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This paper considers a discrete-time linear time invariant system in the presence of Gaussian disturbances/noises and sparse sensor attacks. First, we propose an optimal decentralized multi-sensor information fusion Kalman filter based on the observability decomposition when there is no sensor attack. The proposed decentralized Kalman filter deploys a bank of local observers who utilize their own single sensor information and generate the state estimate for the observable subspace. In the absence of an attack, the state estimate achieves the minimum variance, and the computational process does not suffer from the divergent error covariance matrix. Second, the decentralized Kalman filter method is applied in the presence of sparse sensor attacks as well as Gaussian disturbances/noises. Based on the redundant observability, an attack detection scheme by the χ2 test and a resilient state estimation algorithm by the maximum likelihood decision rule among multiple hypotheses, are presented. The secure state estimation algorithm finally produces a state estimate that is most likely to have minimum variance with an unbiased mean. Simulation results on a motor controlled multiple torsion system are provided to validate the effectiveness of the proposed algorithm.

This paper proposes a disturbance observer (DOB)-based robust force control framework for tendon-sheath mechanisms (TSMs) that transmit tension forces from the proximal to the distal end. A detailed physical model of the TSM system, where a motor actuates the tendon and the output corresponds to the contact force at the robot end-effector, is developed. However, the resulting nominal model adopts a simplified representation of friction and involves significant parametric uncertainties due to the inherently complex dynamics of the tendon-sheath structure. By rigorously verifying the well-established robust stability conditions associated with DOB-based control frameworks, it is confirmed that the tendon-sheath transmission system satisfies all required assumptions and stability criteria. Furthermore, the necessary additional conditions can be readily met by appropriately designing the Q-filter, which is comparatively straightforward in practice. This validation supports the theoretical soundness and practical suitability of employing a DOB to effectively estimate and compensate for the system’s inherent parametric uncertainties and external disturbances. Numerical simulations incorporating a discrete-segment tendon model with an advanced friction dynamics formulation demonstrate significant improvements in force tracking accuracy at the tendon’s distal end compared to conventional control schemes without DOB compensation. The results highlight the robustness and effectiveness of the proposed control scheme for tendon-driven robotic systems.

In this paper, we propose systematic controller design guidelines to ensure both individual vehicle stability and string stability in cooperative adaptive cruise control (CACC)-based platoon systems, assuming a homogeneous platoon where all vehicles share identical dynamic models. We rigorously demonstrate that the limitation of conventional adaptive cruise control (ACC) in maintaining the target inter-vehicle distance can be effectively overcome by incorporating the desired acceleration of the preceding vehicle as a static feedforward input. Furthermore, by formulating transfer functions in the frequency domain, we analytically derive the conditions required to ensure both individual vehicle stability and string stability of the CACC system. Building on this insight, we propose a practical and theoretically well-founded design guideline for determining the proportional, derivative, and feedforward gains of control input under a constant time gap spacing policy. The proposed guidelines are validated through simulations conducted in a realistic platooning scenario involving multiple vehicles.

This paper proposes a practical design guideline for selecting control parameters in adaptive cruise control (ACC) systems to ensure both individual vehicle stability and string stability in vehicle following systems with homogeneous longitudinal dynamics. The primary control objective is to regulate spacing errors under a constant time-gap policy, which is commonly adopted in ACC applications. By employing a simple proportional-derivative (PD) controller, we present a clear methodology for tuning the proportional and derivative gains. The proposed approach demonstrates that string stability can be effectively achieved using this straightforward control structure, making it highly applicable for assisting practitioners in selecting appropriate parameters for real-world platooning scenarios. We provide a rigorous analysis of the necessary and sufficient conditions for selecting PD gains, along with practical guidelines for implementation. The effectiveness of the design guideline is further validated through simulations conducted in realistic driving scenarios.

In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.

Controlled drug delivery systems can provide sustained release profiles, favorable pharmacokinetics, and improved patient adherence. Here, a reservoir-style implant comprising a biodegradable polymer, poly(ε-caprolactone) (PCL), was developed to deliver drugs subcutaneously. This work addresses a key challenge when designing these implantable drug delivery systems, namely the accurate prediction of drug release profiles when using different formulations or form factors of the implant. The ability to model and predict the release behavior of drugs from an implant based on their physicochemical properties enables rational design and optimization without extensive and laborious in vitro testing. By leveraging experimental observations, we propose a mathematical model that predicts the empirical parameters describing the drug diffusion and partitioning processes based on the physicochemical properties of the drug. We demonstrate that the model enables an adequate fit predicting empirical parameters close to experimental values for various drugs. The model was further used to predict the release performance of new drug formulations from the implant, which aligned with experimental results for implants exhibiting zero-order release kinetics. Thus, the proposed empirical models provide useful tools to inform the implant design to achieve a target release profile.

Since heavy-duty trucks play an important role in logistics and platooning of those trucks improves the fuel efficiency, the platooning technology for tractor-trailer type vehicles has recently gained significant attention in the transportation sector. This paper introduces a method to guarantee the lateral string stability of a platoon comprising multiple identical articulated vehicles. The proposed controller employs the feedback linearization technique, forming a simple proportional-derivative (PD) controller augmented with a feedforward control term by receiving the preceding vehicle’s steering angle information. This study represents the first attempt to ensure the lateral string stability of tractor-trailer platoons. Simulation results show that the lateral distance deviation does not amplify toward the tail of the platoon when the PD and feedforward control gains are designed such that the magnitude of the error propagation transfer function remains less than unity.

IntroductionThe conduct of clinical research is essential during public health emergencies, including COVID-19, to characterise the natural history of the infection to inform case definitions, identify risk factors for severe disease, transmission patterns, short and long-term complications and safe and effective treatments and vaccines. Policies aimed at mitigating transmission of SARS-CoV-2 proved challenging to conduct clinical research. Here, we describe the Vital Status and Outcomes of COVID-19 (VISION) study, a hybrid no-touch and low-touch clinical research protocol following participants recently infected with SARS-CoV-2.Methods and analysisIn this prospective longitudinal no-touch and low-touch observational study of recent SARS-CoV-2 infection, participants are enrolled virtually into a no-touch online primary cohort, which collects clinical information using electronic surveys. Eligible participants are able to additionally enrol into low-touch cohorts that collect biospecimens to characterise viral and immune dynamics.Ethics and disseminationThe VISION study is approved by the UNC Biomedical Institutional Review Board. Virtual enrolment coupled with hybrid no and low-touch data collection reduces barriers to participation in clinical research while allowing for an expansive investigation of the COVID-19 disease course.

Embedding a filter is one of the simplest ways to enhance the disturbance attenuation performance of feedback control systems. In this paper, we introduce the filter-embedded disturbance observer (FDOB) and present a rigorous stability analysis of the FDOB. The proposed robust stability condition for the closed-loop system with the FDOB shows that if the filter to be embedded is stable and has zero relative degree with unity high-frequency gain, then the FDOB can be designed by simply adding the filter to a well-designed conventional disturbance observer (DOB) that guarantees closed-loop robust stability, and by adjusting the time constant of the Q-filter of the conventional DOB. It is also highlighted that the FDOB can be implemented by integrating the filter into the Q-filter of the conventional DOB, maintaining the add-on structure of the conventional DOB. In addition, it is shown that internal models of disturbances can be directly embedded into the filter of FDOB, which does not affect the design of the Q-filter. Simulation results on a motor control system are provided to validate the theoretical results.

We present a hybrid-type observer for detecting the switching time and estimating both the active mode and the states of continuous-time switched linear systems. The systems under consideration have external inputs and are affected by unknown disturbances. In addition, noise corrupts the output measurements. In this setting the switching cannot be detected immediately, and thus, this paper presents a condition that relates the amount of delay to the sizes of the unknown disturbances/noises, the external inputs, and the states, and the strength of the observability. Once the condition is satisfied, the proposed observer and algorithm return the exact active mode and approximate state information of the switched system. A numerical example is also presented to show the performance of our algorithm..