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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]

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]

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]

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]

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 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]

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]

The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms. • Smith Predictor is introduced into maglev control system to mitigate the adverse impact from TD. • Analyzed application value of Smith Predictor in levitation control system with time delay. • Provided suggestions for the broader implementation of Smith Predictor in practical engineering. [ABSTRACT FROM AUTHOR]

This paper investigates safety-critical event-triggered control (ETC) for nonlinear systems. It proposes a new ETC strategy that ensures event-triggered safety by using a tunable input-to-state safe barrier function. Then, a method is devised to effectively save communication resources and reduce computational load through the construction of a suitable dynamic event-triggered mechanism. Furthermore, the exclusion of Zeno behavior is guaranteed for the closed-loop system. Finally, this paper culminates by presenting two illustrative examples that showcase the effectiveness of proposed control strategies. • Address the issue of sampling errors and provide a less conservative approach. • Ensure event-triggered safety of nonlinear systems. • The definite exclusion of Zeno behavior in event-triggered control. [ABSTRACT FROM AUTHOR]

This paper is devoted to the tracking control for an uncertain robotic system with both output constraint and dead-zone input. Remarkably, the distinctive characters of the system are reflected by system uncertainties and output constraint. First, more serious uncertainties are involved since unknown nonlinear dynamic matrices, external disturbance and the dead-zone input (see unknown slopes and break points therein) are simultaneously considered, but those of the related literature are not. Second, weaker conditions on the output constraint are allowed since the constraint functions considered are only first but not more order continuously differentiable while any their time derivatives are not necessarily available for feedback. This leads to the incapability of the traditional control schemes on this topic. To solve the control problem, a novel control framework is proposed based on time-varying feedback which overcomes the serious system uncertainties while relaxes the conditions on output constraints. Specifically, a state transformation with a time-varying gain is first introduced to derive a new system. Then, by using the traditional backstepping method with the introduction of the time-varying gain in the estimations of some uncertain terms, a time-varying feedback controller is explicitly designed, which ensures that all the states of the resulting closed-loop system are bounded while system output asymptotically tracks the reference signal without any violation of the output constraint. Finally, simulation results for two practical examples are provided to validate the effectiveness of the proposed theoretical results, and moreover, a comparison with PID method is given to show the superiority of the proposed method on tracking accuracy and robustness. • More serious uncertainties are involved in the system under investigation than those of the related literature. • Weaker conditions are allowed on the output constraint than those of the related literature. • A novel time-varying control scheme is proposed by introducing a time-varying gain in control design. [ABSTRACT FROM AUTHOR]

A fixed-time distributed formation control strategy is investigated for multiple underactuated unmanned surface vehicles (USVs) with unmeasured velocities and input saturation. Initially, a necessary coordinate transformation is applied to the mathematical model of USVs to address the underactuated issue. Subsequently, a fixed-time extended state observer (FESO) is constructed to estimate unmeasured velocities and lumped disturbances of USVs based on input and output data in the control loop. Meanwhile, the leader–follower approach is applied to achieve a preset formation. A fixed-time differentiator is utilized to compute real-time differential signals for virtual control laws, which simplifies the complexity of controller design. Furthermore, a fixed-time distributed formation controller is designed based on an asymmetric differentiable saturation model. The effects of input saturation are eliminated by a designed auxiliary system. Finally, the fixed-time stability of the closed-loop system is analyzed through the Lyapunov stability theory. The comparison simulation results verify the effectiveness and superiority of the proposed formation control scheme. • A distributed fixed-time control strategy is proposed for USV formation. • The designed controller with asymmetric and smooth saturated curves. • The proposed control method scaled flexibly without communication burden. [ABSTRACT FROM AUTHOR]

Robust control of uncertain fully actuated systems (FASs) with nonlinear uncertainties and perturbed input matrices is considered. Motivated by the recent work on this issue, two novel robust controllers are further developed for two cases under different assumptions. For both cases, the assumption on the perturbation input matrix in the previous work is relaxed to a significant extent, which allows many typical perturbation input matrices, such as constant ones, to be handled, while the previous method cannot. Moreover, for the first case, the assumption on the system uncertainty is further relaxed, and the states of the closed-loop system are globally bounded and converge into an arbitrarily small spherical domain centered at the origin. For the second case, with another requirement on the system nonlinearity imposed, the global exponential stability of the closed-loop system is achieved. The successful application in an electromechanical system verifies the effectiveness of the method. • The nonlinear uncertainty and the uncertainty in the input matrix are considered. • A controller makes the states converge globally into an arbitrarily small region. • Another controller achieves the global exponential stability. • The assumptions on the perturbed input matrix in the previous work are relaxed. • A successful application in the control of electromechanical systems. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive dynamic surface (DSC) guidance law for missile is designed to intercept the maneuvering target with field-of-view (FOV) and terminal angle constraints in three-dimensional(3D) space, and the missile autopilot dynamics is considered. Firstly, the time-varying transformation function related to line of sight (LOS) is used to replace the FOV constraints, transforming the process-constrained control problem into the output-constrained control problem. Meanwhile, the 3D coupled relative kinematics model considering missile autopilot dynamics and maneuvering target acceleration is established. Secondly, a novel time-varying asymmetric barrier Lyapunov function (TABLF) with dead-zone characteristics is introduced to the adaptive dynamic surface guidance law design process to improve the robustness of parameter debugging. Thirdly, with the help of a nonlinear adaptive filter, the 'explosion of complexity' problem can be avoided effectively, which is caused by analytic computation of virtual signal derivatives. Furthermore, aiming at the problem of autopilot dynamic errors, target acceleration disturbances, and unmeasurable parameters in the model, a novel adaptive law is used to evaluate online. Then, the stability of the closed-loop system is rigorously proven using Lyapunov criteria. Ultimately, Numerical simulations with various constraints and comparison studies have been considered to show the feasibility and effectiveness of the proposed missile guidance law. • The terminal angle constraint guidance (TACG) law within field of view (FOV) constraints is developed in the three-dimensional(3D) space while considering the autopilot dynamics and the maneuvering target acceleration simultaneously, which can promote the guidance accuracy. • The utilization of the novel FOV constraint transformation can transform the FOV constraints into the output constraints, which facilitates the derivation of adaptive dynamic surface control (DSC) scheme. • The time-varying asymmetric barrier Lyapunov function (TABLF) with the dead zone characteristic is designed to derive the 3D TACG law with FOV constraints, which can enhance the accuracy of convergence and improve the robustness of parameter debugging. • The 'explosion of complexity' is avoided by using the novel nonlinear adaptive filter. In addition, a novel adaptive law is designed to adapt the unknown parameters automatically containing autopilot modeling error, target acceleration disturbance, and unmeasurable parameters. [ABSTRACT FROM AUTHOR]

This paper introduces a fuzzy intermittent control issue for nonlinear PDE-ODE coupled system under spatially point measurements (SPMs), which can be represented by an ordinary differential equation (ODE) and a partial differential equation (PDE). Firstly, the nonlinear coupled system is aptly characterized by the Takagi–Sugeno (T–S) fuzzy PDE-ODE coupled model. Subsequently, based on T–S fuzzy model, a novel Lyapunov function (LF) is provided to design a fuzzy intermittent controller ensuring exponential stability of the closed-loop coupled system. The stabilization conditions are presented by means of a group of space-dependent linear matrix inequalities (SDLMIs). Finally, simulation results are given to illustrate the effectiveness of the proposed design method in the control of a hypersonic rocket car (HRC). [ABSTRACT FROM AUTHOR]

This work reflects on a fast finite-time control issue of nonlinear systems. Both the unmeasurable states of system and unknown nonlinearities are consideblack in this article. A state observer is constructed to eliminate the constraint that the states of system need to be measublack. By utilizing the fuzzy logic systems (FLSs), the unknown nonlinearities are coped with. The singularity issue from the virtual controllers design is skillfully tackled by constructing the smooth piecewise function. The practical fast finite-time stability criterion (fast FTS criterion) is firstly established. Then, a fast finite time output feedback controller is established. By means of the proposed stability criterion, the fast finite time stability of the closed-loop system is guaranteed. Eventually, two examples demonstrate the efficacy of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive nonlinear proportional-derivative (ANPD) controller for a two-wheeled self-balancing robot (TWSB) modeled by the Lagrange equation with external forces. The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative (NPD) controller and a genetic algorithm, in which the proportional-derivative (PD) parameters are updated online based on the tracking error and the preset error threshold. In addition, the genetic algorithm is employed to adaptively select initial controller parameters, contributing to system stability and improved control accuracy. The proposed controller is basic in design yet simple to implement. The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces. The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory, providing theoretical assurance of its robustness. Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors, demonstrating the effectiveness and performance of the proposed controller. The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots, which has great applicability in the field of robot control systems. This represents a promising solution for applications requiring precise and stable motion control under varying external conditions. [ABSTRACT FROM AUTHOR]

This paper presents a safe-guaranteed backstepping sliding mode heading controller for the underactuated hovercraft in the presence of slew safety constraint and system uncertainties. To begin with, based on the four degrees-of-freedom mathematical model of the hovercraft with system uncertainties, a novel slew rate constraint scheme is proposed to constrain the virtual slew rate of the hovercraft by designing auxiliary dynamic function, and redefine the error constraint envelope according to the prescribed performance control idea to realise the slew rate error constraint. In addition, a second-order fixed time disturbance observer is designed to quickly estimate the uncertainties of the system. Finally, all tracking errors of the closed-loop system are verified global asymptotically stable. The simulation results show that the slew rate can be constrained within the set safety range $r \lt 2.5^\circ /s$ r < 2.5 ∘ / s , and the error signals can converge to 0. [ABSTRACT FROM AUTHOR]

Issues of design and research of energy-efficient and reliable semiconductor DC voltage converters for wide application in power supply devices of arc plasmatrons used in plasma metal cutting installations are considered. An estimated structural dynamic model of a soft-switching DC converter with a closed-loop control system combining the power part and the control system, intended for use as part of the latter as a digital module, was built. A technique is proposed and methods of controlling the converter are found, which provide the specified duration of transient processes, the permissible value of load current pulsations in a quasi-steady mode and the astatism of the output current, which confirms the correctness of the proposed technique. A prototype of a pulse stabilizer with digital control was made. The results of experimental studies of the sample confirm the effectiveness of the developed control device, namely the achievement of the specified duration of transient processes caused by a step change in the load current, close to 10-12 periods of conversion and astatism of the output current. It is shown that the application of a pulse stabilizer, in which a digital control loop is used, has significant advantages compared to analog options and has the advantages of a strategic plan. The use of combined control allows you to significantly reduce the requirements for the overall gain of the main control channel, which greatly facilitates the choice of sequential digital correction. Research results may be of interest to specialists in the field of power electronics, power supply systems of autonomous objects and control systems. References 14, figures 11. [ABSTRACT FROM AUTHOR]

The issue of state feedback sliding mode control (SMC) for a particular kind of active quarter-car suspension system is discussed in this work. The suspension systems' dynamic system is built with the three control objectives of maximal actuator control force, suspension deflection, and ride comfort in mind. The next step is to build the state-feedback controller with the disturbance (vibration) attenuation level in mind to guarantee the asymptotic stability of the closed-loop system. The algorithm for SMC design is introduced. It is predicated on choosing the sliding surface correctly using the invariant ellipsoid approach. The system motion in the sliding mode is guaranteed to be little affected by mismatched disturbances according to the control architecture. Furthermore, the presence of admissible controllers is articulated in terms of LMIs through the use of Lyapunov theory and the linear matrix inequality (LMI) technique. The objective is to create a desired dynamic state-feedback controller when these requirements are met. Lastly, a quarter-car model is used to illustrate how successful a suggested approach is. [ABSTRACT FROM AUTHOR]

This paper investigates the feasibility of coaxial deep borehole heat exchanger (CDBHE) applications to the University of California San Diego (UCSD) campus. By collecting different geophysical source data for various formations and well logs around the UCSD campus, a multilayered thermophysical model for the ground on the site is established. Water circulation within a closed coaxial loop system considers the geothermal energy extraction under uncertainty consideration of the unknown deeper layers heat flow gradient as coupled with the variation of pipe insulation properties, flow rates, outer pipe diameter, grout, and depths between 1 and 4 km. A finite-element framework models the Navier–Stokes fluid flow and heat transfer in the CDBHE system, validated with a field test on CDBHE from the literature. Results show that a 4-km CDBHE could produce a thermal power of 600 kW under the optimum geological conditions at the UCSD site: the water flow rate of 2.78 L/s and a ground thermal gradient of 60 ℃/km. Thermal power shares from different layers indicate that deeper formation layers contribute more to the thermal power than the shallower layers because increasing the CDBHE length from 1 to 4 km can lead to a maximum of 900% increase in thermal power and a 50% expansion in thermal plume for a CDBHE with an insulated inner pipe between the upper and lower bound heat flow bounds. An inner pipe with an insulated depth of 2 km produces only 1–6% less power than a fully insulated inner pipe for the 4-km CDBHE, and thus, a partially insulated vacuum-insulated tube (VIT)-plastic inner pipe is suggested as the best practice. Furthermore, the CDBHE thermal power increases by 5% when the grout thermal conductivity increases from 1 to 3.65 W/(K∙m), close to the formation thermal conductivity, and then maintains almost the same, and the 4-km CDBHE with flow rates of 2.78–6.94 L/s at the UCSD site can directly supply a low-temperature heating radiator system for room heating. This study suggests practical ranges for geothermal energy extraction for southern California. A CDBHE with a well-insulated inner pipe of 0.05 W/(m∙K), the thermal power of lower and upper-bound heat flow cases can vary by 60% from the mean. Finally, water as the working fluid is more efficient than CO2, doubling CDBHE's thermal power. The effects of the investigated factors provide guidelines for future geothermal resource exploitation in southern California. [ABSTRACT FROM AUTHOR]

Optimal control theory is a branch of mathematics. It is developed to find optimal ways to control a dynamic system. In 1957, R.Bellman applied dynamic programming to solve optimal control of discrete-time systems. His procedure resulted in closed-loop, generally nonlinear, and feedback schemes. Optimal control problems which will be tackled involve the minimization of a cost function subject to constraints on the state vector and the control. Lagrange multipliers provide a method of converting a constrained minimization problem into an unconstrained minimization problem of higher order. The necessary condition for optimality can be obtained as the solution of the unconstrained optimization problem of the Lagrange function and the bordered Hessian matrix is used for the second-derivative test. A spectral method for solving optimal control problems is presented. The method is based on Bernoulli polynomials approximation. By using the Bernoulli operational matrix of integration and the Lagrangian function, stochastic optimal control is transformed into an optimisation problem, where the unknown Bernoulli coefficients are determined by using Newton’s iterative method. The convergence analysis of the proposed method is given. The simulation results based on the Monte-Carlo technique prove the performance of the proposed method. Some error estimations are provided and illustrative examples are also included to demonstrate the efficiency and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of two-dimensional (2D) system-based modified preview repetitive control (MPRC) with equivalent-input-disturbance (EID) for continuous-time systems. First, an EID-based MPRC law is used to improve the tracking performance and disturbance attenuation. Next, by using a new equality constraint, a continuous-discrete 2D system is established and the design problem of the EID-based MPRC law is transformed into the stability problem of the 2D system. Then, we employ the 2D system theory together with the linear matrix inequality (LMI) approach, a sufficient condition is derived to ensure the stability of the closed-loop system. By solving an LMI, the gains of the controller and state observer can be obtained. Finally, two numerical examples are provided to illustrate the effectiveness and superiority of the developed controller design technique. [ABSTRACT FROM AUTHOR]

Power electronic converters are widely used in various fields of electrical equipment. Due to their fast dynamics and non-linear nature, controlling them requires dealing with various complexities. Therefore, having a well-designed, high-speed, and robust controller is critical to ensure the effective operation of these devices. In a DC-DC converter, steady-state performance with minimum error and fast dynamic response relies on controller design. This paper presents the design of a multi-stage PID controller with an N-filter combined with a one plus proportional derivative (1+PD) controller. This controller illustrates fast tracking reference voltage; additionally, it shows incredible results when the DC-DC converter operates in different modes. The parameters of the proposed controller are effectively determined using the golden eagle optimization (GEO) algorithm. Furthermore, a comprehensive comparison between the proposed controller, proportional–integral–derivative (PID), and fractional order PID (FOPID) controllers, as well as different metaheuristic optimization methods in various conditions, has been conducted to demonstrate the effectiveness of the proposed controller. The behavior of the closed-loop system under different conditions has been thoroughly investigated. The superior time and frequency domain characteristics of the closed-loop system with the PIDn(1+PD) controller highlight its superiority over other controllers. The demonstrated enhancements in settling time, voltage regulation accuracy, and transient response emphasize the potential applicability of the proposed control strategy in real-world power electronics systems, particularly in scenarios requiring high efficiency, stability, and dynamic performance. [ABSTRACT FROM AUTHOR]

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In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To process unknown nonlinear dynamics, radial basis function neural networks (RBFNNs) are introduced to approximate them, and some adaptive updating control laws are designed to estimate unknown parameters. Furthermore, during the dynamic surface control (DSC) design process, first-order low-pass filters are introduced to solve the complexity explosion problems caused by repeated differentiation. After that, an NN-based adaptive dynamic surface tracking controller is proposed to achieve the tracking control. By applying the proposed controller, it can be guaranteed that not only the output of the system can track the desired trajectory, but also that the tracking error can converge to a small neighborhood of zero, while all signals of the closed-loop system are bounded. Finally, the effectiveness of the proposed controller is verified through two examples. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time prescribed performance control problem for a class of axis-motion servo systems subject to the external disturbances and parameter uncertainties. To eliminate the requirement for velocity measurements in the control process, an auxiliary observer is first designed to reconstruct the velocity signal of the controlled plant. Subsequently, an error transformation procedure incorporating a prescribed performance index is integrated into the control system architecture. To overcome the limitations of periodic control design, a robust event-triggered controller is developed, ensuring that the dynamic error of the closed-loop system exhibits fixed-time convergence. Through rigorous theoretical analysis and proofs, it is demonstrated that the proposed event-triggered strategy guarantees Zeno-behavior-free operation. Finally, simulation results are presented to validate the effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This study focuses on examining the issues of extended dissipative-based composite anti-disturbance reliable tracking control for stochastic Takagi–Sugeno fuzzy systems afflicted by sensor faults and multiple disturbances. Explicitly, the multiple disturbances include the autonomous Wiener process and non random noises with partly known information that are generated by an exogenous plant. To address the difficulty of estimating the non random disturbance while considering the partially known information, the study incorporates a fuzzy stochastic disturbance observer. Furthermore, to solve the output tracking issue of the system under consideration, a modified repetitive tracking control is implemented. Then, combining the methodologies of disturbance observer-based control technique with modified repetitive control, a composite anti-disturbance reliable tracking control strategy is developed for achieving the intended tracking goal despite the multiple disturbances and sensor faults encountered. Additionally, the proposed approach involves extended dissipativity scheme, which includes $ H_\infty $ H∞, passivity, dissipativity, and $ \mathfrak {L}_2 - \mathfrak {L}_\infty $ L2−L∞ performances in a unified framework. In particular, by employing Lyapunov–Krasovskii functional approach, the essential stability criteria for the proposed closed-loop system are articulated in the form of linear matrix inequalities. Additionally, numerical illustrations are presented to exemplify the application and efficiency of the developed control protocol. [ABSTRACT FROM AUTHOR]

This paper addresses the co-design of event-triggered dynamic output-feedback (DOF) control for discrete-time linear parameter-varying (LPV) systems. Two independent event-triggering schemes are introduced to determine when to transmit data from the sensor to the controller and from the controller to the actuator channels. Enhanced conditions employing linear matrix inequalities (LMIs) are derived to establish constructive criteria for simultaneously designing the gain-scheduled DOF controller and the triggering mechanisms, ensuring the asymptotic stability of the closed-loop LPV system's origin. Additionally, a convex optimisation problem is proposed to enlarge the inter-event sampling on the independent channels of sensor-to-controller and controller-to-actuator. Numerical examples are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article investigates the trajectory tracking control problem for wheeled mobile robot (WMR) subject to both velocity and torque constraints. Firstly, a more general model is established by considering the displacement between the centre of mass and the midpoint of the driving wheels of the WMR, based on which, a new bounded kinematic controller is proposed by combining the first-order filtering approach to keep the trajectory tracking error asymptotically stable. Then the dynamic controller is designed and the stability of the overall closed-loop system is proved by the Lyapunov stability theory and Barbalat's lemma. Some conditions are given to ensure that both the velocity constraints and torque constraints are satisfied. Finally, some numerical examples are given to show the effectiveness and advantages of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

This study addresses the tracking problem for robot arms with parametric uncertainties in the model, position measurements available, and no velocity measurements. A filtering technique based on position information is used to compensate for the unmeasured velocity information. A linear filter-based controller is designed to eliminate the controller's dependence on velocity measurements by utilizing adaptive neural networks for model uncertainties. The stability of the closed-loop system is guaranteed by the Lyapunov method. To demonstrate the performance of the proposed controller, numerical simulation results are generated using a two-degree-of-freedom robot arm model and compared comparatively with adaptive fuzzy logic method. [ABSTRACT FROM AUTHOR]