Closed-loop Control Research Articles

A Digital Twin System for Adaptive Aligning of Large Cylindrical Components

Most large aerospace cylindrical components still adopt a manual aligning method with low automation, large manual intervention, and heavy dependence on operator workers, resulting in the low quality and efficiency of large component aligning, which seriously prolongs the manufacturing time of aerospace products. To cope with this issue, based on closed-loop adaptive control and digital twin (DT) technologies, an adaptive aligning system for large cylindrical components, i.e., the DT aligning system, is proposed in this study. For the DT aligning system, through the DT multi-dimensional modeling, i.e., geometric modeling, physical modeling, functional modeling, and data modeling, it can be divided into a physical space, a virtue space, and twin data. Note that the association, mapping, and interaction between physical space and virtual space of the aligning system can be realized via the twin data, thereby realizing real-time virtual display, monitoring, and control of the large component aligning. In addition, based on the measured pose data, aligning stress, and predicted aligning error, an adaptive force/position control method for large component aligning is proposed, and it can achieve real-time decision-making and precise execution of the aligning process. Finally, through application validation, the DT process system can realize the real-time status perception and process execution decision during the large component aligning. Finally, through experimental validation, it is found that the proposed system, i.e., the DT aligning system, can improve the quality and efficiency of the large aerospace cylindrical component aligning, as well as the automation and intelligent level of the aligning system.

Study on penetration depth in laser welding: A process information database-based control strategy and OCT measuring verification

Penetration depth acts as a crucial indicator reflecting laser welding quality, thus the control of its stability and the perception of its fluctuation state are increasingly garnering attention. This paper proposes a process information database-based control strategy for penetration depth, and the control validity is verified through penetration depth detection utilizing optical coherence tomography (OCT). The process information database stores diverse expected penetration depth knowledge formed by a substantial quantity of varying welding speeds with fixed other process parameters under undisturbed welding conditions. In the database, the stable average values inside the standard penetration depth information and the corresponding heat input (HI) values are connected and mapped via an artificial neural network (ANN). In response to abnormal variations in the penetration depth curve caused by interferences during welding, according to the HI gap predicted by the trained ANN from the penetration depth gap arising from the curve deviation, the control unit can calculate the new welding speed required to feed the penetration depth curve back to within the steady fluctuation range. Based on OCT, the keyhole depth signal is acquired, and a deep belief network is built to predict the penetration depth curve via the correlation between the reconstructed keyhole depth obtained by ensemble empirical mode decomposition and the penetration depth. This detection method demonstrates that the penetration depth curve can be controlled accurately. Finally, a closed-loop real-time feedback control system for penetration depth is established.

Stability enhancement for seamless control in networked microgrids with energy storage: Nonlinear spatio-temporal control perspective

The integration of distributed energy resources into modernized networked microgrids, combined with the increasing variability in load dynamics, presents significant stability challenges. This research offers a comprehensive analysis of the stability of cascaded interactions in nonlinear multi-timescale systems, including grid-following and grid-forming inverters. The proposed grid-forming controller, integrated with energy storage systems and a nonlinear Lyapunov function, facilitates seamless control and stabilization of these inverters. This approach addresses challenges related to nonlinear plant and network dynamics, uncertainties in state variables, and unmodeled system dynamics. The closed-loop control system ensures asymptotic spatio-temporal dynamical stability through constrained time state convergence to stable equilibrium points while minimizing control oscillations. Comparative analysis and high-fidelity hardware-in-loop emulations demonstrate the superior performance of the proposed controller over traditional ones in diverse dynamic scenarios. Its ability to rapidly reject disturbances, minimize overshoot, converge efficiently, and enhance power quality confirms its effectiveness and highlights its potential for real-world applications.

Trajectory tracking of Jiaolong submersible with velocity constraints via dual closed-loop control

Trajectory tracking of Jiaolong submersible with velocity constraints via dual closed-loop control

Disturbance rejection for switched singular systems using state decomposition technique and equivalent-input-disturbance with a dynamic state observer

In this study, an equivalent-input-disturbance (EID) method with a dynamic state observer and a state decomposition technique (SDT) are used to explore the disturbance rejection of a class of linear switched singular systems. The EID approach defines an EID signal, is defined for the control input channel and has the same impact on the system as exogenous disturbances. Additionally, it employs an observer to estimate the EID and achieves good disturbance-rejection performance. However, in the EID method, the coefficient matrix of the observer needs to be consistent with the coefficient matrix of the original system, which limits the application of the method. So, a dynamic state observer is designed to reconstruct the system state and estimate the disturbance in this study. Based on the state feedback control strategy, a disturbance-rejection control law containing disturbance information is designed and a closed-loop control system structure is established. Subsequently, the state equation of the closed-loop system is reorganized and decomposed into an algebraic equation and a differential equation using the SDT. Then, a Lyapunov function with few decision variables is designed to obtain an admissible criterion for the closed-loop system and the controller gains under arbitrary switching signals. Finally, the effectiveness of the presented method is verified via numerical simulations.

Optimal control transport of neutral atoms in optical tweezers at finite temperature

The transport of neutral atoms in Rydberg quantum computers is a crucial step for the initial arrangement of the grid as well as the dynamic connectivity, recently successfully demonstrated. We study the application of optimal control and the quantum speed limit for the transport of neutral atoms in optical tweezers at finite temperatures and analyze how laser noise affects transport fidelity. Open-loop optimal control significantly enhances transport fidelity, achieving an improvement up to 89% for the lowest analyzed temperature of 1µK for a distance of 3µm. Furthermore, we simulate how the transport fidelity behaves in release-and-capture measurements, which are realizable in the experiment to estimate transport efficiency and implement closed-loop optimal control. Published by the American Physical Society 2024

Fixed-time and predefined-time group-bipartite consensus for uncertain networked Euler-Lagrange systems

This paper aims to investigate the fixed-time and predefined-time group-bipartite consensus (FTGBC, PTGBC) problems for uncertain networked Euler-Lagrange systems (NELSs) using neural network (NN). An auxiliary sliding mode variable describing the local communication topology is first introduced within the fixed-time and predefined-time frameworks, and the NN technique is used to estimate online uncertainty of NELSs, which ensures the achievement of the desired FTGBC and PTGBC goals, respectively. Moreover, the allowable upper bound expressions for fixed-time and predefined-time are derived by analyzing the convergence of the closed-loop control systems, thus ensuring the adaptability, stability, and robustness of the proposed FTGBC and PTGBC control schemes, which are further verified by numerical simulation examples.

Closed-loop oxygen usage during invasive mechanical ventilation of pediatric patients (CLOUDIMPP): a randomized controlled cross-over study.

The aim of this study is the evaluation of a closed-loop oxygen control system in pediatric patients undergoing invasive mechanical ventilation (IMV). Cross-over, multicenter, randomized, single-blind clinical trial. Patients between the ages of 1 month and 18 years who were undergoing IMV therapy for acute hypoxemic respiratory failure (AHRF) were assigned at random to either begin with a 2-hour period of closed-loop oxygen control or manual oxygen titrations. By using closed-loop oxygen control, the patients' SpO2 levels were maintained within a predetermined target range by the automated adjustment of the FiO2. During the manual oxygen titration phase of the trial, healthcare professionals at the bedside made manual changes to the FiO2, while maintaining the same target range for SpO2. Following either period, the patient transitioned to the alternative therapy. The outcomes were the percentage of time spent in predefined SpO2 ranges ±2% (primary), FiO2, total oxygen use, and the number of manual adjustments. The median age of included 33 patients was 17 (13-55.5) months. In contrast to manual oxygen titrations, patients spent a greater proportion of time within a predefined optimal SpO2 range when the closed-loop oxygen controller was enabled (95.7% [IQR 92.1-100%] vs. 65.6% [IQR 41.6-82.5%]), mean difference 33.4% [95%-CI 24.5-42%]; P < 0.001). Median FiO2 was lower (32.1% [IQR 23.9-54.1%] vs. 40.6% [IQR 31.1-62.8%]; P < 0.001) similar to total oxygen use (19.8 L/h [IQR 4.6-64.8] vs. 39.4 L/h [IQR 16.8-79]; P < 0.001); however, median SpO2/FiO2 was higher (329.4 [IQR 180-411.1] vs. 246.7 [IQR 151.1-320.5]; P < 0.001) with closed-loop oxygen control. With closed-loop oxygen control, the median number of manual adjustments reduced (0.0 [IQR 0.0-0.0] vs. 1 [IQR 0.0-2.2]; P < 0.001). Closed-loop oxygen control enhances oxygen therapy in pediatric patients undergoing IMV for AHRF, potentially leading to more efficient utilization of oxygen. This technology also decreases the necessity for manual adjustments, which could reduce the workloads of healthcare providers. This research has been submitted to ClinicalTrials.gov (NCT05714527).

Enhancing HVAC multivariable system performance through hybrid modeling and direct Nyquist Array control

This study explores a closed-loop multivariable control system for HVAC systems. A hybrid distributed parameter-lumped model was developed using MATLAB’s System Identification Application, resulting in a transfer function matrix. The Direct Nyquist Array (DNA) control strategy was applied, dividing the HVAC system into two SISO loops, each equipped with PID controllers. Stability analysis confirmed system stability according to the Nyquist criterion. Simulation of the system under DNA control showed improved performance over the open-loop setup, with faster response times of nearly 1 s and overshoots between 7% and 15%, maintaining thermal comfort and occupant satisfaction. The system effectively managed ambient heat transfer variations, maintaining desired airflow rate and air temperature. The closed-loop setup exhibited robustness against disturbances, quickly returning to steady-state values. Settling times ranged from 1 to 2 s with minimal impact on HVAC performance. Overall, the closed-loop multivariable DNA control with SISO PID controllers proved reliable for enhancing energy efficiency and thermal comfort in HVAC systems. Practical application This study provides a comprehensive framework for multivariable control in HVAC systems, significantly benefiting built environment professionals by enhancing energy efficiency and occupant comfort. By applying advanced control strategies, the research offers practical solutions for optimizing HVAC performance, reducing operational costs, and ensuring sustainability in building management. The detailed analysis and methodologies presented can be directly implemented to improve system reliability and responsiveness, thereby supporting professionals in creating smarter, more resilient, and environmentally friendly built environments.

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

Penetration State Recognition during Laser Welding Process Control Based on Two-Stage Temporal Convolutional Networks.

Vision-based laser penetration control has become an important research area in the field of welding quality control. Due to the complexity and large number of parameters in the monitoring model, control of the welding process based on deep learning and the reliance on long-term information for penetration identification are challenges. In this study, a penetration recognition method based on a two-stage temporal convolutional network is proposed to realize the online process control of laser welding. In this paper, a coaxial vision welding monitoring system is built. A lightweight segmentation model, based on channel pruning, is proposed to extract the key features of the molten pool and the keyhole from the clear molten pool keyhole image. Using these molten pool and keyhole features, a temporal convolutional network based on attention mechanism is established. The recognition method can effectively predict the laser welding penetration state, which depends on long-term information. In addition, the penetration identification experiment and closed-loop control experiment of unequal thickness plates are designed. The proposed method in this study has an accuracy of 98.96% and an average inference speed of 20.4 ms. The experimental results demonstrate that the proposed method exhibits significant performance in recognizing the penetration state from long sequences of welding image signals, adjusting welding power, and stabilizing welding quality.

Robust Control of Exo-Abs, a Wearable Platform for Ubiquitous Respiratory Assistance

Abstract Existing noninvasive breathing assist options compatible with out-of-hospital settings are limited and not appropriate to enable essential everyday activities, thereby deteriorating the quality of life. In our prior work, we developed the Exo-Abs, a novel wearable robotic platform for ubiquitous assistance of respiratory functions in patients with respiratory deficiency. This paper concerns the development of a model-based closed-loop control algorithm for the Exo-Abs to automate its breathing assistance. To facilitate model-based development of closed-loop control algorithms, we developed a control-oriented mathematical model of the Exo-Abs. Then, we developed a robust absolutely stabilizing gain-scheduled proportional-integral control algorithm for automating the breathing assistance with the Exo-Abs, by (i) solving a linear matrix inequality formulation of the Lyapunov stability condition against sector-bounded uncertainty and interindividual variability in the mechanics of the abdomen and the lungs and (ii) augmenting it with a heuristic yet effective gain scheduling algorithm. Using in silico evaluation based on realistic and plausible virtual patients, we demonstrated the efficacy and robustness of the automated breathing assistance of the Exo-Abs under a wide range of variability in spontaneous breathing and Exo-Abs efficiency: the absolutely stabilizing gain-scheduled proportional-integral control resulted in small exhalation trajectory tracking error (&amp;lt;30 ml) with smooth actuation, which was superior to (i) its proportional-integral control counterpart in tracking efficacy and to (ii) its proportional-integral-derivative control counterpart in chattering.

Variational analysis of sensory feedback mechanisms in powerstroke-recovery systems.

Although the raison d'etre of the brain is the survival of the body, there are relatively few theoretical studies of closed-loop rhythmic motor control systems. In this paper we provide a unified framework, based on variational analysis, for investigating the dual goals of performance and robustness in powerstroke-recovery systems. To demonstrate our variational method, we augment two previously published closed-loop motor control models by equipping each model with a performance measure based on the rate of progress of the system relative to a spatially extended external substrate-such as a long strip of seaweed for a feeding task, or progress relative to the ground for a locomotor task. The sensitivity measure quantifies the ability of the system to maintain performance in response to external perturbations, such as an applied load. Motivated by a search for optimal design principles for feedback control achieving the complementary requirements of efficiency and robustness, we discuss the performance-sensitivity patterns of the systems featuring different sensory feedback architectures. In a paradigmatic half-center oscillator-motor system, we observe that the excitation-inhibition property of feedback mechanisms determines the sensitivity pattern while the activation-inactivation property determines the performance pattern. Moreover, we show that the nonlinearity of the sigmoid activation of feedback signals allows the existence of optimal combinations of performance and sensitivity. In a detailed hindlimb locomotor system, we find that a force-dependent feedback can simultaneously optimize both performance and robustness, while length-dependent feedback variations result in significant performance-versus-sensitivity tradeoffs. Thus, this work provides an analytical framework for studying feedback control of oscillations in nonlinear dynamical systems, leading to several insights that have the potential to inform the design of control or rehabilitation systems.

Suppression of solar array vibration by torque compensation using a magnetorheological actuator: A hardware-in-the-loop test study

Sun-tracking-induced vibrations of a large flexible solar array are characterized by a wide frequency range and persistent disruptions, making them an important challenge for a high-precision spacecraft. This paper describes a hardware-in-the-loop test for a novel vibration suppression method that employs magnetorheological torque compensation. To provide the compensating torque, a test bench is built using a magnetorheological actuator (MRA). A comprehensive model is employed to quantitatively analyze suppressions in terms of solar array driving, solar array motion, and spacecraft disturbance. For comparison, the test is run in both open-loop and closed-loop modes. The results demonstrate that with closed-loop control, the maximum fluctuation of driving torque decreases by 50.90%. The sun tracking achieves a more stable speed. Moreover, disturbances produced by the vibration of the solar array are decreased by 59.84%. These findings suggest that using torque compensation with an MRA can successfully reduce the sun-tracking-induced vibration of a large flexible solar array while minimizing the impact on the spacecraft platform.

Comprehensive compensation method for co‐phase power supply in electrified railways based on V/v transformer and electromagnetic single‐phase var compensator

AbstractTo solve the problem of negative‐sequence and reactive power in electrified railway, this paper proposes a comprehensive compensation method based on V/v transformer and electromagnetic single‐phase var compensator (ESVC) for co‐phase power supply. First, based on the principles of static var generator and single‐phase rotary phase shifting transformer, the topology and model of ESVC have been established, and the compensation mechanism has been analysed. Second, the topological structure and mathematical model of co‐phase power comprehensive compensation device (CPCD) are put forward based on the principles of V/v transformer and ESVC, and the operation mode of CPCD in multiple scenarios is designed. Then the strategy of CPCD with double closed loop control is analysed: corresponding compensation mode is selected according to negative‐sequence unbalance degree and expected power factor value. In this strategy, the compensated current output by ESVC is taken as the quantity of external loop control, and the rotation angle of ESVC is taken as the quantity of internal loop control to realize double‐closed loop control of CPCD. Finally, the comprehensive CPCD compensation model is built on the simulation platform and validated the accuracy of the mathematical model and the effectiveness of the control strategy.

H2 norm based parameter optimization of multiple tuned mass dampers for resonance suppression

Flexible dynamic behavior of ultra-precision motion stage significantly deteriorates control performance. To tackle this problem, this paper presents an [Formula: see text] norm based parameter optimization of multiple Tuned Mass Dampers (TMDs) for resonance suppression applied on linear flexible structures, assuming all parameters of multiple TMDs are independent, and considering locations of TMDs as variables. Linear flexible structures with multiple TMDs are modeled as a closed-loop control system through modeling in steps. Genetic algorithm is implemented employing [Formula: see text] norm as the optimization criterion. The effectiveness of the optimization is numerically verified on a free-free thin plate. The effects of uncertainties in TMDs parameters, linear flexible structure parameters, and TMDs failure on the vibration suppression effect are studied. The proposed modeling and optimization methods are promising for application to various flexible structures with provided modal frequencies and mode shape matrix.

Immersion and Invariance Adaptive Control through Polynomial Adaptation

Abstract In conventional immersion and invariance (I&amp;I) adaptive control design, control parameter adaptation is typically linear with respect to the parameter-error-induced perturbation, resulting in quadratic-rate dissipation of energy associated with the off-the-manifold variable. Departing from such a convention, this article contributes a novel strategy - polynomial adaptation. As the name suggests, control parameter adaptation in this approach takes the form of a general polynomial in relation to the perturbation. Accordingly, this new design induces polynomial-rate energy dissipation, which is faster than the quadratic one in the conventional scheme, thereby enhancing closed-loop control performance. The theoretical underpinnings of the new approach are demonstrated through the design of an I&amp;I adaptive tracking control law for a general nth-order, single-input-single-output, parametrically uncertain, nonlinear system in the controllable canonical form. Additionally, a numerical study of the proposed method on the second-order forced Duffing oscillator showcases its improved transient performance in comparison to a baseline controller developed with the standard I&amp;I adaptive control technique.

Design a Computer Controlled Unmanned Underwater Vehicle Thruster Using Smart Closed Loop Controller

The first step of designing an Unmanned Underwater Vehicle (UUV) depends mainly on the selection of the thrusters as UUVs require many thrusters to be installed onboard for smooth operation. The widely used thrusters in UUVs are has relatively large dimensions and they just spin in the water without reporting any kind of important information such as the status of the thruster and the RPM of the motor. This project aims to design and implement a new computer-controlled thrusting system from end-to-end that fits various UUVs with more advantages including smaller size thruster, cheaper in price, and with more additional smart capabilities that reports thruster’s instantaneous RPM, power consumption, proper operation, malfunctions, damages, and water stream blockage.

A new positive output DC–DC buck–boost converter based on modified boost and ZETA converters

A new DC–DC buck–boost converter with a wide conversion ratio is presented in this paper. The proposed buck–boost converter consists of a combination of modified boost converter and ZETA converter, which has the advantages of both converters such as continuous input/output current and positive polarity of the output voltage. The combination of these two converters achieves semi-quadratic voltage gain and makes the proposed converter suitable for industrial and renewable energy applications. With a voltage gain higher than that of the ZETA converter and modified boost converter, the proposed converter also reduces input current stress due to its continuity. Two operating states are available for this converter in continuous conduction mode. This converter has two switches that operate simultaneously and can be easily controlled. The converter's output voltage ripple and output capacitor current stress are reduced as a result of continuous output current. Computational analysis and the introduced structure efficiency considering the influence of parasitic elements are presented in this paper. The small signal modelling and closed-loop control, as well as simulation and experimental results are also presented. This converter has also been compared with other similar and recently presented topologies. Finally, a 40–60 W, 20–76 V for boost mode and 10 V for buck mode prototype was implemented to verify the accuracy of the computational analysis.

Model Predictive Temperature Control for Retinal Laser Treatments.

Manual, individual adjustment of the laser power in retinal laser therapies is time-consuming, is inaccurate with respect to uniform effects, and can only prevent over- or undertreatment to a limited extent. Automatic closed-loop temperature control allows for similar temperatures at each irradiated spot despite varying absorption. This is of crucial importance for subdamaging hyperthermal treatments with no visible effects and the safety of photocoagulation with short irradiation times. The aim of this work is to perform extensive experiments on porcine eye explants to demonstrate the benefits of automatic control in retinal laser treatments. To ensure a safe and reliable temperature rise, we utilize a model predictive controller. For model predictive control, the current state and the spot-dependent absorption coefficients are estimated by an extended Kalman filter (EKF). Therein, optoacoustic measurements are used to determine the temperature rise at the irradiated areas in real time. We use fluorescence vitality stains to measure the lesion size and validate the proposed control strategy. By comparing the lesion size with temperature values for cell death, we found that the EKF accurately estimates the peak temperature. Furthermore, the proposed closed-loop control scheme works reliably with regard to similar lesion sizes despite varying absorption with a smaller spread in lesion size compared to open-loop control. Our closed-loop control approach enables a safe subdamaging treatment and lowers the risk for over- and undertreatment for mild coagulations in retinal laser therapies. We demonstrate that modern control strategies have the potential to improve retinal laser treatments for several diseases.