Stable Control Research Articles

Capillary wave tweezer

Precise control of microparticle movement is crucial in high throughput processing for various applications in scalable manufacturing, such as particle monolayer assembly and 3D bio-printing. Current techniques using acoustic, electrical and optical methods offer precise manipulation advantages, but their scalability is restricted due to issues such as, high input powers and complex fabrication and operation processes. In this work, we introduce the concept of capillary wave tweezers, where mm-scale capillary wave fields are dynamically manipulated to control the position of microparticles in a liquid volume. Capillary waves are generated in an open liquid volume using low frequency vibrations (in the range of 10–100 Hz) to trap particles underneath the nodes of the capillary waves. By shifting the displacement nodes of the waves, the trapped particles are precisely displaced. Using analytical and numerical models, we identify conditions under which a stable control over particle motion is achieved. By showcasing the ability to dynamically control the movement of microparticles, our concept offers a simple and high throughput method to manipulate particles in open systems.

Cascade PID Control for Altitude and Angular Position Stabilization of 6-DOF UAV Quadcopter

UAVs are commonly used in transportation, especially in the express delivery of light cargo parcels. However, controlling UAVs is difficult because of their complex structure and wide range of operations in space. The research contribution is proposed a cascade control structure using six PID controllers for the 6-DOF UAV quadcopter, that ensures the altitude angulars positions control at the desired values and maintains flight balance stability for the 6-DOF UAV quadcopter. First, the mathematical dynamic models for the 6-DOF UAV quadcopter have been researched and developed, including the translational dynamic mathematical model and the rotational dynamic mathematical model of the 6-DOF UAV quadcopter. This is a complex object with strong nonlinearity and difficult control. And then, the article introduces the method of designing six PID controllers for 6-DOF UAV quadcopter to meet the requirements, based on applying the Ziegler-Nichols experimental method. Applying the Ziegler-Nichols experimental method makes the process of designing a UAV quadcopter control system simple, straightforward and heuristics with fast controller parameters tuning. Next, the article presents the results of modeling and simulation of the 6-DOF UAV quadcopter control system on Matlab/Simulink. The simulation results show that the six proposed PID controllers have ensured the flight balance stability at the desired altitude and angular positions with overshoot less than 20%, steady-state error less than 1%. This shows the prospect of applying the proposed PID control method to physical UAVs, easily adjusting PID parameters to suit the flight environment.

Target Tracking Two Degrees of Freedom State Feedback Control for Continuous Flow Microfluidic Chips Temperature Controller

Microfluidic chips represent a cutting-edge technology for manipulating fluids within micrometer-scale spaces and are gradually becoming a new favorite platform in life science research. Precise and fast zonal temperature control is essential for accelerating biological experiments. However, current multi-channel temperature controllers typically rely on multiple channel sets to achieve single set-point control, which results in discrepancies between the fluid temperature distribution and sensor temperature due to the distributed temperature field in the fluid channel. To estimate the actual temperature and implement gradient temperature control, this paper introduces an extension of the target tracking (TT) two degrees of freedom (2DOF) state feedback control (SFC) method, followed by a presentation of simulation and experimental results. Through comparisons with an enhanced PID system in both simulation and experimentation, the paper demonstrates an 8.96% reduction in the maximum temperature difference across different regions and a 27.89% decrease in the time taken to reach various temperatures. This solution effectively addresses the existing challenges in temperature control for microfluidic chips, offering a more precise and stable control within the desired temperature range.

The diagnostic accuracy of quality control rules

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (Ped), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (Pfr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when Ped is plotted against Pfr and only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(NUF)) than comparable Westgard rules.

A Stabilization Control Strategy for Wind Energy Storage Microgrid Based on Improved Virtual Synchronous Generator

In high-penetration renewable-energy grid systems, conventional virtual synchronous generator (VSG) control faces a number of challenges, especially the difficulty of maintaining synchronization during grid voltage drops. This difficulty may lead to current overloads and equipment disconnections, and it has an impact on the security and reliability of the system, as well as limiting the dynamic reactive power support capability of the system. To solve this problem, in this study, a wind–solar hybrid power generation system is designed with a battery energy storage device connected on the DC side, and proposes a low voltage ride-through (LVRT) control strategy for the grid-connected inverter based on an improved VSG. The control strategy employs an integrated current limiting technique combining virtual impedance and vector current limiting to ensure that the VSG exhibits good dynamic power support characteristics during symmetrical faults by adjusting the setpoint value of reactive power. At the same time, it maintains the synchronization and power angle stability of the VSG itself to achieve the goal of LVRT. Simulation results show that the proposed control strategy can effectively suppress the renewable power fluctuations (about 30% reduction in fluctuations compared to the conventional strategy) and ensure the safe and reliable operation of the renewable energy sources and VSGs during grid-side faults. In addition, it provides a given reactive power support and stable grid voltage control (voltage dips reduced by about 20%), which significantly enhances the LVRT capability of the hybrid wind–solar-storage generation system.

Feedback linearization control to avoid saturation of the high frequency transformer of a dual active bridge DC–DC converter for a DC microgrid

This paper introduces an innovative control strategy for a dual active bridges DC–DC converter employed to regulate voltage levels between two feeders in a DC microgrid. The controller is specifically designed to regulate the output voltage at a predetermined reference value and to ensure a zero mean value for both primary and secondary currents of the high-frequency transformer, regardless of any imbalance in one of the active bridges. This is particularly important in the face of potential imbalances in one of the active bridges resulting from construction disparities in converters or variations in conduction resistances in power transistors. Given the nonlinear nature of the converter, the controller is designed using feedback linearization. The output is selected with a relative degree equal to the system order, resulting in a stable controller exhibiting good dynamic performance under scenarios such as reference changes, linear load fluctuations, and the integration of constant power loads. The performance of the proposed control strategy is validated through both simulation and experimental results.

Contact detection in a rib-reinforced vacuum driven actuator with an embedded CSR bridge sensor

ABSTRACT Stable control and accurate sensing are necessary for the safe operation of soft robots, and flexible sensors that can follow the flexible movements of soft robots are needed. In this paper, flexible bending sensors are embedded in a rib-reinforced vacuum-driven actuator with no risk of rupture, considering the application of flexible sensors to human cooperative work and wearable devices. The bending sensor is a bridge circuit with conductive silicone rubber (CSR) for variable resistance. The CSR bridge sensor consists of four CSRs that capture deformation and a circuit with a conductive coating spray printed on a laminated sheet. The sensor value is the output voltage divided by the input voltage, and the effects of the drift and input voltage variations are canceled out. The bending sensor embedded in the silicone actuator has a linear relationship, and the rib-reinforced vacuum driven actuator provides angle PID control for continuously changing reference inputs by feeding back sensor estimated angle. Furthermore, contact detection was established by using the pressure estimated from the CSR bridge sensor and the pressure sensor error as the threshold. The algorithm provides reliable contact detection and force estimation with actuator response thresholds and anti-chattering.

#1533 The relationship between the severity of anemia, the level of inflammation markers and the dose of epoetin in patients in pre-dialysis stages of CKD

Abstract Background and Aims Inflammation is known to be an important factor associated with hemoglobin variability in patients with anemia of chronic disease. However, the question remains whether high levels of C-reactive protein, a widely used marker of inflammatory activity, and other inflammatory markers predict less stable anemia control in patients with CKD. The purpose of this study was to establish the relationship between the severity of anemia with the levels of inflammatory markers (C-reactive protein, IL-6) and the dose of epoetin in patients with pre-dialysis stages of CKD. The purpose of our study was to study the age-related characteristics of the nutritional status in patients with CKD of the dialysis stages who are on parenteral nutrition. Method 180 patients (96 men and 84 women) with CKD as a result of nephropathies of diabetic and non-diabetic etiology were examined. Chronic pyelonephritis was diagnosed in 96 patients, chronic glomerulonephritis - in 73, polycystic kidney disease - in 11 patients. Glomerular filtration rate was calculated based on serum creatinine concentration using the CKD-EPI formula (2011). The patients were divided into 2 groups, depending on the achievement of the target hemoglobin value. Thus, group 1 included patients with CKD C3, C4, whose hemoglobin concentration was above 110 g/l (n = 101). Group 2 included patients whose hemoglobin concentration was less than 110 g/l in at least one analysis (n = 79). Results In the examined patients, a significant correlation was found between the range of hemoglobin concentration and the range of CRP concentration (p < 0.05), as well as between the range of hemoglobin concentration and the variation in the percentage of hypochromic erythrocytes (p < 0.05), between the range of hemoglobin concentration and the variation of ferritin ( p < 0.05). The change in the percentage of hypochromic erythrocytes also correlated with the change in IL-6 (p < 0.05) and the change in CRP ( p < 0.05). We found an association between the average weekly dose of epoetin and the levels of CRP, IL-6 and TNF-α. Patients with TNF-α levels ≥2 ng/mL and IL-6 ≥40 ng/mL required a significantly higher dose of epoetin than patients with lower levels of these markers (128 U/kg per week versus 57 U/kg at week). Conclusion The establishment of a relationship between inflammatory markers and hemogram and iron parameters suggests that inflammation had an indirect effect on the increase in hemoglobin through its effect on iron metabolism. The results of the study indicate the presence of diabetic and non-diabetic etiology of systemic inflammation in CKD, more so in the group of patients with type 2 diabetes mellitus.

Optimization technology of hydroelectric power plant unit speed control based on the constriction coefficient-based particle swarm gravitational search algorithm fusion model

In recent years, the integration of wind power into hydropower networks has become a trend. But after wind power is connected to the grid, its unstable power will have an impact on the stability of the power grid. In order to improve the impact of wind power grid connection on the stability of the power supply network, a water motor speed control fusion model considering wind power interference is proposed. Firstly, analyze the impact of wind power grid connection and construct a speed regulation model for grid connected units. Secondly, the gravity search algorithm is introduced to optimize the unit speed control parameters. Considering that the algorithm is prone to local convergence, the convergence factor particle swarm optimization algorithm is adopted to optimize the gravity search algorithm. In addition, considering the impact of wind power interference on unit regulation, the Hopf bifurcation theory is introduced to analyze the dynamic regulation parameter range of hydropower units, in order to meet the requirements of stable operation of the power grid. The research contribution is mainly reflected in suppressing wind power grid connection interference through the speed regulation of hydroelectric units. At the same time, considering the impact of multiple interferences on grid connection, an intelligent model is introduced to optimize the speed control parameters of the unit, thereby improving the stable impact of wind power grid connection on the water conservancy grid. In the simulation analysis of hydroelectric unit speed regulation, after adding 5 % disturbance signal, the proposed model under rigid water hammer disturbance could stabilize the unit's stable control within 15 s, which is superior to other models. In the simulation analysis of speed regulation under wind power disturbance, the proposed model could achieve the fastest and most stable speed regulation under rigid water hammer step wind power disturbance, with a duration of 60 s. The proposed model could respond quickly to small overshoot and overshoot in elastic water hammer slope type wind power disturbances. Therefore, the proposed speed regulation technology for hydropower units has excellent application effects in practical scenarios, which will provide effective technical references for wind power grid connection and hydropower unit regulation.

Controlling the fold: proprioceptive feedback in a soft origami robot.

We demonstrate proprioceptive feedback control of a one degree of freedom soft, pneumatically actuated origami robot and an assembly of two robots into a two degree of freedom system. The base unit of the robot is a 41 mm long, 3-D printed Kresling-inspired structure with six sets of sidewall folds and one degree of freedom. Pneumatic actuation, provided by negative fluidic pressure, causes the robot to contract. Capacitive sensors patterned onto the robot provide position estimation and serve as input to a feedback controller. Using a finite element approach, the electrode shapes are optimized for sensitivity at larger (more obtuse) fold angles to improve control across the actuation range. We demonstrate stable position control through discrete-time proportional-integral-derivative (PID) control on a single unit Kresling robot via a series of static set points to 17 mm, dynamic set point stepping, and sinusoidal signal following, with error under 3 mm up to 10 mm contraction. We also demonstrate a two-unit Kresling robot with two degree of freedom extension and rotation control, which has error of 1.7 mm and 6.1°. This work contributes optimized capacitive electrode design and the demonstration of closed-loop feedback position control without visual tracking as an input. This approach to capacitance sensing and modeling constitutes a major step towards proprioceptive state estimation and feedback control in soft origami robotics.

Disturbance rejections of polynomial fuzzy systems under equivalent-input-disturbance estimator approach

This paper proposes an integrated robust stabilization and anti-disturbance control scheme for nonlinear systems using a polynomial fuzzy model approach. To estimate unknown disturbances, an equivalent-input-disturbance (EID) estimator is employed. The proposed approach incorporates a novel fuzzy model assisted by EID estimator into the sum-of-squares-based approach, utilizing a polynomial fuzzy model-based observer to estimate the disturbance effect. A suitable fuzzy rule-based control law is developed by utilizing the parallel distributed compensation approach and the output of the EID estimator. To ensure stability, fuzzy membership functions are converted into sum-of-square polynomials using a polynomial curve fitting approach, allowing their exact shape information to be used in the stability condition. The addressed system is transformed into an augmented system by incorporating the system, observer, and filter states, simplifying the analysis. Gain matrices for the controller and observer are obtained using Lyapunov stability theory and sum-of-squares methods to confirm asymptotic stabilization of the fuzzy system. Two numerical examples are presented to demonstrate the effectiveness of the proposed control design method.

Intelligent Control of Pre-Chamber Pressure Based on Working Condition Identification for the Coke Dry Quenching Process

The pre-chamber pressure is an important control parameter that affects the coke dry quenching process. It often fluctuates violently and is detrimental for the safe operation of the coke dry quenching process. This study proposes an intelligent control method for the pre-chamber pressure based on working condition identification for the coke dry quenching process to realize stable control of the pre-chamber pressure. First, by describing the coke dry quenching process and analyzing the factors affecting the pre-chamber pressure, an intelligent control strategy was developed. Then, the K-means clustering algorithm was used to identify the working conditions of pre-chamber, and the working conditions were divided into two categories: stable and fluctuating. For stable conditions, a fuzzy proportional-integral-derivative controller was designed to improve the pressure control accuracy. For fluctuating conditions, an expert controller was designed to rapidly adjust the pressure. Finally, experiments based on actual data were performed and the results showed that the proposed method can effectively improve the control accuracy of pressure under different conditions. This satisfies the requirements for a continuous coke dry quenching process.

Adaptive output feedback stabilisation control for cascaded systems with output constraints and disturbance

The system under consideration is a cascaded system composed of integral input-to-state stable inverse dynamics and a non-holonomic system. An adaptive output feedback stabilisation control is proposed for the system with disturbance and output constraints. The dynamic uncertainty is eliminated using the technique that changes the supply rate. An extended state observer is proposed by defining the non-vanishing disturbance as a new state variable of the system. The asymmetric time-varying output constraint is solved by utilising the tan-type barrier Lyapunov function. The result shows that the adaptive output feedback controller guarantees the stability of the closed-loop system without violating the asymmetric time-varying output constraints under the backstepping technique. Simulation results are given to verify the effectiveness of the control method.

Nonlinear Attitude and Altitude Trajectory Tracking Control of a Bicopter UAV in Geometric Framework

In this paper, we deal with a Bicopter drone that has two thrusters and two tilting servos. Both the position and attitude dynamics of Bicopter are globally expressed on the Special Euclidean group SE3. A simple control allocation method is proposed to map between the control wrench and actuator inputs for the Bicopter. A geometric nonlinear attitude and altitude tracking controller is developed for the Bicopter and the asymptotic stability analysis is performed using the Lyapunov method for the closed-loop nonlinear system. The performance of the proposed altitude and attitude stabilization controller is validated through experimental hardware developed in-house. The attitude controller performance is validated through simulations and shown to be comparable against an linear matrix inequality-based control law.

Multi‐event‐based distributed cooperative predictive control for the multi‐agent system

AbstractIn this paper, we provide the detailed distributed cooperative predictive control scheme for the multi‐agent system (MAS) affected by the network delays. Firstly, we restate the distributed cooperative predictive control problem by introducing iterative learning‐based MAS, which can guarantee the cooperative predictive control of the MAS. To alleviate the unfavorable network constrains, the multi‐event‐triggered conditions are formulated via considering the predictive and error data sufficiently. With these preparations, the well‐posed Roesser‐type two‐dimensional (2D) system is achieved equivalently to the distributed iterative learning predictive system. On this basis, we employ 2D predictive system analysis and control theory to realize the predictive control for the equivalent 2D system and then obtain the collaborative predictive control for the MAS under multi‐event‐triggered mechanism. The corresponding stability criteria, controller, and observer gains are provided by the executable matrix constraints and algorithms design. To conclude the paper, the numerical example is proposed to illustrate the effectiveness and practicability of the provided methods and algorithms.

The research on high efficiency water injection development of carbonate rock reservoir in the middle east

More and more attention has been paid to the waterflood development of carbonate reservoir in the Middle East with continuous expansion of the scale of carbonate reservoir development. Strong non-homogeneity of carbonate reservoirs results in serious conflicts between injection and production, causing low degree of water-driven control in the well network, and low degree of vertical mobilization. This article takes the main reservoir of an oil field in the Middle East region as an example, combining geological evaluation, dynamic analysis, and reservoir development strategies to study the effectiveness of water injection development in carbonate reservoirs. It shows that there is a correlation between pore type, oil-water relative permeability, and development method in the development of carbonate reservoirs. For reservoirs with matrix pores and micropores, water injection should be strengthened in the later stage of development; for reservoirs with dissolved pores and coarse pores, the iso-permeability point is relatively high, and the later development should focus on balanced water injection. Three different waterflooding models for formation development are designed to verify the feasibility of fine waterflooding schemes. The main differences are that one set of well patterns is combined injection and production, and three sets of well patterns are layered system waterflooding. The results show that the development effect in layered system waterflooding is the best. The daily production can be increased by about 16%, the cumulative oil production can be increased by about 8%, and the recovery factor can be increased by about 3%. Eventually, the stable oil and water control of carbonate reservoir can be realized.

Using LQR controller for vertical position control on EAST

Vertical position control is essential for stabilizing plasma with elongated configurations. The EAST tokamak is equipped with a set of in-vessel control (IC) coils dedicated to this purpose. Currently, a PD controller with fixed parameters is used for the vertical position control of EAST plasma. However, the response of the plasma in the vertical position changes with changes in plasma configuration, which can result in different control parameter requirements. It is essential to develop a model-based fast-tuning control algorithm for ensuring stability in the vertical position under different configurations. In this study, a model-based vertical position controller tuning method based on a linear quadratic regulator algorithm (LQR) is proposed. Compared with contemporary PD controllers, the proposed model-based LQR controller can enable adjusting controller parameters based on the response of the system, achieving stable control under different vertical position responses. In the EAST experiment, the model-based LQR controller achieved stable control under a shot with a continuously increasing growth rate and reached a maximum controllable vertical displacement growth rate of 968 s−1. The robustness of the system was also demonstrated in a free drift experiment. The new vertical displacement control method can be adapted to different system states and plasma configurations and improve the controllability and safety of future devices.

A longitudinal evaluation of personalized intrinsic network topography and cognitive decline in Parkinson's disease.

Resting state functional magnetic resonance imaging (R-fMRI) offers insight into how synchrony within and between brain networks is altered in disease states. Individual and disease-related variability in intrinsic connectivity networks may influence our interpretation of R-fMRI data. We used a personalized approach designed to account for individual variation in the spatial location of correlation maxima to evaluate R-fMRI differences between Parkinson's disease (PD) patients who showed cognitive decline, those who remained cognitively stable and cognitively stable controls. We compared fMRI data from these participant groups, studied at baseline and 18 months later, using both network-based statistics (NBS) and calculations of mean inter- and intra-network connectivity within pre-defined functional networks. The NBS analysis showed that PD participants who remained cognitively stable showed exclusively (at baseline) or predominantly (at follow-up) increased intra-network connectivity, whereas decliners showed exclusively reduced intra-network and inter- (ventral attention and default mode) connectivity, in comparison with the control group. Evaluation of mean connectivity between all regions of interest (ROIs) within a priori networks showed that decliners had consistently reduced inter-network connectivity for ventral attention, somatomotor, visual and striatal networks and reduced intra-network connectivity for ventral attention network to striatum and cerebellum. These findings suggest that specific functional connectivity covariance patterns differentiate PD cognitive subtypes and may predict cognitive decline. Further, increased intra and inter-network synchrony may support cognitive function in the face of PD-related network disruptions.

Research on Multi-Mode Control of Electro-Hydraulic Variable Displacement Pump Driven by Servo Motor

The electro-hydraulic power source with an electro-hydraulic variable pump driven by a servo motor is suitable for electrified construction machinery. To achieve better energy efficiency in different working conditions, the multi-mode control scheme was proposed for the electro-hydraulic power source. The control scheme includes pressure control, flow control, and torque control modes. The switching rule among the three control modes was formulated based on the minimum pump pressure. The fuzzy PID controller was designed, and a composite flow regulation strategy was formulated, including the load-sensitive adaptive displacement regulation and servo motor variable speed regulation. The AMESim-Simulink co-simulation model of multi-mode control was established. The test platform was built, and the experimental study was carried out. The results indicate that the fuzzy PID control has a shorter response time and a more stable control effect compared with PID control. Additionally, the composite flow regulation strategy improves the flow regulation range by 36% and reduces the flow overshoot by 20% compared with the load-sensitive adaptive displacement regulation. As the main control valve received an opening step signal, the full flow regulation (7~81 L/min) of the power source took approximately 0.5 s to rise and 0.2 s to fall. The relative error of pressure difference for the main control valve was 0.63%. When receiving the pressure and torque step signal, the pump pressure and pump input torque both took approximately 0.45 s to rise and 0.2 s to fall. The relative errors of pump pressure and torque control were 0.2% and 0.16%, respectively. In the multi-mode control, the electro-hydraulic power source could switch smoothly between flow control mode, pressure control mode, and torque control mode. These results provide a reference for the multi-mode control of an electro-hydraulic power source with an electro-hydraulic variable pump driven by a servo motor.

The role of 14-3-3β in acute asthma in children and analysis of the risk factors for asthma exacerbation

Objective To investigate the role of 14-3-3β in acute asthma exacerbations in children and analyze the risk factors for asthma exacerbations. Methods This study recruited 101 children with acute asthma exacerbations, 101 children with stable asthma, and 65 healthy children. Serum 14-3-3β was compared among the three groups. Factors such as asthma family history, skin prick test, serum-specific IgE test, coinfections, and clinical indicators (FeNO, FEV1, white blood cells, eosinophils, and serum IgE level) were compared between the asthma groups. Risk factors associated with acute asthma exacerbations were identified using multivariate logistic regression models. ROC curve was drawn to determine the diagnostic sensitivity and specificity of 14-3-3β. Results Serum 14-3-3β was significantly greater in the acute asthma group than in the stable asthma and control groups. Serum 14-3-3β was higher in severe acute asthma group than in mild-moderate asthma group. There were no significant differences in serum 14-3-3β levels between stable asthma and control groups (p > .05). Multivariate logistic regression analysis revealed that serum 14-3-3β level, FeNO, coinfection, and FEV1 z-score significantly increased the odds of acute asthma exacerbations in children. The optimal 14-3-3β cutoff value (39.79 ng/mL), had a sensitivity of 69.3% and specificity of 94.1% for predicting acute asthma exacerbations. Conclusions 14-3-3β is elevated in children with acute exacerbations of asthma, and increases with exacerbation severity. 14-3-3β, FeNO, FEV1, and coinfection could be independent risk factors for predicting asthma exacerbations. The optimal 14-3-3β cutoff value for predicting asthma exacerbations was 39.79 ng/mL.