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In a closed-loop supply chain, the reuse of spare parts from returned systems is a recovery process referred to as spare parts harvesting. The unpredictability of the parts supply capacity from returned systems is a challenge in healthcare industry as product returns depend on several factors and regulatory and legal requirements must be respected. The focus of this paper is to provide a forecasting method of harvested parts supply capacity in healthcare industry that combines statistical methods with field information and business knowledge to provide an informed forecast. We propose a dynamic forecasting process that gets updated monthly employing TSB-Croston, 12-month moving average, ARIMA, ARIMA with seasonality, and a new business knowledge based model. A prediction method of the inventory state changes is introduced. The forecasters judgment is transformed into validation rules for an automatic forecast adjustment. This method is evaluated on more than 1400 time series with intermittent behaviour representing General Electric Healthcare spare parts harvesting history. We evaluate the performance of our method compared to each tested model using a modified MAPE, MAE, MSE, and RMSE. By means of the designed method, the forecast performance is improved compared to all tested models. [ABSTRACT FROM AUTHOR]

Tower cranes are typical underactuated systems, characterized by high-state coupling and lack of available control inputs, resulting in major challenges for the dynamics analysis. A dynamic model of tower cranes without simplifications is established, where the nonlinearities, unknown frictions, and wind disturbances are emphatically considered. Based on the developed model, an adaptive robust sliding mode control (ARSMC) scheme is proposed, which can achieve accurate payload positioning and sufficient swings suppression, even in the presence of unknown frictions and wind disturbances. Specifically, a sliding mode surface and a suppression function are designed to eliminate payload swings; a sliding mode convergence law is constructed to alleviate the chattering problem; the robustness of the controller is enhanced by designing an estimation strategy of wind disturbances; an effective parameter estimation is presented to improve the adaptive ability of unknown parameters. The stability of the closed-loop system is proved by utilizing the Lyapunov technique and LaSalle's invariance principle. Finally, the effectiveness of the tower crane model and the superiority of the ARSMC are verified by multiple comparative simulations. [ABSTRACT FROM AUTHOR]

Hybrid closed-loop (HCL) systems remain underexplored within aviation, and as atmospheric pressure changes can independently affect insulin pumps and continuous glucose monitoring readings, this preliminary study assessed the feasibility of HCL safety evaluation, in both fasting and post-prandial states, by using hypobaric chamber to simulate flights. Participants with type 1 diabetes and on HCL were studied: Medtronic Guardian 4-Medtronic 780G-SmartGuard (n = 4), Dexcom G6-Omnipod DASH-Android APS (n = 1), and Dexcom G6-Ypsomed Pump-CamAPS (n = 1). Flight cabin pressures of 550 mmHg and 750 mmHg were simulated in a hypobaric chamber. Seven-hundred-50 glucose measurements were taken, with glucose levels demonstrating a stable decline to 4 mmol/L during fasting. To maintain a tight fasting and post-prandial glucose range across the different pressure settings, the HCL administered insulin as expected. While not demonstrating any apparent issues, repeating flight simulation protocol with other systems, examining longer flights, and undertaking larger, powered randomised controlled trials can confirm their safety in aviation. [ABSTRACT FROM AUTHOR]

Background: Automated insulin delivery (AID) is widely available to people with type 1 diabetes (T1D), providing superior glycemic control versus traditional methods. The next generation of AID devices focus on minimizing user/device interactions, especially around meals ("full closed loop," [FCL]). Our goal was to assess the postprandial glycemic impact of the bolus priming system (BPS), an algorithm delivering fixed insulin doses based on the likelihood of a meal having occurred, in conjunction with UVA's latest AID. Method: Eleven adults with T1D participated in a supervised randomized-crossover trial assessing glycemic control during two 24-h sessions with identical meals and activity—with and without BPS. On the day in-between study sessions, participants underwent food and activity challenges to test BPS safety and robustness. Continuous glucose monitor (CGM) outcomes and total insulin doses were assessed overall and following meals with potential for BPS to dose additional insulin (CGM >90 mg/dL for 1 h prior). Results: Daytime CGM outcomes were similar with and without BPS: time-in-range (TIR) 70–180 mg/dL 70.6% [62.2–76.5] versus 65.7% [58.6%–80.6%]; time-below-range <70 mg/dL 0% [0–2.1] versus 0% [0–1.3]; respectively. Insulin delivery during 3 h postprandial was indistinguishable 33.5 U [26.4–47.0] versus 35.7 U [28.7–44.9]. Among 43 out of 66 meals with potential to trigger BPS (24/19 BPS/no-BPS), postprandial incremental area-under-the-curve (iAUC) was lower for BPS versus no-BPS (2530 ± 1934 versus 3228 ± 2029, P = 0.047), but CGM outcomes were inconclusive: 4-h-TIR 51.2% [19.8–83.3] versus 40.2% [20.8–56.3] (P = 0.24). There were no severe adverse events. Conclusion: While there was no difference in TIR, when BPS was active an improved postprandial AUC in FCL was obtained via earlier insulin injection. [ABSTRACT FROM AUTHOR]

The paper investigates the finite-time adaptive consensus control of nonlinear multi-agent systems (MASs) by output-feedback. During the process of control design, the fuzzy logic system (FLS) is employed to approximate nonlinear function, as well as constructing a fuzzy state observer to estimate unmeasured states. Combining the dynamic surface control (DSC) with adaptive backstepping method conquers the complexity explosion issue. Then, semi-global practical finite-time stability (SGPFS) for closed-loop system is obtained under arbitrary switching communication topologies. All the signals of the overall system are uniformly ultimately bounded (UUB). Finally, the availability of developed control approach will be demonstrated through a simulation. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive path-tracking control of autonomous ground vehicles with sideslip effects and time-varying input delays. To handle the problem of unknown time-varying input delays, the vehicle kinematic model is transformed into a novel chain model, and a delay-based auxiliary integral term is introduced for the estimation of the unknown terms caused by time-varying delays. To avoid modeling errors caused by existing linear approximation methods, a new adaptive path-tracking control strategy is proposed, such that the optimal tracking performance is achieved by appropriately adjusting certain design parameters. In addition, the inherent complexity explosion issue is avoided with the aid of a boundary estimation strategy. All signals of the closed-loop systems are guaranteed to be bounded. Simulation results illustrate the effectiveness of the method proposed. [ABSTRACT FROM AUTHOR]

This paper aims to investigate input-to-state stability (ISS) of nonlinear impulsive switched systems under mode-dependent event-triggered impulsive control (MDETIC) method. A novel mode-dependent event-triggered mechanism (MDETM) is devised, where triggering impulsive instants are determined by some predesigned event conditions. Different from existing MDETM, there are two types of impulsive behavior involved, including the impulsive behavior of system itself and event-triggered one. The novel MDETM not only reduces communication cost and energy consumption but also excludes "Zeno behavior." Then, the ISS criteria of the closed-loop system are established based on MDETIC strategy, admissible edge-dependent average dwell time (AED-ADT), and admissible edge-dependent average impulsive interval (AED-AII) methods. Finally, two examples are given to verify the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This research presents a predefined-time control strategy for the trajectory tracking of a space manipulator subjected to parametric uncertainty and time-varying disturbance. Firstly, a nonlinear disturbance observer with predefined time convergence is constructed to achieve accurate estimation of the lumped disturbance without requiring any prior information. Subsequently, a unique predefined-time terminal sliding surface containing arctan function is proposed, which avoids the singularity problem that exists in traditional terminal sliding surfaces. Afterwards, a novel robust terminal sliding mode control law is designed based on the estimated knowledge. The developed controller ensures the predefined time stability of the closed-loop system, and the convergence time's upper bound can be explicitly defined in advance through two specific parameters for any initial conditions. Finally, numerical simulations and comparative tests verify the effectiveness and superiority of the suggested controller. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel control design framework for nonlinear dynamical systems that is not based on traditional Lyapunov approach. Specifically, the Iterative Control Framework (ICF) is designed to guarantee the convergence of the closed-loop system state to zero without a priori verification of Lyapunov-like conditions. The approach is based on a numerical routine that reconfigures the control input vector at each iteration in such a way that when the control input is applied to the system, the system trajectory reaches closer to the desired state. This allows the control of real-world systems regardless of complexity in model nonlinearities or system dimensionality. Here we apply this framework to spacecraft control during the final stage of its rendezvous with another space vehicle, that is, docking. Since spacecrafts are controlled by impulsive thrusters with very short activation time, this application presents an ideal case study for ICF. We show that all states of the dynamical model are driven to the desired equilibrium and run Monte Carlo simulations to demonstrate the robustness of the approach. [ABSTRACT FROM AUTHOR]

A new method is proposed for robust partial quadratic eigenvalue assignment problem (RPQEAP). We first derive an expression of the solution to partial quadratic eigenvalue assignment problem, which yields Schur decomposition associated with quadratic closed-loop system. Then normality departure is used to measure the robustness of quadratic closed-loop system. On these grounds, our method is proposed for RPQEAP such that the normality departure is as small as possible. The proposed method is effective either for distinct prescribed eigenvalues or for repeated prescribed eigenvalues. It directly deals with quadratic control system and avoids the linearization of quadratic eigenproblem. Moreover, our method does not need the unchanged eigenpairs of the open-loop system and the inversion of mass matrix M. [ABSTRACT FROM AUTHOR]

In this article, I design a predictor-based neural network (NN) controller for unmanned aerial vehicles (UAVs) with input quantization to address the trajectory tracking problem in the presence of time-varying disturbances caused by aerodynamics and external environment. The NN with a state predictor (SP) is employed in the controller design to improve transient performance without high-frequency oscillations and address the problem of instability caused by the time-varying disturbances. Additionally, the prediction errors from the SP are used to update the learning rate of the NN, resulting in smoother and faster learning responses. Furthermore, a hysteresis quantizer is employed to discretize signals and reduce the transmission burden on digital hardware, which can enhance the suitability of the system for practical implementation. Based on the Lyapunov method, the closed-loop system of the UAV achieves input-to-state stability (ISS). Finally, to validate and assess the performance and effectiveness of our proposed control method, I present and analyze both simulation results and experimental results from real-world applications. [ABSTRACT FROM AUTHOR]

The present paper considers a cascade of heat-heat system with different reaction coefficients, where the actuator is presented at the arbitrary position $ \xi $ in the domain $ (0,1) $ with pointwise feedback heat flux. A sufficient and necessary condition regarding two reaction coefficients of the cascaded heat-heat model is derived to guarantee the controllability of the cascaded system. Based on the modal decomposition approach, a pointwise feedback controller is introduced to stabilize the unstable coupled system if $ \xi\in(0, 1) $ and satisfies $ \xi\neq\frac{2k+1}{2n_2} $ for any integers $ n_2\in \mathbb{N}^+ $, $ k\in\{0,1,2,\cdots,n_2-1\}. $ Via the Lyapunov method, sufficient conditions are derived for guaranteing exponential stability and well-posedness of the closed-loop systems. Numerical simulation demonstrates that the proposed control scheme effectively stabilizes the performance of the cascaded system. [ABSTRACT FROM AUTHOR]

The field of bioelectronic medicine has advanced rapidly from rudimentary electrical therapies to cutting-edge closed-loop systems that integrate real-time physiological monitoring with adaptive neuromodulation. Early innovations, such as cardiac pacemakers and deep brain stimulation, paved the way for these sophisticated technologies. This review traces the historical and technological progression of bioelectronic medicine, culminating in the emerging potential of closed-loop devices for multiple disorders of the brain and body. We emphasize both invasive techniques, such as implantable devices for brain, spinal cord and autonomic regulation, while we introduce new prospects for non-invasive neuromodulation, including focused ultrasound and newly developed autonomic neurography enabling precise detection and titration of inflammatory immune responses. The case for closed-loop non-invasive autonomic neuromodulation (incorporating autonomic neurography and splenic focused ultrasound stimulation) is presented through its applications in conditions such as sepsis and chronic inflammation, illustrating its capacity to revolutionize personalized healthcare. Today, invasive or non-invasive closed-loop systems have yet to be developed that dynamically modulate autonomic nervous system function by responding to real-time physiological and molecular signals; it represents a transformative approach to therapeutic interventions and major opportunity by which the bioelectronic field may advance. Knowledge gaps remain and likely contribute to the lack of available closed loop autonomic neuromodulation systems, namely, (1) significant exogenous and endogenous noise that must be filtered out, (2) potential drift in the signal due to temporal change in disease severity and/or therapy induced neuroplasticity, and (3) confounding effects of exogenous therapies (e.g., concurrent medications that dysregulate autonomic nervous system functions). Leveraging continuous feedback and real-time adjustments may overcome many of these barriers, and these next generation systems have the potential to stand at the forefront of precision medicine, offering new avenues for individualized and adaptive treatment. [ABSTRACT FROM AUTHOR]

All cells in the human body, including cancer cells, possess specific electrical properties crucial for their functions. These properties are notably different between normal and cancerous cells. Cancer cells are characterized by autonomous oscillations and damped electromagnetic field (EMF) activation. Cancer reduces physiological variability, implying a systemic disconnection that desynchronizes bodily systems and their inherent random processes. The dynamics of heart rate, in this context, could reflect global physiological network instability in the sense of entrainment. Using a medical device that employs an active closed-loop system, such as administering specifically modulated EMF frequencies at targeted intervals and at low energies, we can evaluate the periodic oscillations of the heart. This procedure serves as a closed-loop control mechanism leading to a temporary alteration in plasma membrane ionic flow and the heart's periodic oscillation dynamics. The understanding of this phenomenon is supported by computer simulations of a mathematical model, which are validated by experimental data. Heart dynamics can be quantified using difference logistic equations, and it correlates with improved overall survival rates in cancer patients. [ABSTRACT FROM AUTHOR]

Due to the rising price and limited resource supply chain of Li [NixMnyCoz]O2 (x + y + z = 1) (NMC) cathode material, lithium-ion battery (LIB) recycling technologies have been emerging as the best solution to address the price issue. Mainly, conventional hydrometallurgy processes have been applied to the LIB recycling field in recognition of its value. One remarkable advantage of the hydrometallurgy method is that it serves as a bridge to enable the Hydro-to-Cathode® method. However, using recycled raw materials in the production of precursor cathode materials needs to be studied in parallel with the impurity (dopant) effect. The insufficient selective impurity removal technology leads to unexpected electrochemical properties in the final NMC cathode active material, which can be doped by several different impurities. Consequently, scrutinizing dopant elements (inorganic and organic) is critical if we want to consider the Hydro-to-Cathode® method as a major recycling process of NMC cathode material. [ABSTRACT FROM AUTHOR]

Decreasing the position error and control torque is important for the coordinate control of a modular unmanned system with less communication burden between the sensor and the actuator. Therefore, this paper proposes event-trigger reinforcement learning (ETRL)-based coordinate control of a modular unmanned system (MUS) via the nonzero-sum game (NZSG) strategy. The dynamic model of the MUS is established via joint torque feedback (JTF) technology. Based on the NZSG strategy, the existing coordinate control problem is transformed into an RL issue. With the help of the ET mechanism, the periodic communication mechanism of the system is avoided. The ET-critic neural network (NN) is used to approximate the performance index function, thus obtaining the ETRL coordinate control policy. The stability of the closed-loop system is verified via Lyapunov's theorem. Experiment results demonstrate the validity of the proposed method. The experimental results show that the proposed method reduces the position error by 30% and control torque by 10% compared with the existing control methods. [ABSTRACT FROM AUTHOR]

This study explores the problem of finite-time resilient control for periodic piecewise polynomial time-varying systems in the face of parameter uncertainties, time-varying state delays and external disturbances. Particularly, the considered system is characterized by dividing the fundamental period of periodic systems into numerous subintervals, each of which can be expressed by using matrix polynomial functions. The foremost intention of this work is to lay out a resilient controller such that the resulting closed-loop system is finite-time bounded and satisfies a mixed H ∞ and passivity performance index. Furthermore, by constructing a periodic piecewise time-varying Lyapunov–Krasovskii functional, a delay-dependent sufficient condition is established in line with Wiritinger's inequality and matrix polynomial lemma to guarantee the needed outcomes of the system under study. Following this, the gain matrix of the devised controller can be calculated by solving the established constraints. As a final step, we conclude with a numerical example that validates the potential and importance of the theoretical discoveries and the developed control scheme. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of event-triggered control (ETC) for vertical take-off and landing (VTOL) aircraft systems under actuator saturation. By introducing the VTOL system with saturated actuators, a composite quadratic Lyapunov function (CQLF) approach is first proposed to describe the problem of the event triggering mechanism. The proposed transfer mechanism not only further saves communication resources, but also further suppresses the conservatism of the attraction domain estimation. Then, sufficient conditions are established via linear matrix inequality (LMI) by incorporating new event triggering mechanism condition and prescribed passive performance metrics under the closed-loop system that is asymptotically stable and strictly passive, respectively. Finally, the method proposed in this paper can effectively reduce the number of triggers and expand the domain of attraction. The validity and feasibility of the obtained results are demonstrated by two example simulations. [ABSTRACT FROM AUTHOR]

In this article, we study an event-triggered asymptotic tracking control problem for a class of networked nonlinear systems with unmeasurable states. In contrast to the majority of existing event-triggered control results, where only the input or output signal is triggered, the design problem of a dual-channel event-triggered mechanism is studied to achieve a more comprehensive saving of communication resources. Subsequently, in order to reconstruct system states, a continuous-discrete observer that can achieve asymptotic convergence of estimation errors is constructed based on event-triggered output. Then, an event-triggered asymptotic tracking control scheme is introduced through Levant differentiators, filtered error compensation signals, and the backstepping technique. The Levant differentiators not only address the challenge of computational complexity explosion but also effectively resolve the problem of controller segmentation continuity. The control scheme has been proven to maintain all signals in the closed-loop system bounded and achieve zero tracking error as time approaches infinity. Subsequently, numerical simulations are conducted to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this article, an adaptive event-triggered bounded control strategy is proposed for a class of high-order uncertain switched nonlinear systems with full-state time-varying constraints under average dwell time switching rule. In order to achieve the boundedness of the control signal, the projection operator is introduced. At the same time, the high-order log-type time-varying barrier Lyapunov function method is chosen to ensure that the desired output and states of the systems do not violate the relevant constraints. In addition, the improved event-triggered control strategy effectively reduces the transmission burden and saves the resource cost. The stability analysis shows that the proposed scheme achieves the ultimate boundedness of all signals in the closed-loop systems and the states of the systems do not violate the corresponding constraints. It should be noted that the proposed controller has a known bound and this bound can be ensured by the rectification of the feedback control gain. Finally, the simulation results verify the effectiveness of the control method. [ABSTRACT FROM AUTHOR]

Due to the influence of material characteristics and engineering imperfections, the residual magnetic fields including static and dynamic field in a lightweight magnetically shielded room (MSR) present non-uniform distribution characteristic. To effectively reduce the residual static field, a non-uniform field compensation method based on distributed coils has been proposed. This method takes the L2-norm of the magnetic field at the target array points as the objective function, to optimize the compensation current in each of the designed distributed coils, achieving non-uniform field compensation. To further achieve compensation for non-uniform residual dynamic field, a closed-loop control system containing a voltage divider and multi-channel amplifiers is designed in this paper. Additionally, the coil constant of the distributed differential coils and the initial magnetic field distribution vector for dynamic compensation are redefined. In conjunction with a PI controller, dynamic compensation is achieved using a single optically pumped magnetometer as the feedback component. The experimental results indicate that the average dynamic field decreased from 376.75 pT to 27.80 pT over the central volume of (300 mm)3 in MSR, achieving a near-zero magnetic environment. This method has universal applicability for compensating non-uniform residual field under different working conditions. [ABSTRACT FROM AUTHOR]

Different disciplines are developing various methods for determining and dealing with uncertainties in complex systems. The constrained disorder principle (CDP) accounts for the randomness, variability, and uncertainty that characterize biological systems and are essential for their proper function. Per the CDP, intrinsic unpredictability is mandatory for the dynamicity of biological systems under continuously changing internal and external perturbations. The present paper describes some of the parameters and challenges associated with uncertainty and randomness in biological systems and presents methods for quantifying them. Modeling biological systems necessitates accounting for the randomness, variability, and underlying uncertainty of systems in health and disease. The CDP provides a scheme for dealing with uncertainty in biological systems and sets the basis for using them. This paper presents the CDP-based second-generation artificial intelligence system that incorporates variability to improve the effectiveness of medical interventions. It describes the use of the digital pill that comprises algorithm-based personalized treatment regimens regulated by closed-loop systems based on personalized signatures of variability. The CDP provides a method for using uncertainties in complex systems in an outcome-based manner. [ABSTRACT FROM AUTHOR]

Aims: The study was aimed at assessing the role of the MiniMed780G system of glycemic control before, during, and after Ramadan among people with Type 1 diabetes (PwT1D). Methods: This is a single‐center retrospective analysis of MiniMed780G system users aged 14 years and above whose glycemic profiles were collected from February 21 to May 20, 2023, which corresponds to the Hijri months of Sha'ban, Ramadan, and Shawwal 1444/1445. Data was collected, processed, and analyzed in the framework of the Medtronic Galaxy service of the One Hospital Clinical Service (OHCS) program in Dallah Hospital, Riyadh, Saudi Arabia. Data from 43 PwT1D (24 females, mean age 30 ± 11 years with 14 ± 8 years from diabetes onset) using the MiniMed780G system were collected. Results: Overall, the 3‐month (Sha'ban, Ramadan, and Shawwal) mean sensor glucose (SG), time in range (TIR) (70–180 mg/dL), time below range (TBR) (54–69 mg/dL and < 54 mg/dL), time above range (TAR) (180–250 mg/dL and > 250 mg/dL), and glucose management indicator (GMI) showed no statistical differences within the three periods. No differences in insulin total daily dose have been detected, and no diabetic ketoacidosis (DKA) or severe hypoglycemia events occurred. Conclusion: The use of the MiniMed780G system is safe with favorable glycemic outcomes across nonfasting and fasting months. [ABSTRACT FROM AUTHOR]

A novel non-backstepping output feedback control approach, called as the dual-gain scaling approach, is proposed by combining the extended Lyapunov matrix inequalities with dual-domination idea. This approach provides partially decentralised adaptive output feedback controllers with three event-triggered mechanisms to achieve the global practical tracking of a family of uncertain large-scale nonlinear systems subject to unknown control coefficients and strongly interconnected nonlinearities with output-polynomial growth rate. The dual gains are embedded in the observers and controllers, which can effectively compensate for time-varying control coefficients and unknown constant growth rate multiplied by output-polynomial function. Three different threshold schemes including fixed threshold, relative threshold and time-varying threshold are introduced to save communication resources. The stability analysis shows that the solutions of the closed-loop system are globally uniformly bounded and the tracking error converges to a preset compact set after a finite time; also, there will be no zeno behaviour in the closed-loop response. [ABSTRACT FROM AUTHOR]

This paper studies the problem of global output-feedback tracking control for a class of uncertain nonlinear systems. The system studied in this paper has unknown time-varying control coefficients and unknown reference signal. Notably, the nonlinearities of the system are bounded by the lower triangular linear unmeasured states multiplying the unknown constant, the polynomial-of-output and the polynomial-of-input growth rates, which indicates the presence of serious uncertainties. Motivated by the closely related works, by combining the ideas of universal control and deadzone with backstepping technique, this paper presents a new adaptive tracking control scheme based on two dynamic high-gains in the new forms. The proposed control scheme ensures that the tracking error converges to a specified arbitrarily small interval range after a finite time while the state of the resulting closed-loop system is globally bounded. Finally, the effectiveness of the control scheme is verified by an illustrative example. [ABSTRACT FROM AUTHOR]

For the nonlinear systems with input delay, an adaptive fixed-time tracking control strategy based on multi-dimensional Taylor network (MTN) is proposed for the first time. First, to address the main challenge brought by input delay, an auxiliary system is constructed, which transforms the input delay systems into non-delay systems. Second, the MTNs are introduced into the backstepping design process, which reduce the design difficulty by approximating unknown nonlinear functions. Thus, a control scheme subject to low complexity is obtained. Third, aside from ensuring that the tracking error converges within a small neighbourhood of the origin within a fixed-time, the designed control scheme not only makes all signals in the closed-loop system remain bounded, but also avoids the problem of finite-time control relying on initial state. Finally, three simulations are given to prove the feasibility and superiority of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The paper studied the finite-time semi-global stabilisation problems for a class of nonlinear systems with a novel polynomial growth condition. By using some key properties of a class of parametric Lyapunov equations and constructing time-varying Lyapunov-like functions, two time-varying high-gain controllers, where scalar time-varying functions are generated by differential equations, are designed. Both state feedback and observer-based output feedback are considered. It is shown that the proposed methods can achieve finite-time semi-global stabilisation for closed-loop systems and the controls are bound. Two numerical examples verify the effectiveness of the established results. [ABSTRACT FROM AUTHOR]

This paper considers the stability of the one-dimensional parabolic system, where one end changes over time and the other is the control end with the external disturbance. Firstly, by the boundary immobilisation method, the displacement change of the system boundary is transferred into the equation so that the original system is transformed into a system with fixed boundaries. Secondly, by combining the backstepping transformation and the sliding mode control method, the feedback control is proposed to compensate the instability of the system itself and reject the matched disturbance. Then, the resulting closed-loop system will be in the form of $ \mathcal{A}+ \mathcal{B}(\tau)+ \mathcal{C} D(\tau) $ A + B (τ) + C D (τ) , where $ \mathcal{A} $ A generates a $ C_0 $ C 0 semigroup, $ \mathcal{B}(\tau) $ B (τ) and $ \mathcal{C} $ C are bounded and unbounded operators respectively, and $ D(\tau) $ D (τ) is the external input. The existence of the generalised solution to the closed-loop system is proved by using the eigenfunction expansion of the system solution. By the Lyapunov method, the closed-loop system is shown to be exponentially stable. Finally, some numerical simulations are presented to illustrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper explores the adaptive finite-time neural control issue for nonlinear systems with input dead zone and output hysteresis in nonstrict-feedback form. The unknown functions are estimated by employing the radial basis function neural networks (RBFNN) approach. A systematic adaptive finite-time control method is introduced using the backstepping technique and neural network approximation properties. The stability of the system is also examined by using semi-global practical finite-time stability theory. The established control approach guarantees the boundedness of all signals within the closed-loop system, enabling the system output to accurately follow the desired signal within a finite time framework while maintaining a small and bounded tracking error. Finally, simulation results are shown to demonstrate the efficacy of the suggested strategy. [ABSTRACT FROM AUTHOR]

This paper is concerned with the cooperative control issue of virtually coupled high-speed trains (VCHSTs) under an adaptive dynamic programming (ADP) framework, where a dynamic event-triggered mechanism is employed to govern the communication between sensors and observers. A learning-based observer, equipped with a robust term, is exploited to mitigate the effect of the unknown nonlinear dynamics of the VCHSTs. Furthermore, to realise the distributed design, an auxiliary control signal is employed to simply the closed-loop system and also integrated into the cost function to handle the coupled nature of the investigated systems. The Hamilton–Jacobi–Bellman (HJB) equation is approximated by actor and critic networks in the ADP framework, which iteratively acquires the desired control strategy. By resorting to the common Lyapunov stability, some sufficient conditions are derived to achieve the desired observer gain and learning rates of NNs. Ultimately, the control scheme's efficiency is confirmed by simulations of VCHSTs. [ABSTRACT FROM AUTHOR]

This paper presents an optimal output feedback tracking control scheme for a single-link robot arm (SLRA) model, utilizing reinforcement learning (RL). Initially, a neural network (NN) state observer is developed to accurately estimate the system state. Then, an optimal output feedback controller is constructed based on the RL algorithm and the optimal backstepping control (OBC) method to effectively control the SLRA system. Subsequently, employing Lyapunov stability theory, it is demonstrated that all signals in the closed-loop system are guaranteed to remain bounded. In conclusion, a simulation case is presented to demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Exponential stabilisation is undoubtedly an essential property to study for any control system. This property is often difficult to establish for nonlinear distributed systems and even more difficult if the state of such a system is subject to a time-delay. In this context, this paper is devoted to the study of the well-posedness and exponential stabilisation problems for the one-dimensional delayed Fisher's partial differential equation (PDE) posed in a bounded interval, with homogeneous Dirichlet condition at the left boundary and controlled at the right boundary by Dirichlet condition. Based on the infinite dimensional backstepping method for the linear and undelayed corresponding case, a feedback law is built. Under this feedback, we prove that the closed-loop system is well-posed in $ L^2(0,1) $ L 2 (0 , 1) and locally exponentially stable in the topology of the $ L^2(0,1) $ L 2 (0 , 1) -norm by the use of semigroup theory relating to differential difference equations and Lyapunov–Razumikhin analysis, respectively. A numerical example that reflects the effectiveness of the proposed approach is given. [ABSTRACT FROM AUTHOR]

The usage and safety of the Boost and Ease-off features in the CamAPS FX hybrid closed-loop system were analyzed in a retrospective analysis of real-world data from 7,464 users over a 12-month period. Boost was used more frequently than Ease-off, but for a shorter duration per use. Mean starting glucose was above range for Boost (229 ± 51 mg/dL), and within range for Ease-off (114 ± 29 mg/dL). Time spent below 70 mg/dL was low during Boost periods [median (interquartile range; IQR) 0.0% (0.0, 0.5%)], and lower than during no Boost periods [2.1% (1.2, 3.4%)], while time spent above 180 mg/dL was lower during Ease-off periods (15 ± 14%) compared with no Ease-off periods (25 ± 12%). There were no episodes of severe hypoglycemia or diabetic ketoacidosis attributed to Boost or Ease-off use. Boost and Ease-off allow users to engage safely with CamAPS FX to manage their glucose levels during periods of more-than-usual and less-than-usual insulin needs. [ABSTRACT FROM AUTHOR]

Background: The advanced hybrid closed-loop (AHCL) algorithm combines automated basal rates and corrections yet requires meal announcement for optimal performance, which poses a challenge for some. We aimed to compare glucose control in adults with type 1 diabetes (T1D) using the MiniMedTM 780G AHCL system, utilizing simplified meal announcement versus precise carbohydrate (CHO) counting. Methods: In a study involving 14 adults with T1D, we evaluated glycemic control during a 13-week "precise phase," followed by two 3- to 4-week simplified meal announcement phases: "fixed one-step" (preset of one personalized fixed CHO amount) and "multistep" (entry of multiples of one, two, or three of these presets depending on meal size estimate). Results: The mean age was 45.7 ± 12.4, and 10 participants were male (71%). Mean baseline HbA1c was 6.8% ± 1.2% and time in range (TIR) was 67.5% ± 16.7%. Comparing the fixed one-step to the precise study phase, TIR was similar (75.4 ± 13% vs. 77.7 ± 9%, P = 0.12), and glucose management indicator (GMI) was slightly higher (6.8 ± 0.4 vs. 6.6 ± 0, P = 0.01). Furthermore, there was less level 1 and 2 hypoglycemia (1.6 ± 1% vs. 2.8 ± 2%, P = 0.03 and 0.3 ± 5% vs. 0.65 ± 1%, P = 0.08) but slightly more level 1 and 2 hyperglycemia (17.1 ± 8% vs. 15.0 ± 7%, P = 0.05 and 5.5 ± 5% vs. 3.6 ± 3%, P = 0.04). When comparing the multistep with the precise phase, GMI was identical (6.6%) and TIR superior (80.5 ± 10% vs. 77.7 ± 9%, P = 0.02). Additionally, there was less level 1 hypoglycemia (1.9 ± 1% vs. 2.8 ± 2%, P = 0.01) and a trend for less level 2 hypoglycemia (0.4 ± 0.7% vs. 0.65 ± 1%, P = 0.08). Conclusions: A simplified meal announcement strategy for adults using the MiniMed 780G system, relying on three increments of a fixed one-step CHO amount, may offer a way to improve glycemic control and ease self-care. For patients with more limitations, using one fixed one-step CHO amount could be a safe alternative to meeting most consensus glycemic targets. [ABSTRACT FROM AUTHOR]

Overhead cranes play a pivotal role in various industrial applications. This paper presents two methodologies for suppressing the payload's swing and completing the accurate positioning. The original crane model is initially transformed into a chained form. Two nonlinear controllers are devised to regulate the trolley's position and achieve the payload's anti-swing control. The first approach utilizes backstepping, extended state observer, and filter technique to effectively estimate system state and disturbance and make the closed-loop system uniformly ultimately bounded. In contrast, the second method involves sliding mode control and finite-time disturbance observer to ensure the finite-time convergence of the resulting closed-loop system and the accurate disturbance estimation. Finally, simulation results are provided to validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Research on initial errors and constraint restrictions is one of the main research directions in the field of control of uncertain robotic systems. An adaptive iterative learning control (AILC) method based on radial basis function (RBF) neural network is proposed to address the trajectory tracking problem of the long-stroke hybrid robot system with random initial errors and full state constraints. The RBF neural network is used to approximate the unknown nonlinear terms, and the network weights are updated using an iterative learning law that incorporates a projection mechanism. Additionally, a robust learning strategy is used to compensate for both the approximation error of the neural network and the external disturbances that vary with each iteration. To relax the requirement of traditional iterative learning control (ILC) for identical initial condition, an equivalent error function is constructed based on the time-varying boundary layer. The tangent-type barrier Lyapunov function (BLF) is designed to ensure that the joint position and speed of the robot system are bounded within a predetermined range. Through stability analysis based on barrier composite energy function (BCEF), it can be proved that the boundedness of all signals in the closed-loop system and the tracking error of the robot system will converge to an adjustable residual set asymptotically. Finally, through simulation experiments conducted on the MATLAB platform, the results demonstrate that the method overcomes the random initial errors of the system effectively, ensures that the system satisfies the full-state constraints, and realizes high-precision trajectory tracking. [ABSTRACT FROM AUTHOR]

This paper examines fault-tolerant quantized control for neural networks under persistent dwell-time switching, considering the presence of actuator faults and dynamic output quantization. The dynamic scaling factor (DSF) of the quantizer is designed as a piecewise function concerning the output to avoid the possibility of division by zero. To reduce conservatism, the controller is designed to combine the system model with a time scheduler constructed with a minimum time span. A sufficient condition for the asymptotic stability and L2-gain of the closed-loop system is derived using a piecewise Lyapunov functional and decoupling approach. When the condition is satisfied, the needed feedback gains and the parameter range associated with the DSF can be determined by exact mathematical expressions. For comparison, feedback gains that depend only on the system mode are also studied, and the corresponding design method is presented. The numerical simulation results demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

To identify the frequency and amplitude of a periodic signal in real-time, a novel approach termed the "Online Harmonics Extraction Approach (OHEA)" is proposed in this paper. This method employs a notch filter with an adjustable center frequency to identify the frequency of periodic signals accurately. The computation of the envelope curve and phase-sensitive detection are combined to identify the signal amplitude and smooth out transient stages. By applying the extremum-seeking method, the identified results are fed back to adjust the center frequency, forming a closed-loop system. The convergence of the identification process is analyzed qualitatively, and a parallelized multi-component structure is proposed. Simulations and experimental results on a disturbance identification system verify the effectiveness and superiority of OHEA in the real-time identification of time-varying frequency and amplitude. [ABSTRACT FROM AUTHOR]

This paper investigates an output feedback adaptive fault-tolerant tracking control for a class of nonlinear systems with system nonlinearities, sensor failures and external disturbances, in which sensor redundancy is employed to enhance measurement reliability. A sensor fusion mechanism, together with a novel history-based weighted average algorithm is first designed to fuse all sensor outputs. Then, an adaptive controller based on the sensor fusion output, a dynamic gain and a state observer is constructed to handle all the uncertainties caused by system nonlinearities, external disturbances, sensor failures and fusion mechanism. It is shown that by using the proposed scheme, the closed-loop system is stable, the sensor fusion mechanism can eliminate the effects of faulty sensors, and the real tracking error can be driven into a small compact set mainly affected by the fusion error. Experimental results are accomplished to validate the proposed scheme. • An adaptive output feedback tracking scheme with redundant sensors and sensor fusion mechanism. • A novel weighted algorithm is proposed to obtain a continuous and differentiable fusion function. • The weighting functions can regulate their values to eliminate the effects of faulty sensors. • Minority sensors can lose all effectiveness so that the sensor failure patterns are more general. [ABSTRACT FROM AUTHOR]

Control of the family of systems that can be represented in the Euler Lagrange (EL) form is both challenging from a theoretical perspective and applicable to a broad spectrum of real systems. For this type of control problem, given that any parameter estimation error and disturbances are not directly addressed, the system performance deteriorates, and stability cannot be deduced in advance. Considering these issues, this work presents the design and the corresponding analysis of a saturation function based, model-free, continuous robust controller for mechanical systems represented in the EL form. In order to avoid chattering in controller input, which is a common problem in most robust and high-gain control designs, the proposed method makes use of continuously differentiable terms. The stability of the closed-loop system is ensured via rigorous Lyapunov-based arguments. To ease the tuning of the controller gain, an adaptive gain-tuning algorithm is proposed to be applied as an add-on. The effectiveness of the controller is demonstrated by a simulation study on a twin rotor multi-input–multi-output system (TRMS) model Furthermore, the feasibility of the proposed method is then tested on an in-house built, inherently unstable, and therefore extremely sensitive mobile robotic platform. In the experimental study, satisfactory performances are attained for both the controller and the gain-tuning algorithm where less than 0. 5 ° error is obtained in roll and pitch angles and less than 1 ° error is achieved in the yaw direction. • A novel robust controller for a class of Euler–Lagrange systems is designed. • The controller requires no prior knowledge of the system dynamics. • The control gains are tuned according to novel adaptive update algorithms. • The effectiveness of the controller is verified through simulations on a TRMS model. • The controller's performance is experimentally verified on an in-house built ballbot. [ABSTRACT FROM AUTHOR]

This paper proposes a prescribed performance tracking control scheme for a category of nonlinear stochastic time-delay systems with input saturation and state asymmetric time-varying constraints. First, to solve the non-differentiable problem caused by input saturation, a smooth nonlinear function was utilized to approximate the saturation function. A nonlinear mapping technique was employed to transform the constrained problem into a bounded convergence problem. The time-delay problem was then solved by constructing the corresponding Lyapunov–Krasovskii function. The error feedback controller was constructed by combining the backstepping technique, the dynamic surface technique, the neural network approximation technique, and the adaptive control method. Based on stochastic mean-square stability theory, all signals in the closed-loop system are proven to be bounded under the designed control scheme. Also, this scheme ensures that the system states always stay within the constraint range, and the tracking error meets the prescribed performance constraint. Finally, the feasibility and superiority of the proposed control scheme were validated through simulation. [ABSTRACT FROM AUTHOR]

Model Reference Adaptive Control (MRAC) guarantees closed loop stability and desired steady state performance of dynamical systems without undue dependence upon their mathematical models. However, the applicability of MRAC may not be suitable for systems that are crucial to safety due to its poor transient response. A modified MRAC design is presented in this paper for the purpose of enhancing the transient closed loop performance of MRAC by utilizing generalized dynamic inversion (GDI) and nullspace control. Two adaptive control actions take place under the proposed control design. The first control action is responsible for enforcing the reference model dynamics, and the second control action works to enhance the transient performance of MRAC. The two control actions do not interfere with each other because they act on two orthogonally complement control subspaces. The GDI-based MRAC law forces the uncertain dynamical system to follow the reference model, and it also restricts the undesirable oscillations intensity of the closed loop transient system response. Simulations are conducted on a flying wing aircraft model to demonstrate the efficacy of the proposed design. [ABSTRACT FROM AUTHOR]

After eliminating the speed sensor in the linear induction motor (LIM) high-performance closed-loop control system, the speed feedback information is missing in the speed closed loop. The accuracy of speed observation results is affected by changes in magnetizing inductance and primary resistance. This effect can cause significant oscillations in the results of the speed sensorless control system, preventing them from converging. An enhanced model reference adaptive system (MRAS) multi-parameter parallel identification methodology based on the interconnected second-order super-twisting algorithm (SOSTA) is proposed. To enhance the system's dynamic performance, we designed an improvement to the MRAS observer based on the SOSTA, with a focus on the LIM state-space equation that considers dynamic edge-end effects. The impact of parameter alterations on the LIM system is examined. To improve speed observation accuracy and system stability, a two-parameter MRAS identification model was created. The Popov hyperstability principle was used to formulate control laws for these two parameters, ultimately enabling the identification of these two parameters. The identified values were fed back to the speed observation and control system, which reduces the coupling of these two parameters and speed. Simulation and hardware-in-the-loop experiments demonstrate that the observation system estimates speed accurately when these two parameters undergo abrupt changes within the rated speed range, enhancing the precision and robustness of the speed sensorless control system. [ABSTRACT FROM AUTHOR]

Direct energy deposition is an additive technology that can quickly manufacture irregularly shaped quartz-glass devices. Based on this technology and coaxial laser/wire feeding, open-loop tests were conducted under different process parameters. A closed-loop temperature control system was designed and built for the molten pool temperature in quartz-glass additive manufacturing. It was based on a PID (proportional–integral–derivative) control algorithm for adjusting laser power. Changes in the macroscopic morphology, microstructure, and other qualities of the final additive result before and after the temperature control of the quartz glass were examined. Relative to constant laser powers of 120 W and 140 W, the temperature control of the multi-pass single-layer lateral additives produced dense surface microstructures of the additively produced quartz glass, and the molding quality was better. [ABSTRACT FROM AUTHOR]

Radon and thoron exhalation rates from samples are estimated by the standard closed-loop technique using online radon monitors. Conventionally, the mass balance equation is formulated by considering the closed air volume of the sample chamber and the detector chamber put together. This model serves the purpose of estimating the radon/thoron exhalation rates for the prescribed pump flow rate of 1 L min−1 using RAD7 online monitor. The flow rate requirement is crucial for thoron measurement due to its short half-life. In the present work, an alternate model is proposed which simulates the dynamics of radon/thoron concentration dictated by the air entry and exit rate and brings out the effect of pump flow rate. This model is more of academic interest, where sample chamber and detector chamber are considered as two separate entities since they are separated by tubing. The mass balance equation is reformulated considering the air entry and exit in and out the individual chambers. The radon buildup in the sample chamber and detector chamber were treated separately by two coupled differential equations. The equations were numerically solved. The model reiterated the fact that the lower flow rates do not affect the buildup profile of relatively long-lived 222Rn (half-life 3.8 d) and its steady-state concentration attained in the closed air volume. However, experiments carried out for flow rates 0.3 and 0.5 L min−1 with RAD7 monitor using powdered granite sample with higher 226Ra and 232Th concentrations gave contradicting results. The radon effective removal rate was found to decrease with increase in flow rate from 0.3 to 1 L min−1. This issue was investigated, and it was speculated that the thoron interference problem might not be properly addressed for flow rates <1 L min−1. This was ascertained by observing the effective radon removal rate in the absence of thoron by conducting radon decay experiments with different flow rates. For the case of short-lived thoron (half-life 55 s), the model described the dynamics of thoron concentration in the closed loop and the steady-state concentrations attained in the detector and sample chamber. As expected, the model showed that due to decay losses during transit of thoron between the chambers, the steady-state concentrations attained in the chambers considerably differ from each other even for 1 L min−1 flow rate. [ABSTRACT FROM AUTHOR]

This paper addresses the ultimate boundedness control problem for a class of networked nonlinear systems with the round-robin (RR) protocol and uniform quantisation. The communication between sensor nodes and the controller is implemented via a constrained communication channel. The quantised output of the system is transmitted to the remote controller through a communication channel subject to a transmission delay. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. On the other hand, the uniform quantisation effects of the network are characterised by a round function (i.e. the nearest integer function). The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that, in the presence of RR protocol and uniform quantisation effects, the closed-loop system is ultimately bounded. The controller is designed based on mean square stability analysis and Lyapunov-like method. A set of sufficient conditions for the ultimate boundedness of the closed-loop system are established and, on the basis of which, the desired controller gains are obtained by solving a set of linear matrix inequalities. The effectiveness of the proposed method is verified by numerical examples. [ABSTRACT FROM AUTHOR]

Background and Objectives: The two-axis inertially stabilized platforms (ISPs) face various challenges such as system nonlinearity, parameter fluctuations, and disturbances which makes the design process more complex. To address these challenges effectively, the main objective of this paper is to realize the stabilization of ISPs by presenting a new robust model-free control scheme. Methods: In this study, a robust adaptive fuzzy control approach is proposed for two-axis ISPs. The proposed approach leverages the backstepping method as its foundational design mechanism, employing fuzzy systems to approximate unknown terms within the control framework. Furthermore, the control architecture incorporates a model-free disturbance observer, enhancing the system's robustness and performance. Additionally, novel adaptive rules are devised, and the uniform ultimate boundedness stability of the closed-loop system is rigorously validated using the Lyapunov theorem. Results: Using MATLAB/Simulink software, simulation results are obtained for the proposed control system and its performance is assessed in comparison with related research works across two scenarios. In the first scenario, where both the desired and initial attitude angles are set to zero, the proposed method demonstrates a substantial mean squared error (MSE) reduction: 96.2% for pitch and 86.7% for yaw compared to the backstepping method, and reductions of 75% for pitch and 33.3% for yaw compared to the backstepping sliding mode control. In the second scenario, which involves a 10-degree step input, similar improvements are observed alongside superior performance in terms of reduced overshoot and settling time. Specifically, the proposed method achieves a settling time for the pitch gimbal 56.6% faster than the backstepping method and 58% faster for the yaw gimbal. Moreover, the overshoot for the pitch angle is reduced by 53.5% compared to backstepping and 35.5% compared to backstepping sliding mode control, while for the yaw angle, reductions of 43.6% and 37.6% are achieved, respectively. Conclusion: Through comprehensive simulation studies, the efficacy of the proposed algorithm is demonstrated, showcasing its superior performance compared to conventional control methods. Specifically, the proposed method exhibits notable improvements in reducing maximum deviation from desired angles, mean squared errors, settling time, and overshoot, outperforming both backstepping and backstepping sliding mode control methods. [ABSTRACT FROM AUTHOR]

This study delves into an event-triggered hierarchical learning control framework for air-breathing hypersonic vehicles subject to practically constrained actuators. The hierarchical learning mechanism is adeptly integrated into both the control and allocation layers. In the control layer, an emotional deterministic learning control methodology is proposed with predefined-time disturbance observers and filters to attain predefined-time convergence of system tracking and learning, while compensating for lumped disturbances stemming from allocation errors and external disturbances. An intelligent triggered allocation approach is implemented in the allocation layer to distribute the desired control effect to the actuator with fast and low-complexity allocation considering practical actuator characteristics. The proposed control scheme ensures that all signals in the closed-loop system converge to a residual set in close proximity to the origin within a predefined time, whose time constant can be adjusted as desired by the designer. Furthermore, as the system is governed by the event-triggered mechanism, the communication burden can be considerably reduced. The effectiveness of the proposed controller is demonstrated through both theoretical proof and numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, the problem of real-time reachable set control for fuzzy singularly perturbed systems with time-varying delays and disturbances is investigated. First, by combining the Lyapunov stability theory with the free-weighting matrix approach and linear matrix inequality technique, the real-time reachable set control problem related to fuzzy singularly perturbed systems is given adequate conditions. Subsequently, the matrix decoupling approach is applied to calculate the controller gains. Moreover, the stability boundary $ {\bar \eta } $ η¯ can be established using the dichotomy technique by utilizing the adequate criteria in the following theorems. Finally, two examples are offered to illustrate the effectiveness of the strategy. [ABSTRACT FROM AUTHOR]