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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]

This paper deals with the problem of robust regulation of a Planar Vertical Takeoff and Landing (PVTOL) aircraft affected by crosswind disturbances. The proposed approach simultaneously exploits the advantages of passivity-based control and the integral sliding mode (ISM) control technique. We demonstrate that the passivity-based controller accomplishes the PVTOL regulation within a guaranteed stability region. At the same time, the ISM controller can effectively counteract the undesirable disturbances effect from the beginning of the operation since the disturbances are never seen in the measurable output. Using the passivity approach with LaSalle's Invariance Theorem, we construct the required Lyapunov function to establish the closed-loop system stability. The proposed combination of controllers results in a robust system that satisfactorily solves the regulation problem. Numerical simulations are provided to show that the proposed approach allows the tracking of different reference signals: pulse-train shaped trajectory and ellipse-shaped trajectory, considering the presence of perturbations (crosswind). Furthermore, to illustrate the effectiveness of the proposed technique, a comparative analysis considering two robust control strategies is provided. [ABSTRACT FROM AUTHOR]

Neurofeedback (NF) is endogenous neuromodulation of circumscribed brain circuitry. While its use of real-time brain activity in a closed-loop system is similar to brain–computer interfaces, instead of controlling an external device like the latter, the goal of NF is to change a targeted brain function. In this special issue on NF, we present current and future methods for extracting and manipulating neural function, how these methods may reveal new insights about brain function, applications, and rarely discussed ethical considerations of guiding and interpreting the brain activity of others. Together, the articles in this issue outline the possibilities of NF use and impact in the real world, poising to influence the development of more effective and personalized NF protocols, improving the understanding of underlying psychological and neurological mechanisms and enhancing treatment precision for various neurological and psychiatric conditions. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'. [ABSTRACT FROM AUTHOR]

To study the regulation and feedback mechanism of cholecystokinin and trypsin in Black bream, Megalobrama pellegrini (Tchang, 1930) 60 days after hatching under 15 days short-term fasting and different feeding frequencies within 24 hours during the same period, Black bream (wet weight 183.75 ± 61.16 mg, total length 20.74 ± 4.08 mm) developed in a recirculating aquaculture system (RAS) were selected. In the short-term fasting trial, body weight, trypsin, and cholecystokinin (CCK) of the feeding control group (FCG) were higher than those of the fasting trial group (FTG). Trypsin and CCK in FTG reached the lowest value on day 9, and CCK content reached the highest value on day 11. In the 24-hour daily rhythm experiment, juvenile fish were randomly assigned to (A) once feeding, (B) twice feeding, (C) three times feeding, and (D) fasting. CCK showed a minimum at 1:00+ in group A, a peak at night in group B\C\D, and a maximum in group C, and a single satiety stimulus can lead to increased hunger. The four treatment groups had an apparent closed-loop regulation, while the control point of the fasting group (D) shifted forward to the next day. In this study, we found only negative feedback regulation of CCK and trypsin at the end of fasting, considering whether the secretory site or anti-inflammatory response caused the increase of CCK. The damage of epithelial cells in the villi of the foregut was greater than that in the hindgut and hepatopancreas, and the detachment of epithelial cells and the striatal margin was the main damage. Different feeding frequencies in a single day did not directly affect the long-term fluctuation of CCK and trypsin diurnal rhythm. Three meals per day may be more conducive to the long-term growth of juvenile Black bream. This study aimed to provide a reference for the feeding strategy of juvenile Black bream in the RAS. [ABSTRACT FROM AUTHOR]

Precise current decoupling is required to achieve good control performance in the vector control of permanent magnet synchronous motor (PMSM), but traditional decoupling methods are unable to solve the problem of poor current decoupling effectiveness when the system inductance parameters are mismatched. Therefore, a decoupling control method of PMSM based on improved nonlinear extended state observer (INESO) is proposed in this paper. Firstly, a smooth, differentiable nonlinear function is used to replace the traditional fal function, which overcomes the problem of discontinuous gain changes. Secondly, a time-varying gain is designed to address the problem of reduced observer performance due to differential peak values in traditional NESO. Finally, the stability of INESO and the current loop closed-loop system is proven, followed by simulation and experimental verification. The simulation and experimental results show the proposed method effectively observes and compensates for system uncertainties, including parameter perturbations, external disturbances, and unmodeled dynamics. This method achieves complete decoupling of d and q -axes currents, while suppressing interference and enhancing the control performance of PMSM. The proposed INESO decoupling method reduces the d -axis current fluctuation about 96% and 90% when the load changes abruptly under motor inductance parameter mismatch, and can reduce q -axis current fluctuation about 88% and 78% when the d -axis current steps, respectively, compared with the conventional Current Feedback Decoupling Control (CFDC) and CDDC decoupling methods. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the fixed-time almost disturbance decoupling (ADD) stabilisation problem for a class of nonlinear systems in the p-normal form. Under suitable assumptions, a novel fixed-time ADD feedback controller is designed to ensure all states in the underlying system are not affected by disturbances. By constructing an appropriate Lyapunov function, it is shown that the corresponding closed-loop system is fixed-time stable which means the upper bound of the settling time depends on the control design parameters only. To testify the effectiveness of the proposal, two simulation examples are presented. [ABSTRACT FROM AUTHOR]

This paper presents an observer-based event-triggered boundary control strategy for the one-phase Stefan problem, utilising the position and velocity measurements of the moving interface. The design of the observer and controller is founded on the infinite-dimensional backstepping approach. To implement the continuous-time observer-based controller in an event-triggered framework, we propose a dynamic event triggering condition. This condition specifies the instances when the control input must be updated. Between events, the control input is maintained constant in a Zero-Order-Hold manner. We demonstrate that the dwell-time between successive triggering moments is uniformly bounded from below, thereby precluding Zeno behaviour. The proposed event-triggered boundary control strategy ensures the well-posedness of the closed-loop system and the satisfaction of certain model validity conditions. Additionally, the global exponential convergence of the closed-loop system to the setpoint is established using Lyapunov approach. A simulation example is provided to validate the theoretical findings. [ABSTRACT FROM AUTHOR]

In this paper, we consider cyber physical systems security control problems under DoS attacks via the tracking-removed autoencoder. The DoS attack model is described by the switch signal, which occurs in the controller-actuator transmission channel. Then, the linear matrix inequality theory is used to solve the average dwell time of the attack mode that the system can tolerate. Moreover, when the attack dwell time exceeds the tolerance range, a tracking-removed autoencoder is chosen to train to get the control signal. And it can be proved that the closed-loop system with the controller based on the tracking-removed autoencoder is asymptotically stable with $ H_\infty $ H ∞ performance index. Finally, the correctness and advancement of the theory are proved by an example. [ABSTRACT FROM AUTHOR]

In this paper, a min–max adaptive dynamic programming approach is studied for a zero-sum differential game problem with unknown nonlinear dynamics. The unknown nonlinear dynamics is learned through the online Recurrent Neural Network (RNN). The error between the learned RNN model and the dynamics of the system is proved to converge to zero. The policy iteration algorithm is utilised to solve the Hamilton–Jacobi–Isaacs (HJI) equation associated with the differential game. Furthermore, the value function in the HJI equation is approximated through a critical Neural Network with its weights and activation functions updated online iteratively. The Uniform Ultimate Bounded stability of the closed-loop system is proved based on the Lyapunov theory. Finally, the effectiveness of the proposed solution method is demonstrated by applying it to three examples. [ABSTRACT FROM AUTHOR]

Introduction: Time in tight range (TITR) is an emerging and valuable metric for assessing normoglycemia. The latest advancement in automated insulin delivery (AID) systems, the advanced hybrid closed-loop (AHCL) systems, are particularly noteworthy for managing type 1 diabetes (T1D) and enhancing glycemic control. Methods: In a real-world clinical setting, we carried out a retrospective evaluation of TITR in 42 adult subjects with T1D using the AHCL Minimed™ 780G system over a 12-month period. Results: Within just 14 days of activating the automatic mode, the AHCL Minimed™ 780G system showed rapid improvement in TITR, and in the other continuous glucose monitoring (CGM) metrics. This improvement persisted over 12 months, achieving the proposed 45–50% range for effective glycemic control. Conclusion: The AHCL Minimed™ 780G system significantly enhances TITR, demonstrating continuous improvement throughout a 12-month follow-up period. [ABSTRACT FROM AUTHOR]

The major contribution of this study is the feedback design of a finite-time convergence sliding mode control to solve the trajectory-tracking problem in a class of mechanical systems. Some advantages are that the controller presents a continuous signal by integration of the high-frequency switching term. Another benefit is the design and implementation of an uncertainty and disturbance estimator (UDE) to robustify the closed-loop system. We use Lyapunov tools to develop the closed-loop stability analysis and to give an expression of the convergence time t = t through this, we can reduce the convergence time by tuning the gains of the controller. We illustrate the performance of the proposed control structure via numerical simulations conducted for a mass-spring-damper system and experiments developed in a pendular system. [ABSTRACT FROM AUTHOR]

Cardiac failures and other cardiovascular diseases are a primary cause of death worldwide. Cardiovascular disorders, including heart failure, are the primary cause of death globally. Controller design for pacemakers is a crucial area of research. In this study, a novel proportional-integral-derivative (PID) controller design that can be used to efficiently regulate the heart rate of the cardiac pacemaker is presented. The proposed PID controller employs only one Differential Voltage Current Conveyor (DVCC) active element, two resistors, and two capacitors. The proposed PID controller circuit has voltage differential inputs, thus eliminating the need for the extra differential amplifier (DA) circuit required for closed-loop systems such as the cardiac pacemaker heart rate control system. A fractional-order (FO) PID controller (PIλDμ) circuit is created from the proposed integer order (IO) PID controller circuit. A cardiac pacemaker application example is given to demonstrate the workability of the proposed FO and IO PID controller circuits. Using 0.18 µm CMOS parameters and the PSPICE simulation program, both the proposed FO and IO PID controller circuits in a closed-loop system are performed to verify the theoretical behavior. [ABSTRACT FROM AUTHOR]

An event-triggered-super twisting sliding mode control (ET-STSMC) with saturation function in reaching law have been designed for a nonlinear Quadcopter model with bounded disturbance and its performance is compared with Event Triggered-Sliding mode control (ET-SMC). Simulation results have been obtained for altitude and attitude tracking, demonstrating the stability of the closed-loop system with the proposed control. The event-triggering conditions are derived based on the Lyapunov method, ensuring non-accumulation of inter-event execution time. Experiments have been performed in real-time to analyse the robustness and computational cost in terms of the number of control updates of the proposed control strategy under normal flight, external disturbances, and parameter uncertainty. Simulation and experimental results show that ET-STSMC can achieves better tracking performance and robustness with reduced computational cost compared to ET-SMC during all flight conditions. [ABSTRACT FROM AUTHOR]

This study introduces a novel control approach for a twin rotor multi-input multi-output system (TRMS), specifically targeting the pitch and yaw movements. The proposed method employs a sliding mode controller (SMC) with variable gains, aiming to overcome limitations like chattering and excessive control effort. Unlike traditional controllers, the gains here dynamically adjust based on the error state, enhancing the robustness of the system against external disturbances and parameter uncertainties. The control algorithm draws inspiration from both first-order and higher-order sliding mode controllers. To rigorously assess the robustness of the controller, Gaussian White noise is incorporated into the model. By dynamically adjusting gains, the proposed approach aims to minimize control effort while mitigating control signal overestimation arising from model uncertainties. Furthermore, stability analysis confirms that the operating point of the closed-loop system converges within a finite time. The effectiveness of this novel controller is validated through simulations using the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

This paper investigates the stochastic path following control of underactuated marine vehicles (UMVs) subject to multiple disturbances and constraints. Firstly, the complex marine environment in which UMVs navigate typically contains stochastic components, thus the multiple disturbances are categorized as slow-varying deterministic disturbances and stochastic disturbances. Secondly, a position-constrained line-of-sight (PCLOS) based fractional-order sliding mode stochastic (FSMS) control strategy is established to achieve path following control of UMVs. A PCLOS guidance law based on universal barrier Lyapunov function is proposed to ensure that the position errors remain within the constraint ranges, which is versatile for systems with symmetric constraints or without constraints. An FSMS controller based on fractional-order theory and sliding mode control is designed to improve the dynamic response speed of the system and effectively attenuate chattering phenomenon. A stochastic disturbance observer is developed to estimate the slow-varying deterministic disturbances in the stochastic system, and auxiliary dynamic compensators are used to mitigate the impact of input constraints. Lastly, theoretical analysis indicates that the closed-loop system is stable and the position constraint requirements are satisfied. Comparative simulations illustrate the effectiveness of the proposed control strategy. • The multiple disturbances are categorized as slow-varying deterministic disturbances, and stochastic disturbances. • A novel PCLOS guidance law is designed to ensure that the position errors do not exceed the given constraint ranges. • The fractional-order sliding mode stochastic control method exhibits improved robustness and flexibility compared to traditional integer-order sliding mode control method. [ABSTRACT FROM AUTHOR]

Crane systems are essential systems utilized in industry and for research. Nevertheless, they are always affected by endogenous and exogenous disturbances, which may generate undesirable payload oscillations, compromising people's security and the system itself. Thus, to deal with these issues and control these mechatronic systems efficiently, this manuscript develops a novel robust observer-based proportional-retarded controller for perturbed two-dimensional cranes, considering variation in the rope length. This novel scheme makes the trolley follow a desired reference signal while reducing the payload variations. The controller structure allows for compensating disturbances, while a new control approach introduces artificial delays that stabilize the closed-loop system and attain the desired control objective. A formal theoretical analysis demonstrates the validity of the new proposal. Then, experimental results show the outstanding performance of the proposed control scheme and its superior performance against other methodologies from the literature. [Display omitted] • A novel robust observer-based proportional-retarded controller applied to 2D-crane systems is proposed. • Unlike previous works, artificial delays are utilized to achieve trajectory-tracking tasks while reducing payload oscillations. • The novel controller reduces payload vibrations and avoids derivative actions. • The conjunction of the observer and the proportional retarded controller provides robustness against internal and external disturbances. • Experimental results demonstrate the outstanding performance of the novel controller when compared against other robust control schemes. [ABSTRACT FROM AUTHOR]

In this paper, a feedback controller based on the extended state observer is proposed for fully actuated systems. First, a generalized proportional–integral observer is designed to estimate states and disturbances simultaneously. Using the linear parameter varying approach and the convexity principle, a linear matrix inequality condition is given to obtain the observer gains. Second, on the basis of the full-actuation property and the estimated states, a feedback controller, utilizing estimated disturbances to compensate for system disturbances, is designed to make all the states of the closed-loop system uniformly ultimately bounded. In addition, if disturbances are constant or slow time-varying, the observation errors and the states of closed-loop system are all exponentially convergent. Two illustrations are provided to show the validity and practicality of the proposed approach. Simulation results show that the estimated disturbances can follow the true values with relatively small errors, so compensating the system disturbances with estimated values can effectively reduce the ultimate bounds of states of the closed-loop system. [ABSTRACT FROM AUTHOR]

This manuscript discuss the issue of stabilization for positive 2D (two dimensional) fractional order continuous Takagi-Sugeno Fuzzy Systems represented by the Roesser model with fixed delays. Employing linear programming approach while establishing positivity constraint on the 2D fractional system in closed-loop, delay-independent stabilization conditions are introduced by using Lyapunov-Krasovskii functions. [ABSTRACT FROM AUTHOR]

This paper introduces a design and analysis framework for a multivariable gradient-based stochastic extremum-seeking control system that considers delays. The study addresses multi-input systems with time delays in both input and output channels. The introduced new predictor feedback mechanism utilizes stochastic sinusoidal perturbation-based estimates of the Hessian's matrix in order to compensate the delay effects in the real-time optimizer. The incorporation of this feedback into the closed-loop system ensures exponential stability for the average dynamics and convergence to a small neighborhood around the unknown extremum point. The derived results are rigorously established through the application of backstepping transformation and stochastic averaging techniques in infinite dimensions. The effectiveness of the proposed predictor-based stochastic extremum-seeking approach for delay compensation is illustrated through a numerical example. [ABSTRACT FROM AUTHOR]

Traditional high-voltage pulse generators, like Marx generators often face challenges related to efficiency and complexity. In this paper, a solid-state multi-module high-voltage pulse generator that integrates capacitor-diode voltage multipliers (CDVM) with DC-DC boost converters and closed-loop voltage control is proposed to overcome these challenges. The system achieves high output voltage by coupling the pulsed output voltages of individual low-voltage DC sources in series across each module. The proposed design was modeled using MATLAB, and experimental testing was conducted on a single stage. Comparative analyses between timedomain parameters, proportional-integral (PI), and fractional order proportional integral derivative (FOPID) controllers were performed. Both MATLAB simulations and experimental validations demonstrate the effectiveness of this approach. The rise time, peak time, settling time, and steady-state error are all improved using an FOPID controller, decreasing from 0.32 to 0.31 seconds, 0.42 to 0.35 seconds, and 3.15 to 2.20 seconds, respectively. These findings indicate that a closed-loop FOPID controller enhances time-domain performance parameters more effectively than a PI controller for a two-stage DC-DC voltage multiplier. [ABSTRACT FROM AUTHOR]

In this paper, we present an adaptive optimal control algorithm for solving the tracking control problem of multiple autonomous surface vehicles under uncertain dynamics and unknown external disturbances. The proposed control algorithm uses an adaptive dynamic programming technique with optimal compensation terms. A disturbance observer is designed to handle the problem of unknown time-varying external disturbances. It is proven that all the signals in the closed-loop system are bounded. Simulation results are provided to illustrate the effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This study is the first time devoted to seek an online optimal tracking solution for unknown nonlinear singularly perturbed systems based on single network adaptive critic (SNAC) design. Firstly, a novel identifier with more efficient parametric multi-time scales differential neural network (PMTSDNN) is developed to obtain the unknown system dynamics. Then, based on the identification results, the online optimal tracking controller consists of an adaptive steady control term and an optimal feedback control term is developed by using SNAC to solve the Hamilton–Jacobi–Bellman (HJB) equation online. New learning law considering filtered parameter identification error is developed for the PMTSDNN identifier and the SNAC, which can realize online synchronous learning and fast convergence. The Lyapunov approach is synthesized to ensure the convergence characteristics of the overall closed loop system consisting of the PMTSDNN identifier, the SNAC and the optimal tracking control policy. Three examples are provided to illustrate the effectiveness of the investigated method. [ABSTRACT FROM AUTHOR]

This paper exhibits a proportional-type robust current controller for permanent magnet synchronous motors (PMSMs), incorporating the variable bandwidth technique driven by the proposed online auto-tuner and the disturbance observer (DOB) as the subsystems. There are two contributions: (a) the proposed online auto-tuner implements the variable bandwidth for the closed-loop system to boost the transient current tracking performance and (b) the combination of proportional-type feedback controller and DOB eliminates the requirement of the integral action, ensuring the steady-state error rejection property. Moreover, it is proved that the resultant feedback system recovers the target current tracking performance without steady-state errors. The experimental study is conducted to verify the efficacy of the proposed controller using a 700-W prototype PMSM. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a learning-based framework that addresses the point-to-point vehicular navigation problem through a robust output regulation approach and test it through Ultra-Wide Band (UWB) communication noise data. Our focus is on the learning-based control policy design and ensuring the stability of the closed-loop system for vehicle dynamics. It is seen that our proposed solution, which relies on reinforcement learning, is data-driven and does not require accurate knowledge of the vehicle motion model. Specifically, we explore learning-based optimal tracking control through state feedback and output feedback, which we categorize as policy iteration and value iteration, respectively. To validate our approach, we incorporated noise samples from a real-world UWB positioning platform into our simulation. Our findings demonstrate that the learning-based method may be effective in both vehicular point-to-point tracking and interference tolerance, even in the presence of real-world noise interference. [ABSTRACT FROM AUTHOR]

The problem of memory feedback tracking control for unmanned aerial vehicle systems subject to nonlinear actuator faults and disturbances is investigated in this paper. First, a generalized extended state observer is constructed to get the estimates of the system states and the disturbances. Then, by incorporating the obtained estimates in the control design, an anti-disturbance memory feedback tracking control law is designed such that the resulting closed-loop augmented system is asymptotically stable, and thereby the states of the unmanned aerial vehicle system track the given reference trajectories with satisfactory disturbance rejection performance. Notably, by constructing appropriate asymmetric Lyapunov–Krasovskii functional, the stability and stabilization conditions for guaranteeing the desired tracking and disturbance attenuation performance are derived in terms of linear matrix inequalities. Further, the observer gains are evaluated using the pole placement approach. Finally, numerical simulations are given to verify that the proposed control strategy is viable. [ABSTRACT FROM AUTHOR]

In order to improve the control accuracy and robustness of path tracking system for the transplanter, a fuzzy predictive function control method was proposed using feedback linearization in this study. The kinematic model of transplanter was established using Frenet coordinate system. The state feedback method was applied to the nonlinear transplanter system to make the closed loop system become linear system. The Morlet wavelet function was selected as the basis function in predictive function control. The control law of path tracking system for transplanter was designed by the predictive function control algorithm. The weighting coefficient of lateral error in the performance index function for the predictive function control was adjusted online by designing fuzzy rules according to the lateral error and the reference path curvature. The weighting coefficient of change rate of lateral error in the performance index function for the predictive function control was adjusted dynamically by designing fuzzy rules according to the lateral error and the change rate of lateral error. The simulation platform was built for path tracking control of transplanter using Matlab/Simulink software. The simulation results of the fuzzy predictive function control showed that the lateral errors of straight path tracking asymptotically approached zero, and there was no overshoot of actual driving curves at different operating speeds for the straight path tracking. In the straight path tracking, the in-line distance of the fuzzy predictive function control was 1.2, 2.3 and 3.3 m, and the in-line distance of the conventional model predictive control was 2.6, 2.3 and 4.6 m, respectively, when the operating speeds of transplanter were 0.5, 1.0 and 1.5 m/s, respectively. In the case of curve path tracking for the fuzzy predictive function control, the maximum absolute values of lateral error were 0.7, 2.4 and 5.1 cm, and the standard values of lateral error were 0.4, 1.5 and 2.8 cm, respectively, when the operating speeds of transplanter were 0.5, 1.0 and 1.5 m/s, respectively. In the case of curve path tracking for the conventional model predictive control, the maximum absolute values of lateral error were 4.3, 5.5 and 7.8 cm, and the standard values of lateral error were 3.1, 3.5 and 5.0 cm, respectively, when the operating speeds of transplanter were 0.5, 1.0 and 1.5 m/s, respectively. The average operation cycle of the fuzzy predictive function control algorithm was 0.012 s, which was 0.004 s less than that of the conventional model predictive control algorithm. Compared with the conventional model predictive control, the dynamic performance, control accuracy and robustness of path tracking system for transplanter were improved on the premise of ensuring the real-time performance by the fuzzy predictive function control. The automatic driving control system of transplanter was built to install the satellite antenna, satellite receiver, angle sensor, electric steering wheel, controller and vehicle-mounted touch screen on the transplanter. The field experiment was carried out with the automatic driving control system of transplanter. The field test results showed that the fuzzy predictive function control had the strong robustness to the changes of operating speed and reference path curvature. The transplanter tracked the reference path smoothly and effectively. The maximum absolute value of lateral error occurred near the intersection of the straight path and the curve path. Once the operating speeds of transplanter were 0.5, 1.0 and 1.5 m/s, the maximum absolute values of lateral error were 5.9, 7.5 and 9.8 cm, the standard values of lateral error for the straight path were 1.4, 1.7 and 2.7 cm, and the standard values of lateral error for the curve path were 2.5, 3.6 and 5.5 cm, respectively. The fuzzy predictive function control can fully meet the actual control requirements of transplanter, and provided a reference for the research on predictive control method of path tracking for transplanter. [ABSTRACT FROM AUTHOR]

This article presents a tuned control algorithm for the speed and course of a four-wheeled automobile-type robot as a single nonlinear object, developed by the analytical approach of compensation for the object's dynamics and additive effects. The method is based on assessment of external effects and as a result new, advanced feedback features may appear in the control system. This approach ensures automatic movement of the object with accuracy up to a given reference filter, which is important for stable and accurate control under various conditions. In the process of the synthesis control algorithm, an inverse mathematical model of the robot was built, and reference filters were developed for a closed-loop control system through external effect channels, providing the possibility of physical implementation of the control algorithm and compensation of external effects through feedback. This combined approach allows us to take into account various effects on the robot and ensure its stable control. The developed algorithm provides control of the robot both when moving forward and backward, which expands the capabilities of maneuvering and planning motion trajectories and is especially important for robots working in confined spaces or requiring precise movement into various directions. The efficiency of the algorithm is demonstrated using a computer simulation of a closed-loop control system under various external effects. It is planned to further develop a digital algorithm for implementation on an onboard microcontroller, in order to use the new algorithm in the overall motion control system of a four-wheeled mobile robot. [ABSTRACT FROM AUTHOR]

This work studies the dynamic positioning (DP) control issue of unmanned surface vessels subjected to thruster saturation, error constraints, and lumped disturbances composed of time-varying marine environmental disturbances and model parameter uncertainties. Combining the disturbance-accurate estimation technique and the prescribed performance control strategy, a novel prescribed-time DP control scheme is established to address this challenging problem. In particular, the prescribed-time lumped disturbance observer is designed to accurately estimate external marine disturbances, which guarantees that the estimation error converges to zero within a prescribed time. Subsequently, a prescribed performance control strategy is proposed to guarantee that the positioning errors of DP surface vessels with thruster saturation constraints meet the error constraints requirements within a prescribed time. Furthermore, an anti-windup compensator is presented to mitigate the thruster saturation and improve the robustness of the DP control system. The stability analysis demonstrates that all positioning errors of the closed-loop system can converge to predefined performance constraints within a prescribed time. Finally, the numerical simulation confirms the efficacy and superiority of the proposed PTDP scheme. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive control scheme is proposed for the path-following problem of a nonholonomic mobile robot with uncertain dynamics based on barrier functions. To optimize communication resources, we integrate an event-triggered mechanism that avoids Zeno behavior and ensures that the tracking error of the closed-loop system converges to a small neighborhood around zero within a fixed time, while consistently satisfying predefined transient performance requirements. Extensive simulation studies demonstrate the effectiveness of the proposed approach and validate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper introduces an extended state observer-based command filtered backstepping control method to improve the tracking accuracy and synchronization performance of multi-motor-driving servo systems under the condition of low-speed nonlinear friction dynamics. Firstly, a novel and effective four-motor synchronization scheme is designed and various groups of synchronization feedback signals are introduced to achieve accurate synchronization performance among motors. Then, the observer is designed to estimate the friction torque. And the controller is developed via command filtered backstepping technique to avoid additional computational complexity, making the control signals suitable for practical application. Finally, the stability of the closed-loop system is analyzed, and the tracking and synchronization performance is verified through designed experiments. [ABSTRACT FROM AUTHOR]

This paper investigates the control problem of a spacecraft attitude manoeuvrer with external disturbances. Firstly, the spacecraft attitude dynamical model is introduced; then, the tube-based framework is constructed, which includes a nominal system and an error system. Based on that, the control law design would be a two-step process. To start with, the nominal control law is developed via an adaptive dynamic programming technique and a neural network approximation in order to provide a nominal trajectory to the desired attitude. Moreover, based on the nonsingular terminal sliding mode control scheme, the error controller is derived to lead the actual system to track the nominal trajectory and suppress disturbances. The stability of the closed-loop system is analyzed via the Lyapunov approach and the simulation results could verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider the output feedback event-triggered tracking control problem for a class of switched nonlinear multi-agent systems (MASs) with sensor faults and state constraints. For unknown nonlinear functions in the system, fuzzy logic systems are used to approximate them. To address sensor faults, sensor error compensation coefficients are designed to compensate for the errors caused by sensor faults. Meanwhile, state observer is designed to estimate the unmeasurable states in the system, providing necessary information for control design. Based on directed switching networks containing a directed spanning tree, an event-triggered output feedback controller is designed to enable the MAS to track the leader agent. By constructing a suitable barrier Lyapunov function, the stability of the system is analyzed, and it is proved that the consensus tracking can be achieved without violating the state constraints, the uniform boundedness of all the closed-loop system signals is ensured and the Zeno behavior can be eliminated. Finally, the effectiveness of the proposed algorithm is verified through a simulation example. [ABSTRACT FROM AUTHOR]

Current attempts to implement and apply automated control systems for the management of glucose homeostasis in individuals with diabetes are partly successful. In most semi and closed loop control systems to mimic the action of a normal pancreas in diabetes patients, insulin is administered subcutaneously. However, the parameters for insulin diffusion and transport time constants are relatively large and have wide individual variations. Therefore, deviation from a normal meal can result in suboptimal euglycemic control. Stable and reliable closed loop feedback control using continuous glucose monitoring under these conditions is difficult and needs regular interventions from the user. This article describes the translation of the endocrine physiology of a normal pancreas to an electronic equivalent. With this translation, the complex effects of a direct intravenous pulsatile method of insulin and glucagon administration can be simulated in accordance with physiological observations in a healthy subject and has been built with standard electronic components. This device is applicable for any individual and under any condition to automatically maintain the desired optimal euglycemic condition. The insulin and glucagon response control is presented in the same physiological pulsatile manner as is observed in healthy individuals. [ABSTRACT FROM AUTHOR]

By using a weighted average dwell time approach, the finite-region stability and stabilization problems are investigated for a class of two-dimensional switched systems with actuator saturation in the Fornasini–Marchesini local state-space model. Firstly, we analyze the finite-region stability of the system studied by introducing the weighted average dwell time approach for the first time. Secondly, the classical state feedback control method is introduced to the system. Based on the established conditions, sufficient criteria are derived to ensure the resulting closed-loop system is finite-region-stable. Finally, a numerical example is provided to show the effectiveness of the provided design approach. [ABSTRACT FROM AUTHOR]

This study aims to investigate the finite-time control problem for a class of strict-feedback time-delay nonlinear systems with unknown functions. The control design is based on a fast finite-time practical stability criterion. Unknown nonlinear functions can be estimated using the universal approximation performance of neural networks. Finite-time control design is performed using adaptive backstepping technology. By performing closed-loop stability analyses and choosing appropriate Lyapunov–Krasovskii functionals, all signals in a closed-loop system can be bounded within a finite time. Subsequently, the proposed control method can be applied for the excitation control of synchronous generators. The effectiveness of the proposed method is verified using a numerical model of a single-machine power system. [ABSTRACT FROM AUTHOR]

External cavity diode laser (ECDL) can continuously alter its output optical frequency by tuning the external cavity. Wide mode-hop-free (MHF) range and linear optical frequency tuning are two critical characteristics of the ECDL. However, using an uncoated laser diode (LD) limits the MHF range due to the influence of internal cavity formed by the LD. To obtain linear optical frequency, a triangular wave voltage is generally used to scan the external cavity. Nevertheless, the inherent hysteresis characteristic of piezoelectric transducer (PZT) in the external cavity introduces nonlinearity in the optical frequency. The limited MHF range and nonlinear optical frequency can greatly affect the performance and accuracy of applications with uncoated ECDL as the light source. Therefore, it is crucial to address these two issues of uncoated ECDL. This study introduces a hybrid method incorporating synchronous tuning with proportional-integral-derivative (PID) feedback control. Synchronous tuning facilitates simultaneous changes in both the internal and external cavities output modes, thereby extending the MHF range. PID feedback control utilizes the displacement signal of prism in the external cavity to establish a closed-loop control system, compensating for the PZT's hysteresis. Through PID feedback control, the uncoated ECDL's optical frequency tuning nonlinearity is effectively suppressed while its MHF range is extended. Experimental results validate the efficacy of this hybrid method within the triangular wave scanning frequency of 50 Hz. [ABSTRACT FROM AUTHOR]

Background: We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. Methods: This prospective observational multicenter study collected demographic, clinical, and 2-week 780G system data at five time points. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. Results: The cohort included 93 children, 43% girls, with a median age of 15.1 years (interquartile range [IQR] 12.9,17.0). A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (ptime < 0.001) after the transition to 780G. The mean hemoglobin A1c (HbA1c) (SE) was 8.65% (0.12) at baseline and dropped by >1% after 1 year to 7.54% (0.14) (ptime < 0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (P < 0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (P = 0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (P < 0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to Advanced Hybrid Closed-Loop (AHCL) usage were predictors of achieving optimal glycemic control. Conclusions: The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of health care professionals, youth, and caregivers. [ABSTRACT FROM AUTHOR]

Aim: To compare the safety in terms of hypoglycemic events and continuous glucose monitoring (CGM) metrics during aerobic exercise (AE) of using temporary target (TT) versus suspension of insulin infusion (SII) in adults with type 1 diabetes (T1D) using advanced hybrid closed-loop systems. Methods: This was a randomized crossover clinical trial. Two moderate-intensity AE sessions were performed, one with TT and one with SII. Hypoglycemic events and CGM metrics were analyzed during the immediate (baseline to 59 min), early (60 min to 6 h), and late (6 to 36 h) post-exercise phases. Results: In total, 33 patients were analyzed (44.6 ± 13.8 years), basal time in range (%TIR 70–180 mg/dL) was 79.4 ± 12%, and time below range (%TBR) <70 mg/dL was 1.8 ± 1.7% and %TBR <54 mg/dL was 0.5 ± 0.9%. No difference was found in the number of hypoglycemic events, %TBR <70 mg/dL and %TBR <54 mg/dL between TT and SII. Differences were found in the early phase, with better values when using TT for %TIR 70–180 mg/dL (83.0 vs. 65.3, P = 0.005), time in tight range (%TITR 70–140 mg/dL) (56.3 vs. 41.5, P = 0.04), and time above range (%TAR >180 mg/dL) (15.3 vs. 31.8, P = 0.01). In the diurnal period, again %TIR was better for TT use (82.1 vs. 73.1, P = 0.02) and %TAR (15.0 vs. 22.96, P = 0.04). No significant differences were found in the CGM metrics during the different phases of AE. Conclusion: Our data appear to show that the use of TT compared with SII is equally safe in all phases of AE. However, the use of TT allows for a better glycemic profile in the early phase of exercise. [ABSTRACT FROM AUTHOR]

The paper presents output feedback control of a class of two-time-scale nonlinear systems. State feedback control for two-time-scale system is converted into output feedback via two high-gain observers. The high-gain observers are designed for reduced-order, quasi-steady-state, and boundary layer models of the two-time-scale system. Analyses reveal three-time-scale structure of the closed-loop system. Convergence of the closed-loop system is guaranteed under sufficient conditions. Simulation results of control of inverted pendulum on a cart illustrate the application of the proposed methodology. [ABSTRACT FROM AUTHOR]

This work presents a methodology for controlling a quadrotor vehicle in both regulation and trajectory tracking tasks when the system is affected by endogenous and exogenous disturbances. In the proposed approach, the quadrotor is driven by a second-order variable-gain sliding mode controller (VG-SMC), which includes a state-dependent variable-gain that allows enhancing the controller performance against disturbances. Besides, the proposed controller achieves finite-time convergence of the position and orientation error signals and their time derivatives. The performance of the closed-loop system is assessed by comparing it with a standard sliding mode controller whose control objective is to track two optimal smooth reference signals. The comparison between both controllers considers the undisturbed and the perturbed cases. Numerical simulations and experimental results demonstrate that the proposed VG-SMC controller provides better overall closed-loop results than those obtained by a fixed-gain sliding mode controller, despite the presence of disturbances. [ABSTRACT FROM AUTHOR]

This paper studies the analysis and synthesis of distributed adaptive control architectures for uncertain multiagent systems with coupled dynamics in a leader-follower setting, where overall closed-loop system stability is established, and sufficient stability conditions are defined. Specifically, we first analyse a standard distributed adaptive control law and reveal local stability conditions that guarantee the boundedness of the closed-loop system trajectories. We next synthesise fixed and adaptive robustifying terms to show relaxed local stability conditions. We also show that the fixed robustifying term can yield high-gain parameters in the resulting control signals, where the adaptive robustifying term removes this high-gain requirement. Finally, an illustrative numerical example is further presented to compare the proposed methods and demonstrate our theoretical contributions. [ABSTRACT FROM AUTHOR]

This paper studies the finite-time output tracking problem for a class of nonlinear sandwich systems with sandwiched dead-zone function and input actuator saturation constraint. To achieve the goal, a systematic adaptive backstepping controller is proposed based on the practical finite-time stability criterion which guarantees the output tracking even if the dead zone and saturation constraints occur, simultaneously. In the control approach to confine the system output to a predefined set, the barrier Lyapunov function is utilised. To cope with the problem of 'explosion of complexity', a finite-time command filter is also employed. Furthermore, the values of the unknown parameters are estimated by appropriate adaptive laws. The finite-time stability of the closed-loop system is proved based on the Lyapunov approach which ensures the boundedness of all signals. Finally, the efficiency and applicability of the proposed method are confirmed by providing the simulation results for the hydraulic servo press system. [ABSTRACT FROM AUTHOR]

In this paper, the problem of reliable bumpless transfer control for switched systems with actuator faults is investigated. A switching law and a class of reliable controllers via output feedback are constructed such that the bumpless transfer performance and H ∞ reliable property of the closed-loop systems are guaranteed. The switching process is divided into two stages, that is, dwell time and state-dependent switching stages. In the dwell time stage, a low bound of the time of the activated subsystem is introduced to restrict the frequent switching and suppress the system bumps. This guarantees the bumpless transfer performance of systems. In the second stage, only the measurable controller states are used to generate the switching signals, which upgrades the feasibility in the frame of output feedback. Finally, to ensure the H ∞ reliable property, the proposed controllers are time-varying, which work in the different switching stages. A simulation example is given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered control problem for Roesser model-based two-dimensional (2D) Markov jump systems with multiple communication channels. In order to optimize the utilization of communication resources, an event-triggered rule (ETR) is proposed based on the structural characteristics of the 2D Markov jump plant. In addition, a stochastic communication protocol (SCP) is utilized to schedule transmissions from the controller to the actuators. Under the ETR and the SCP, an asynchronous state-feedback control scheme is formulated, allowing for mode mismatches between the controller and the 2D plant. A sufficient condition on both stochastic stability and a predefined H ∞ disturbance-attenuation performance of the closed-loop 2D system is established. Building upon this condition and linear matrix inequalities, a computationally efficient method is developed for designing the required state-feedback controller gains. Finally, the feasibility and effectiveness of the proposed event-triggered control approach are demonstrated by the application of a simulation example involving the Darboux equation. [ABSTRACT FROM AUTHOR]

In this paper, a learning-based nearly optimal control framework with fault-tolerant capability is designed to tackle the tracking control problem of a flexible-link manipulator in the presence of actuator fault and model uncertainties. Initially, the optimal control law is obtained by adopting the dynamic programming and a critic structure as the solution of Hamilton–Jacobi–Bellman equation for the nominal model. Then, by implementing an integral sliding mode control, the robustness against actuator fault and model uncertainty is guaranteed. The adaptive laws are constructed based on radial basis functions neural networks to estimate the upper bound of uncertainty and the actuator bias fault, satisfying both optimal performance and chattering reduction of the sliding surface. Furthermore, the actuator effectiveness loss is handled. The stability of the closed-loop system is analytically proven, and the performance of the proposed framework is investigated against several practical operating conditions. This incorporates the fidelity assessment of tracking precision and trackability of control signal using performance indices such as the integral absolute error and root-mean-square error. The results of extensive simulation studies confirm the effectiveness and robustness of the proposed control framework. [ABSTRACT FROM AUTHOR]

To solve the aircraft dynamics modeling problem in the entire envelope range, this work proposes a closed-loop system identification method based on deep learning. A closed-loop flight test was designed, under the framework of the closed-loop flight test, the motion mode of the aircraft was fully stimulated by the input signal of the control rudder surface and the airspeed and position commands. The lateral and longitudinal aerodynamic coefficients were solved from the flight test data, and the black box relationship between the aerodynamic coefficients and their influencing factors was established based on the deep network technology. The aerodynamic coefficient black box model was combined with the dynamics and kinematic equations of the aircraft to form a deep network dynamic model of the aircraft, which belongs to a gray box dynamics model. The deep network can easily and uniformly process different batches of flight test data, thus combining the flight test data at different flight state points, and finally building a complete aerodynamic model within the entire envelope range. Three groups of flight tests were performed: the first group of tests was used for model set training, the second group of test data was used for the selection of the best model, and the third group of flight tests was used for model validation. The model verification was completed from two aspects: the prediction of the aerodynamic coefficient and the prediction of the flight state variables. The results show that the deep network model can complete high-precision modeling of aerodynamic coefficients; and the gray box dynamic model can complete the modeling of aircraft dynamics within the entire envelope, and can be used as a long-term, high-precision flight simulator. [ABSTRACT FROM AUTHOR]

In this study, we address the trajectory tracking control problem for stratospheric airships, characterized by parameter uncertainties and external disturbances. Initially, a mathematical model of the airship is constructed, from which a trajectory tracking error model is derived. Subsequently, a novel sliding mode control law is formulated to enhance control accuracy and accelerate the convergence rate of the sliding mode. Furthermore, radial basis function neural networks are utilized to estimate and compensate for uncertain system parameters and external disturbances, significantly improving the system's robustness. Lastly, the application of Lyapunov's theory verifies the fixed-time stability of the closed-loop system and ensures the convergence of trajectory tracking error to a near-zero vicinity within fixed time. Simulation results strongly support the efficacy of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of rapid reconfiguration control in the chained tethered satellite formation (CTSF) amidst full-state constraints and uncertainties. To tackle this, we propose an innovative event-triggered practical prescribed-time control method grounded in observer theory. Initially, we develop a sliding mode state observer utilizing event triggering to effectively monitor the velocities of adjacent satellites. Subsequently, leveraging the framework of backstepping control, uncertainties are managed by approximating them using fuzzy logic systems. The imposition of full-state constraints is adeptly handled through the barrier Lyapunov function. An event-triggered practical prescribed-time controller (ET-PPTC) is then engineered, drawing on the principles of practical prescribed-time stability. The robustness and stability of the closed-loop control system are rigorously established employing the Lyapunov framework. Finally, through comprehensive numerical simulations, we validate the feasibility and efficacy of the proposed control scheme in facilitating the reconfiguration mission of a four-satellite CTSF. • An intensive study on the rapid reconfiguration control of Chain Tethered Satellite Formation. • Introduces an event-triggered prescribed-time control method for full-state-constrained MAS. • Utilization of event-triggered control to conserve network bandwidth and computational burden. • Achieves preset precision within designated timeframe, enhancing engineering practicality. [ABSTRACT FROM AUTHOR]

• A predefined time control is proposed for morphing aircraft with state constraints. • The unknown disturbances can be estimated faster and more accurately. • The feasibility conditions are not required. • The system state can be limited to preset constraints. • The practical predefined time stability of attitude tracking error is guaranteed. This paper proposes a predefined time control method for morphing aircraft based on an adaptive full-feedback recurrent neural network and a universal barrier function. This method allows morphing aircrafts to track their attitude accurately even under the influence of morphing disturbance, aerodynamic uncertainties and asymmetric time-varying constraints. Specifically, a new universal barrier function is applied to directly perform unconstrained transformations of state variables, which avoids feasibility conditions. Additionally, an adaptive full-feedback recurrent neural network structure is proposed to quickly and accurately approximate additional disturbances and unknown dynamics. Moreover, a backstepping framework is applied to design the predefined time control law, and a command filter is used to prevent the "explosion of complexity" problem. According to stability analyses, the states of the closed-loop system converge within the preset time without violating the state constraints. Finally, the effectiveness of the control algorithm is verified via simulation experiments. [ABSTRACT FROM AUTHOR]