In this study, the problem of adaptive multi-dimensional Taylor network (MTN) control for single-input single-output (SISO) uncertain stochastic non-linear systems is investigated. How to minimise ...the influence of randomness and uncertain non-linearity for less complex computation, and how to improve the real-time performance of the controller are of great significance. To this end, a control approach based on MTN is proposed for tracking control of stochastic non-linear systems. MTNs are used to approximate the non-linearities, and the backstepping technique is employed to construct the MTN controller (MTNC). MTNC involves only addition and multiplication, featuring desirable simplicity and real-time performance. Stability of the system is guaranteed via Lyapunov approach, and it is proved that the proposed controller can guarantee that all signals of the closed-loop system remain bounded in probability, and the tracking error converges to an arbitrarily small neighbourhood around the origin. Finally, a numerical example is given to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this study has good real-time performance and control quality.
Aim
To investigate real‐world glycaemic outcomes and goals achieved by users of the MiniMed 780G advanced hybrid closed loop (AHCL) system aged younger and older than 15 years with type 1 diabetes ...(T1D).
Materials and Methods
Data uploaded by MiniMed 780G system users from 27 August 2020 to 22 July 2021 were aggregated and retrospectively analysed based on self‐reported age (≤15 years and >15 years) for three cohorts: (a) post‐AHCL initiation, (b) 6‐month longitudinal post‐AHCL initiation and (c) pre‐ versus post‐AHCL initiation. Analyses included mean percentage of time spent in AHCL and at sensor glucose ranges, insulin delivered and the proportion of users achieving recommended glucose management indicator (GMI < 7.0%) and time in target range (TIR 70‐180 mg/dl > 70%) goals.
Results
Users aged 15 years or younger (N = 3211) achieved a GMI of 6.8% ± 0.3% and TIR of 73.9% ± 8.7%, while spending 92.7% of time in AHCL. Users aged older than 15 years (N = 8874) achieved a GMI of 6.8% ± 0.4% and TIR of 76.5% ± 9.4% with 92.3% of time in AHCL. Time spent at less than 70 mg/dl was within the recommended target of less than 4% (3.2% and 2.3%, respectively). Similar outcomes were observed for each group (N = 790 and N = 1642, respectively) in the first month following AHCL initiation, and were sustained over the 6‐month observation period.
Conclusions
This real‐world analysis shows that more than 75% of users with T1D aged 15 years or younger using the MiniMed 780G system achieved international consensus‐recommended glycaemic control, mirroring the achievements of the population aged older than 15 years.
This study investigates the problem of finite-time stabilisation by state feedback for a class of non-holonomic systems in chained form with low-order non-linearities, to which the existing control ...methods are inapplicable. By introducing sign function and necessarily modifying the method of adding a power integrator, a state-feedback controller is successfully constructed. Together with a novel switching control strategy, the designed controller guarantees that the states of closed-loop system are regulated to zero in a finite time. A simulation example is provided to illustrate the effectiveness of the proposed approach.
•Sensori/motor network disentangled with novel closed-loop fMRI setup.•The inferior olive seems to play a modulating role in essential tremor.•Sensorimotor network function related to voluntary ...movement in ET was normal.•PD patients showed less motor-related activity in the cerebellum and basal ganglia.
Tremor is thought to be an effect of oscillatory activity within the sensorimotor network. To date, the underlying pathological brain networks are not fully understood. Disentangling tremor activity from voluntary motor output and sensorimotor feedback systems is challenging. To better understand the intrinsic sensorimotor fingerprint underlying tremor, we aimed to disentangle the sensorimotor system into driving (motor) and feedback/compensatory (sensory) neuronal involvement, and aimed to pinpoint tremor activity in essential tremor (ET) and tremor-dominant Parkinson's disease (PD) with a novel closed-loop approach.
Eighteen ET patients, 14 tremor-dominant PD patients, and 18 healthy controls were included. An MR-compatible wrist manipulator was employed during functional MRI (fMRI) while muscle activity during (in)voluntary movements was concurrently recorded using electromyography (EMG). Tremor was quantified based on EMG and correlated to brain activity. Participants performed three tasks: an active wrist motor task, a passive wrist movement task, and rest (no wrist movement).
The results in healthy controls proved that our experimental paradigm activated the expected motor and sensory networks separately using the active (motor) and passive (sensory) task. ET patients showed similar patterns of activation within the motor and sensory networks. PD patients had less activity during the active motor task in the cerebellum and basal ganglia compared to ET and healthy controls. EMG showed that in ET, tremor fluctuations correlated positively with activity in the inferior olive region, and that in PD tremor fluctuations correlated positively with cerebellar activity.
Our novel approach with an MR-compatible wrist manipulator, allowed to investigate the involvement of the motor and sensory networks separately, and as such to better understand tremor pathophysiology. In ET sensorimotor network function did not differ from healthy controls. PD showed less motor-related activity. Focusing on tremor, our results indicate involvement of the inferior olive in ET tremor modulation, and cerebellar involvement in PD tremor modulation.
In this study, an adaptive boundary control is presented for vibration suppression of an axially moving belt system. First, the infinite-dimensional model of the belt system including the dynamics of ...high acceleration/deceleration and distributed disturbance is derived by utilising the extended Hamilton's principle. Subsequently, by using Lyapunov's synthesis method and an adaptive technique, an adaptive boundary control is developed to suppress the belt's vibration and compensate for the system parametric uncertainties. With the proposed control, the stability of the closed-loop system and the uniform boundedness of all closed-loop signals are both ensured. Besides, the S-curve acceleration/deceleration method is adopted to plan the belt's axial speed and the disturbance observer is used to mitigate the effects of unknown boundary disturbance. Finally, the control performance of the closed-loop system is successfully demonstrated through simulations.
The stability of two one-link flexible arms for grasping and orientation control of an object is studied. Flexible arms are modelled by Euler–Bernoulli beam model and the overall system is ...represented by a hybrid partial differential equation (PDE)–ordinary differential equation (ODE) model. The authors' primary concern is the stability analysis of this hybrid PDE–ODE model. In particular, they use the frequency domain method and prove the exponential stability of this system under their previously proposed boundary controller. In addition, they discuss the robustness of the closed-loop system with respect to the several disturbances including disturbances distributed over the arms and disturbances acting at boundaries. Finally, simulation results are presented to investigate the theoretical results.
This article is concerned with a novel data-driven bias-eliminated subspace identification approach for closed-loop systems. Compared with the existing methods, the proposed method first proposes to ...utilize the coprime factorization of the controller to construct an instrumental variable uncorrelated with noise under closed-loop conditions. Furthermore, it can reliably eliminate the pole estimation bias due to the correlation between inputs and noise under feedback control. More importantly, the proposed method establishes a general framework for both open-loop and closed-loop system identification. Performance comparisons with two other closed-loop methods are made from many different aspects. Finally, the performance of the identified system is again demonstrated in the vehicle lateral dynamic system.
Physical activity is a major challenge to glycemic control for people with type 1 diabetes. Moderate-intensity exercise often leads to steep decreases in blood glucose and hypoglycemia that ...closed-loop control systems have so far failed to protect against, despite improving glycemic control overall.
Fifteen adults with type 1 diabetes (42 ± 13.5 years old; hemoglobin A
6.6% ± 1.0%; 10F/5M) participated in a randomized crossover clinical trial comparing two hybrid closed-loop (HCL) systems, a state-of-the-art hybrid model predictive controller and a modified system designed to anticipate and detect unannounced exercise (APEX), during two 32-h supervised admissions with 45 min of planned moderate activity, following 4 weeks of data collection. Primary outcome was the number of hypoglycemic episodes during exercise. Continuous glucose monitor (CGM)-based metrics and hypoglycemia are also reported across the entire admissions.
The APEX system reduced hypoglycemic episodes overall (9 vs. 33;
= 0.02), during exercise (5 vs. 13;
= 0.04), and in the 4 h following (2 vs. 11;
= 0.02). Overall CGM median percent time <70 mg/dL decreased as well (0.3% vs. 1.6%;
= 0.004). This protection was obtained with no significant increase in time >180 mg/dL (18.5% vs. 16.6%,
= 0.15). Overnight control was notable for both systems with no hypoglycemia, median percent in time 70-180 mg/dL at 100% and median percent time 70-140 mg/dL at ∼96% for both.
A new closed-loop system capable of anticipating and detecting exercise was proven to be safe and feasible and outperformed a state-of-the-art HCL, reducing participants' exposure to hypoglycemia during and after moderate-intensity physical activity. ClinicalTrials.gov NCT03859401.
Recent studies have shown that the reactivation of specific memories during sleep can be modulated using external stimulation. Specifically, it has been reported that matching a sensory stimulus ...(e.g., odor or sound cue) with target information (e.g., pairs of words, pictures, and motor sequences) during wakefulness, and then presenting the cue alone during sleep, facilitates memory of the target information. Thus, presenting learned cues while asleep may reactivate related declarative, procedural, and emotional material, and facilitate the neurophysiological processes underpinning memory consolidation in humans. This paradigm, which has been named targeted memory reactivation, has been successfully used to improve visuospatial and verbal memories, strengthen motor skills, modify implicit social biases, and enhance fear extinction. However, these studies also show that results depend on the type of memory investigated, the task employed, the sensory cue used, and the specific sleep stage of stimulation. Here, we present a review of how memory consolidation may be shaped using noninvasive sensory stimulation during sleep.
The reactivation of specific memories during sleep can be modulated using external stimulation, e.g. by matching a sensory stimulus with target information during wakefulness, and then presenting the cue alone during sleep. Presenting learned cues while asleep may facilitate the neurophysiological processes underpinning memory consolidation in humans. Here we present a review of how memory consolidation may be shaped using non‐invasive sensory stimulation during sleep.
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