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"control function"
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Change of Scale and Forecasting with the Control-Function Method in Logit Models
Endogeneity is a model misspecification that precludes the consistent estimation of the model parameters. The control-function method is the most suitable tool to address endogeneity for several discrete choice models that are relevant in transportation research. However, the estimators obtained with the control-function method are consistent only up to a scale. In this paper, we first depict the determinants of this change of scale by adapting an existing result for omitted orthogonal attributes in logit models. Then, we study the problem of forecasting under these circumstances. We show that a procedure proposed in previous literature may lead to significant biases, and we suggest novel alternatives to be used with synthetic populations. We use Monte Carlo experimentation and real data on residential location choice to illustrate these results. The paper finishes by summarizing the findings of this investigation and suggesting future lines of research in this area.
Journal Article
Optimization controller synthesis using adaptive robust control Lyapunov and barrier functions for high-order nonlinear system
The control Lyapunov function (CLF)- and the control barrier function (CBF)-based control methods have been popularly studied to mediate the safety and stability requirements for the nonlinear control system. In this article, we propose a general adaptive robust control framework that can accommodate high-relative-degree constraints and matched and mismatched disturbances in the system dynamics while also avoiding the sharp increase in the time complexity and the conservatism of the controller, which is a challenging problem in current methods. An online adaptive estimation scheme is first presented to estimate the dynamics of matched and mismatched disturbances. Then an adaptive robust CLF (ARCLF) and an adaptive robust CBF (ARCBF) are proposed and integrated with a quadratic program (QP) to synthesize the general adaptive robust control framework, without adding any extra decision variables. The safety and the stability of the proposed method are also proved. Finally, the safe control problem of an underactuated unmanned surface vessel (UUSV) with matched and mismatched disturbances is solved to validate that the proposed method has less conservatism and better control performance compared with the existing methods.
Journal Article
Equalization of the Occlusal State by Wearing a Mouthguard Contributes to Improving Postural Control Function
The aim of this study was to clarify the effect on the postural control function of equalizing the occlusal contact state by wearing a mouthguard. Method: Participants included 23 untrained adults, 11 gymnasts, and 10 weightlifters. Custom mouthguards were fabricated and adjusted so that all teeth were in even contact with light clenching. The standing postural control function was evaluated by the displacement of the center of foot pressure (COP) measured using a gravity center fluctuation meter. Measurement conditions were with and without a mouthguard. Statistical analyses were performed on the differences in COP displacement among participant groups and between mouthguard conditions and the difference in the reduction rate of COP displacement when wearing a mouthguard among participant groups. Results: COP significantly decreased in the order of untrained adults to weightlifters to gymnasts, irrespective of the mouthguard condition. The reduction rate in COP displacement after wearing a mouthguard was greatest in gymnasts. Conclusions: The effect of the mouthguard on postural control function was more pronounced in gymnasts than in untrained adults and weightlifters, and this study suggests that equalization of the occlusal state by wearing a mouthguard contributes to improving postural control function.
Journal Article
Unobserved heterogeneity in auctions
A common concern in the empirical study of auctions is the likely presence of auction-specific factors that are common knowledge among bidders but unobserved to the econometrician. Such unobserved heterogeneity confounds attempts to uncover the underlying structure of demand and information, typically a primary feature of interest in an auction market. Unobserved heterogeneity presents a particular challenge in first-price auctions, where identification arguments rely on the econometrician's ability to reconstruct from observables the conditional probabilities that entered each bidder's equilibrium optimization problem. When bidders condition on unobservables, it is not obvious that this is possible. Here we discuss several approaches to identification developed in recent work on first-price auctions with unobserved heterogeneity. Despite the special challenges of this setting, all of the approaches build on insights developed in other areas of econometrics, including those on control functions, measurement error, and mixture models. Because each strategy relies on different combinations of model restrictions, technical assumptions, and data requirements, their relative attractiveness will vary with the application. However, this varied menu of results suggests both a type of robustness of identifiability and the potential for expanding the frontier with additional work.
Journal Article
A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results
Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings.
Journal Article
Hypothermia or Machine Perfusion in Kidney Donors
In this study of three strategies — hypothermia, machine perfusion, or both — for pretransplantation preservation of kidneys from brain-dead donors, hypothermia was found to be inferior to machine perfusion.
Journal Article
Design of Adaptive Cruise Control with Control Barrier Function and Model-Free Control
This work describes the design of an adaptive cruise control (ACC) applied to a realistic automotive simulation model, considering both upper- and lower-level controllers. The upper-level controller provides a desired acceleration/deceleration to a host vehicle to maintain a safe distance related to a leader vehicle or to track a desired cruise speed otherwise. On the other hand, the lower-level controller provides control signals to the throttle and brake pedals of the host vehicle aiming to track the desired acceleration/deceleration setpoint from the upper-level controller. For the upper-level controller, we consider a control framework that unifies the stability/tracking objective, expressed as a control Lyapunov function (CLF), the safety constraint, expressed as a control barrier function (CBF), and the comfort constraint, by means of a quadratic programming (QP), where safety must be prioritized. The lower-level controller is implemented considering a model-free control. The results, obtained by numerical simulations, demonstrate that the safe distance between the vehicles is ensured and the desired cruise speed is tracked adequately. Therefore, the stability/tracking objective and the safety and comfort constraints, related to the upper-level controller, are properly satisfied. The lower-level controller tracks the desired acceleration/deceleration demanded by the upper-level controller with good performance.
Journal Article
A Hamiltonian Neural Differential Dynamics Model and Control Framework for Autonomous Obstacle Avoidance in a Quadrotor Subject to Model Uncertainty
Establishing precise and reliable quadrotor dynamics model is crucial for safe and stable tracking control in obstacle environments. However, obtaining such models is challenging, as it requires precise inertia identification and accounting for complex aerodynamic effects, which handcrafted models struggle to do. To address this, this paper proposes a safety-critical control framework built on a Hamiltonian neural differential model (HDM). The HDM formulates the quadrotor dynamics under a Hamiltonian structure over the SE(3) manifold, with explicitly optimizable inertia parameters and a neural network-approximated control input matrix. This yields a neural ordinary differential equation (ODE) that is solved numerically for state prediction, while all parameters are trained jointly from data via gradient descent. Unlike black-box models, the HDM incorporates physical priors—such as SE(3) constraints and energy conservation—ensuring a physically plausible and interpretable dynamics representation. Furthermore, the HDM is reformulated into a control-affine form, enabling controller synthesis via control Lyapunov functions (CLFs) for stability and exponential control barrier functions (ECBFs) for rigorous safety guarantees. Simulations validate the framework’s effectiveness in achieving safe and stable tracking control.
Journal Article