Finite-stiffness impedance control retains a static deflection there, while predictive alternatives typically optimize a nonlinear robot or impedance model online. Operational-space cancellation instead exposes a translational error double integrator with a fixed transition matrix and a configuration-scheduled input map, making interaction a predictive quantity rather than a property re-derived per configuration. We build on it a compact offset-free interaction-error MPC for torque-controlled manipulators: a force-domain random-walk state estimates persistent interaction and model error, and a 30-variable convex QP maps the correction through the current task inertia while constraining the applied joint torque. Conditional results establish impedance equivalence of the unconstrained passive feedback, offset-free regulation at feasible frozen configurations, and quadratic stabilizability of the scheduled backbone. In a 1kHz MuJoCo simulation of a 7-DOF Franka FR3, the estimator cuts steady-state error under a repeated 15N step from 2.77mm to 0.042mm when added to the otherwise identical 100Hz MPC. A stiffness-and-damping-calibrated impedance baseline attains 2.59mm but briefly saturates and needs 3.3x the peak positive joint power. Adding ideal measured-force cancellation to that baseline gives 1.39mm, so constant-load rejection is not unique to MPC; the sensorless controller still reaches 0.042mm in the moving task, a 65x reduction without force sensing and without the baseline's saturation or power cost. Demonstrated in simulation under a shared actuator budget, the contribution is an efficient operational-space realization complementing rather than replacing broader interaction-control architectures.

cs.RO↗

arXiv2026

Contact-Consistent Interaction Dynamics Normalization for Predictive Physical Human--Robot Interaction

Safe physical human--robot interaction on floating-base robots requires interaction regulation under changing contact constraints. We develop a contact-consistent normalization in which the residual end-effector channel is represented as a linear double integrator in acceleration coordinates. Both discrete prediction matrices are independent of configuration and support mode; posture and contact enter only through task-inertia force recovery and constraints. The controller combines a constant-Hessian receding-horizon QP, an acceleration-disturbance observer, and a priority-consistent realization. Classical operational-space impedance is shown to be the unconstrained infinite-horizon limit. MuJoCo experiments on a 17-DOF biped and a Menagerie-derived Unitree G1 model evaluate sustained forces, transmitted shocks, and scheduled contact-model changes. The observer sustains near-offset-free tracking across a genuine contact-set switch and a scheduled support-mode transition, while disturbance estimation---not contact consistency alone---is the dominant source of fixed-stance accuracy; covariance inflation gives only scenario-dependent transient benefit.

cs.RO↗

arXiv2026

A Kalman Filter-Based Tracking Loop Design for Real-Time Aerospace GNSS Applications with Minimum Pull-Out Probability

Kalman filter-based (KF-based) tracking loops are a powerful alternative to traditional phase-locked loops (PLLs) for Global Navigation Satellite Systems (GNSS) signal tracking. The primary advantage of the KF is its ability to incorporate high-fidelity models for receiver dynamics and clock errors, allowing the loop to adapt optimally to signal conditions. However, this theoretical optimality is often compromised in practice by the processing delays inherent in real-time systems with hardware correlators, which existing KF formulations typically neglect. This paper introduces a Modified Kalman filter (mKF) that overcomes this limitation specifically for hardware-based architectures. By reformulating the measurement update to be consistent with the processing delays, the proposed mKF maintains optimality in a practical implementation. We further present a systematic method for tuning both the process noise covariance matrix and the correlation time, based on an analytical expression for the pull-out probability (POP), which is validated through Monte Carlo simulation. The mKF is then validated with a GNSS signal simulator, both by post-processing baseband samples and on a real-time GPS receiver with hardware correlators. A direct equivalence between the mKF and a one-delay Digital PLL (DPLL) is established entirely in the digital domain. At equal noise bandwidth, the mKF matches the DPLL's phase error variance while achieving lower error in the higher-order states. Moreover, the mKF sustains lock at bandwidths inaccessible to the optimal one-delay DPLL under the same dynamic stress, positioning the proposed architecture as a robust and noise-efficient solution for high-dynamic aerospace GNSS applications.

eess.SP↗

arXiv2026

FIREQ: FPGA Instrumentation for Readout and Qubit control

We present FIREQ (FPGA Instrumentation for Readout and Qubit control), an open-source RFSoC-based framework for the control and readout of superconducting qubits. FIREQ combines a modular AXI-compliant firmware architecture with a PYNQ-based software stack designed to support extensible hardware integration, deterministic experiment timing, and low-overhead execution of repeated calibration and characterization workflows. The firmware implements direct RF synthesis and acquisition, trigger-based sequencing, programmable pulse generation, frequency-multiplexed readout, and memory-efficient acquisition and waveform buffering. The software adopts a client-server architecture with streamed data transfer and dependency-aware configuration updates to reduce host-device and reconfiguration overhead during parameter sweeps. On an AMD Zynq UltraScale+ RFSoC ZCU216, FIREQ generates RF pulses up to 9.3 GHz with a pulse-duration resolution of 107 ps and an event-timing resolution of 1.7 ns. FPGA resource utilization is compared with representative open-source RFSoC control frameworks, showing a low BRAM footprint while retaining full-rate I/Q generation and acquisition. The RF output is characterized in terms of phase noise, noise spectral density, and inter-channel timing skew. End-to-end operation is validated on a superconducting qubit through resonator spectroscopy, Rabi, Ramsey, and relaxation measurements, yielding T1 = 6.94 us and T2* = 13.50 us. FIREQ can therefore be used both as a qubit-control platform and as an experimental environment for evaluating alternative control and readout IP architectures.

quant-ph↗

arXiv2026

Independent Reinforcement Learning in Discounted Markov Games

In this work, we study radically uncoupled learning in discounted general-sum Markov games. Assuming ``$\mathsf{ETH}$ for $\mathsf{PPAD}$", we show that, for every fixed discount factor, there is no polynomial-time algorithm for computing inverse-polynomially accurate coarse correlated equilibria in discounted general-sum Markov games when players learn independently in decentralized settings. Complementing this hardness result, we provide what appears to be the first \emph{radically uncoupled} algorithm with sub-exponential convergence guarantees to coarse correlated equilibria in discounted general-sum Markov games without imposing any structural restrictions on the game. Our algorithm is a \emph{layered} variant of optimistic mirror descent with an increasing step-size schedule tailored to the multi-agent setting. Finally, we develop both full-feedback and partial feedback versions of the aforementioned algorithm and establish sub-exponential convergence guarantees for each case.

cs.GT↗

arXiv2026

Optimal Uniform Pricing for Multi-Interval Dispatch without Make-Whole Uplifts

In a network with ramp-limited generators and inaccurate net-demand forecasts, practical rolling-window dispatch can drive locational marginal prices (LMPs) below generators' bid-in offers. In such cases, out-of-market (OOM) settlements are used to compensate generators and maintain dispatch-following incentives, but OOM can have negative consequences, including nontransparent real-time price signals, discriminatory compensation, and incentives for untruthful bidding. This paper presents an optimal uniform pricing rule that minimizes demand payments, eliminates OOM make-whole payments, preserves LMP-based congestion charges, and ensures revenue adequacy. We derive the proposed pricing rule in closed form and relate it to existing pricing schemes. Numerical comparisons demonstrate favorable generator profits and reduced price volatility. However, higher generator profits are accompanied by increased demand payments, reflecting the in-market, uniform allocation of ramping costs while preserving the LMP-based congestion charges widely used in real-time market settlements. The numerical results also show that, under LMP with OOM settlement, a price-taking generator has an incentive to inflate its offer, whereas this incentive is absent under the proposed pricing rule within the tested bid range.

eess.SY↗

arXiv2026

A Bayesian Adaptive Spectral Surrogate Model for Efficient Probabilistic Optimal Power Flow Evaluation

This paper presents an adaptive stochastic spectral embedding (ASSE) method to solve the probabilistic AC optimal power flow (AC-OPF), a critical aspect of power system operation. The proposed method can efficiently and accurately estimate the probabilistic characteristics (e.g., mean, variance, median, and quantile-based metrics) of AC-OPF solutions while minimizing power losses. Based on estimated AC-OPF decisions (i.e., generator outputs), the confidence interval (CI)-based production cost index can be determined. Specially, an adaptive domain partition strategy is adopted to guide refinement domain selection and partition. The Bayesian compressive sensing-based coefficient calculation algorithm is integrated to enhance its performance. Numerical studies on modified IEEE 9-bus and IEEE 118-bus systems demonstrate that the proposed ASSE method offers accurate and fast evaluations compared to Monte Carlo simulations. Comparisons with a sparse polynomial chaos expansion, Gaussian process regression, and deep neural networks, further illustrate its efficacy in accurately assessing the responses with strongly localized behavior and non-symmetric distributions, providing practical decision-making bounds for generator outputs and operating costs under uncertainty.

eess.SY↗

arXiv2026

Importance and methods to control, vary, and characterize mud strength for studying locomotion

Animals and robots encounter mud at the water-land interface. Like sand, mud can stay solid or flow like a fluid. Unlike sand, the yield strength of mud at which solid-fluid transitions occur depends on not only the amount of solid relative to fluid (water in mud, air in dry sand), but also how much coarse grains and fine clay are within the solid. Despite understanding of locomotion on/within dry sand dominated by coarse grains with repulsive normal forces and friction, little is known for mud dominated by fine clay with strong cohesion. Here, we developed methods to prepare uniform mud of controlled, variable yield strength and characterize and track its drift from water evaporation. Compared to other flowable substrates, mud strength measured by upward force during penetration is weaker and can vary more, and mud sticks more during extraction to pull downward, making it more challenging for locomotion.

physics.bio-ph↗

arXiv2026

Mudskippers use tail thrusting to help crutching to move on mud of various wetness

At the water-land interface, amphibious fishes encounter wet flowable substrates made of granular solid-water mixtures, which can stay solid or flow like a fluid. As these substrates become wetter or drier, their yield strength (at which solid-fluid transition occurs) and cohesion (how sticky they are) both change, challenging locomotion. Despite substantial understanding of tetrapod locomotion on flowable substrates (mostly dry sand), we know little about how amphibious fishes cope with wet flowable substrates of various wetness. Here, we studied mudskippers on clay mud of controlled, variable wetness over the range where solid-fluid transition occurs. As mud became wetter, its strength decreased by 100-fold, leading the animal to sink deeper, with larger areas of body and fins contacting mud. By contrast, mud stuck most easily at intermediate wetness. The increased sinkage and contact and stickiness change caused more mud to stick to and pull against the animal on wetter mud. We also tested dry mud, which stuck to animal fins as its mucus dried. Despite these challenges, the mudskipper predominately used a conserved crutching gait on all except the wettest mud tested, with a modest performance reduction. When normal crutching became less effective, the animal assisted it with tail thrusting, by bending and straightening it to push downward and backward to generate additional thrust and lift, or even thrusting the tail to jump. These observations suggest that mudskipper's crutching motor program is well adapted to its native muddy substrates but inflexible, with most novelty in tail use.

physics.bio-ph↗

arXiv2026

IMU-Aided Correction of Orientation-Induced Ranging Error in Bluetooth Channel Sounding on Commercial Hardware

Bluetooth Low Energy Channel Sounding (BLE CS), standardized in Bluetooth Core Specification 6.0 (September 2024), enables distance estimation via phase-based ranging (PBR) and round-trip time (RTT). Although prior work has studied CS accuracy in configurations with a fixed orientation, no published work has studied how device orientation affects ranging error on commercial hardware. We present the first study of orientation-induced CS ranging error and a Machine Learning correction using IMU features. This study used the EFR32xG24 Channel Sounding Development Kit, the only commercial CS platform with an integrated six-axis Inertial Measurement Unit (IMU). Our results show that device orientation has a substantial effect on CS ranging accuracy; we found that a Random Forest model trained on the IMU derived orientation achieved a 74.6\% Mean Absolute Error (MAE) reduction under a Leave One Orientation Out Evaluation, demonstrating that IMU readings have potential to improve ranging accuracy.

eess.SY↗

arXiv2026

Strategic and Grid-Aware Maintenance Planning of Offshore Wind Farms

Wind turbines require regular maintenance and the resulting costs are a substantial component of a wind farm's cost of electricity production. As a result, there has been ongoing interest in improving wind turbine maintenance scheduling to find an optimal balance between maintenance costs and the risk of failure or unplanned repairs. What remains understudied is the opportunity for wind farms to schedule maintenance in the context of grid conditions and electricity market clearing. This paper contributes to closing this gap by modeling and studying wind farm maintenance planning in a grid and electricity market context. We also review current U.S. practice of wind farm maintenance scheduling, which motivates this paper and its models. Our focus is the derivation of a strategic maintenance planning problem, alongside an efficient solution approach, in which the wind farm operator aims to submit a derated wind farm capacity such that the resulting market clearing and electricity prices maximize its profit while ensuring that all required maintenance can be performed. We derive and study both deterministic and stochastic versions of the model, with the latter considering environmental and operational uncertainties. We conduct numerical experiments using the IEEE RTS 96-bus testbed with real-world offshore wind farm data and investigate the roles of farm and turbine size, as well as forecast quality. We observe an alignment between strategic and grid-serving maintenance planning and find that wind farms can improve their bottom line with low impact on system costs.

eess.SY↗

arXiv2026

Behavior--Realization Separation for Constrained Physical Human--Robot Interaction

Physical human--robot interaction software often couples desired-behavior specification with constrained realization; we treat these as separate layers. A \emph{behavior layer} supplies a desired contact-port acceleration $a_k^{\mathrm{id}}=f_θ(e_k,\dot e_k,F_{h,k})$. A \emph{realization layer} converts it into constrained robot commands and reports total desired-versus-realized acceleration error instead of hiding it in saturation. A same-objective unconstrained counterfactual separates regularization from constraint intervention, while plant data expose model error. This paper implements a receding-horizon quadratic program realizing memoryless affine behaviors. Changing the behavior modifies objective coefficients through $(C_θ,G_θ)$ while the robot-command variable and feasible set remain unchanged. A planar study instantiates impedance and admittance; the same running layer accepts an impedance--admittance--impedance reassignment without reconstruction, under its existing rate limit. On a torque-controlled 7-DOF Franka FR3 in MuJoCo, the runtime freezes task-space dynamics per solve and enforces torque feasibility across its horizon. Under a sustained 20~N push, it holds a slack-relaxed workspace boundary to within approximately 0.1--0.2~mm, versus 4.4~cm (impedance) and 4.7~cm (admittance) overshoot from instantaneous clipping. A derated actuator budget then activates the torque constraint: horizon-wide enforcement keeps its frozen-model plan feasible to $2.1\times10^{-4}$~N$\cdot$m, whereas a first-step-only ablation plans up to 11.329~N$\cdot$m beyond budget; on the executed nonlinear plant, where both share the same local-model error, the gap is smaller but still favors horizon-wide enforcement (0.161 vs.\ 0.380~N$\cdot$m). These results are a focused proof of behavior--realization separation.

cs.RO↗

arXiv2026

Context-Aware Intelligent Vehicles

Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-cabin monitoring and fleet management, all under tight requirements on accuracy, latency, cost, and reliability. Meeting these requirements is challenging because vehicles operate in complex, uncertain, and rapidly changing environments while running on resource-constrained computing platforms. This paper argues that context-situational factors that give meaning to sensor signals and constrain decisions-should be treated as a first-class principle for next-generation vehicle systems, and operationalized as a unified, shared state for learning, risk assessment, and closed-loop control across the software stack. We systematically review state-of-the- art (SOTA) context-aware methods spanning (i) environment understanding, (ii) planning and control, (iii) safety and security, and (iv) connected vehicles. Based on a trend analysis of context-aware design, we identify four key technical challenges in building a general contextual engine for future intelligent vehicles: multi-modal context fusion, temporal context modeling, handling rare events, and collaborative context sharing. We hope this survey will motivate the development of robust and efficient context-aware vehicle applications.

cs.RO↗

arXiv2026

Order-Adaptive Distributed Integral Control

We address a structural tradeoff in distributed dynamic coordination: when the target complexity is unknown, a low controller order saves states but may leave a persistent tracking error, whereas a high order improves tracking but may burden every agent with unnecessary dynamics. To remove this choice without resorting to computationally more involved nonlinear feedback or chattering-prone nonsmooth feedback, we develop an order-adaptive distributed integral controller (OADIC). Specifically, we start with proportional feedback and add integral states only when locally measurable relative errors show that the current order is inadequate. Meanwhile, we organize the candidate controllers in a nested form, thereby preserving the existing states and gains and maintaining continuous control inputs during order transitions. To provide a theoretical basis for this design, we first characterize the consistency of prescribed relative displacements on the augmented agent--target graph. Next, we construct gains that stabilize all admissible fixed-order subsystems and establish a uniform input-to-state stability bound for the variable-dimension closed loop. Furthermore, we prove that OADIC rejects every insufficient order after finitely many decision intervals and explicitly bound the rejection time of the critical order.

eess.SY↗

arXiv2026

A Modular IoT-Enabled Remote Laboratory Platform for Hybrid Energy System Research and Engineering Education

Remote laboratory systems improve accessibility in engineering education and research by enabling Internet-based interaction with physical equipment. This paper presents a modular IoT-enabled remote laboratory platform for hybrid energy system studies, combining renewable energy emulators, battery storage, and programmable loads within a three-interface architecture based on a web HMI, TIA Portal, and MATLAB/Simulink, all connected through a Talk2M VPN cloud. An industrial PLC and IoT gateway provide deterministic local control as well as secure remote access and monitoring. A hierarchical energy-management algorithm is validated by comparing local and remote executions under identical wind and irradiance profiles. The results show small differences in the energy balances of the renewable sources, battery, and load, while typical communication delays are on the order of 100 ms. Consequently, the platform supports research-grade remote experimentation and project-based learning in control and energy systems engineering.

eess.SY↗

arXiv2026

A Three-phase and Single-phase Compatible Dual-Mode EV On-Board Charger with Integrated Active Power Decoupling

Onboard charger (OBC) is essential part of Electric Vehicle (EV). High-performance EVs are preferring three phase charging to achieve higher power level. However, the ability to charge from a single phase supply is also required. A dualmode OBC for EVs is proposed, which is capable of operating from both three-phase supply and single-phase supply. The single phase charging comes with the requirement of bulky DC link capacitance due to double frequency current in DC link. The proposed topology eliminates this by achieving Active Power Decoupling (APD) using only one additional relay switch and a small capacitor. The proposed topology is verified under different conditions in a detailed simulation, which shows more than an order of magnitude reduction in DC link capacitance during single phase operation.

eess.SY↗

arXiv2026

Low-Complexity Control Under Input Saturation and Performance Constraints: A Bidirectional Modification Scheme

This article addresses the output tracking control problem for a class of high-order uncertain highly-coupled MIMO nonlinear systems subject to input saturation and performance constraints. To resolve the problem, a bidirectional modification mechanism is constructed, which is able to not only relax the constraints when saturation occurs to alleviate potential conflict, but also accelerate the recovery of original constraints after saturation ceases, and further tighten the constraints to enhance control performance if saturation remains inactive at the steadystate phase. Based on the mechanism, a model-, approximationand complexity-explosion-free control scheme is proposed. To bypass the obstacle in Lyapunov analysis, a novel stability analysis framework is developed, which, given that two parameter selection conditions are met, ensures satisfaction of modified constraints and boundedness of all closed-loop signals. Simulation results validate the effectiveness and superiority of the methodology.

eess.SY↗

Compare source metadata on this page

Work	Published	Source identifier	Source
Angle diversity receiver as a key enabler for reliable ORIS-based Visible Light Communication	2026-09-01	2505.10129	arxiv
Toward Interaction Dynamics: A Predictive Framework for Safe Physical Human Robot Interaction	2026-09-01	2606.08281	arxiv
Contact-Consistent Interaction Dynamics Normalization for Predictive Physical Human--Robot Interaction	2026-09-01	2606.14617	arxiv
A Kalman Filter-Based Tracking Loop Design for Real-Time Aerospace GNSS Applications with Minimum Pull-Out Probability	2026-09-01	2606.23925	arxiv
FIREQ: FPGA Instrumentation for Readout and Qubit control	2026-09-01	2608.29399	arxiv
Independent Reinforcement Learning in Discounted Markov Games	2026-09-01	2609.00504	arxiv
Optimal Uniform Pricing for Multi-Interval Dispatch without Make-Whole Uplifts	2026-09-01	2609.00541	arxiv
A Bayesian Adaptive Spectral Surrogate Model for Efficient Probabilistic Optimal Power Flow Evaluation	2026-09-01	2609.00547	arxiv
Importance and methods to control, vary, and characterize mud strength for studying locomotion	2026-09-01	2609.00563	arxiv
Mudskippers use tail thrusting to help crutching to move on mud of various wetness	2026-09-01	2609.00564	arxiv
IMU-Aided Correction of Orientation-Induced Ranging Error in Bluetooth Channel Sounding on Commercial Hardware	2026-09-01	2609.00650	arxiv
Strategic and Grid-Aware Maintenance Planning of Offshore Wind Farms	2026-09-01	2609.00651	arxiv
Behavior--Realization Separation for Constrained Physical Human--Robot Interaction	2026-09-01	2609.00669	arxiv
Context-Aware Intelligent Vehicles	2026-09-01	2609.00682	arxiv
Order-Adaptive Distributed Integral Control	2026-09-01	2609.00688	arxiv
A Modular IoT-Enabled Remote Laboratory Platform for Hybrid Energy System Research and Engineering Education	2026-09-01	2609.00815	arxiv
A Three-phase and Single-phase Compatible Dual-Mode EV On-Board Charger with Integrated Active Power Decoupling	2026-09-01	2609.00822	arxiv
Low-Complexity Control Under Input Saturation and Performance Constraints: A Bidirectional Modification Scheme	2026-09-01	2609.00827	arxiv

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.