Stable Control Research Articles

Research on the Application of Neural Network PID in Quadcopter Aircraft

As a highly maneuverable and flexible unmanned aerial vehicle, quadcopters have broad application prospects in both civilian and military fields. However, due to their complex dynamic characteristics, nonlinearity, and strong coupling, achieving stable and precise control of quadcopters is a challenging task. Traditional control methods often fail to meet the control performance requirements for such complex nonlinear systems. Neural networks provide a new approach to solving control problems in complex systems due to their powerful learning and adaptive capabilities. Neural networks can improve the performance of control systems by learning from large amounts of data, capturing the dynamic characteristics of the system, and adjusting control strategies online. Combining neural networks with PID control is expected to fully leverage the advantages of both. Neural networks can adjust the parameters of PID controllers in real-time, enabling them to better adapt to the complex dynamic changes and external disturbances of quadcopter aircraft. This fusion control method brings new possibilities for improving the control performance of quadcopter aircraft. This study explores the application of neural network PID in quadcopter aircraft to achieve stable and precise control, laying the foundation for its widespread promotion in practical applications.

Framework for Design Validation of Control Algorithms used on Mechanical Hardware-in-the-Loop Nacelle Test Rigs

Full scale multi-MW Wind Energy Converter (WEC) nacelles including the mechanical and electrical components as well as the main and converter control systems, are tested at the Dynamic Nacelle Testing Laboratory (DyNaLab) at Fraunhofer IWES. A Hardware-in-the-Loop environment emulates the missing rotor and accurately applies torque to the nacelle via a motor and the test rig drivetrain. In a current nacelle test campaign, several structural changes have been made to reduce the necessary adaptor tolerances of the test rig interface and to include the nacelle hub. These changes can potentially impact the system’s dynamic response and controller performance. This paper presents the current research with a focus on improving the control algorithms for accurate application of the rotor torque by implementing a simulative validation framework. The objectives of this framework include addressing the impact of modifications to the test rig drivetrain, variations in the nacelle adaptor, and communication delays between real-time simulation models, the test rig, and the WEC controller prior to performing tests on the real system. The methodology shown therefore involves three steps: controller design using a simplified multi-mass torsional model of all components necessary for testing, validation with a high-fidelity virtual test bench model and testing the resulting controller performance during the commissioning phase for the actual test. Overall, this approach is expected to reduce the commissioning duration, enhance the performance of the test rig, and identify the limitations in achieving stable torque control before the application to the real wind turbine nacelle on the test rig.

A phase II study of nivolumab in patients with recurrent or metastatic carcinosarcomas.

6041 Background: We aimed to determine the activity of anti-PD-1 inhibitor, nivolumab in metastatic and/or recurrent carcinosarcoma. Methods: In this phase 2 trial, eligible patients had histologically confirmed metastatic and/or recurrent carcinosarcoma, measurable disease, 1-3 prior chemotherapy, and adequate renal/hepatic/hematologic function. In this single arm phase 2 trial, treatment consisted of nivolumab 3 mg/kg every 2 weeks. Primary outcome was progression free rate (PFR) at 6 months and secondary outcomes included overall response rate, progression-free survival (PFS), overall survival, and safety. Results: Between July 2020 and Nov 2023, 28 patients enrolled and received trial treatment. As of the time of data cut-off (Feb 1, 2024), 4 remains on treatment. Of the 28 patients evaluable, 4 (14.3%) achieved confirmed partial response, and 9 (32.1%) had stable disease, yielding and disease control rate of 46.4%. The median PFS was 2.6 months. The pre-specified primary endpoint was met with 6-months PFR of 30.8%. The common-treatment related adverse events included urticaria (5 [17.9%]), dyspepsia (4 [14.3%]), elevated aspartate aminotransferase (3 [10.7%]), and anemia (3 [10.7%]). The genomic analysis will be available at the meeting. Conclusions: Nivolumab demonstrated promising efficacy with favourable toxicity profile in metastatic/recurrent carcinosarcoma. Clinical trial information: NCT05224999 .

Discrete-Time High-Order Fully Actuated Adaptive Stabilization Control for a Type of Combined Spacecraft With Unknown Parameters

Discrete-Time High-Order Fully Actuated Adaptive Stabilization Control for a Type of Combined Spacecraft With Unknown Parameters

Single Fuzzy Approximator-Based Stabilization Control With Multiuncertainties: A Discrete-Time Prescribed Performance Approach

Single Fuzzy Approximator-Based Stabilization Control With Multiuncertainties: A Discrete-Time Prescribed Performance Approach

Experimental validation of data-driven reactive control strategy for wave energy converters: A Gaussian process regression approach

Wave energy is a renewable energy source that can generate electricity without emitting carbon dioxide using wave energy converters (WECs). WECs face several challenges, such as effectively harnessing wave energy, ensuring operational safety, and implementing cost-saving measures. In this study, a data-driven reactive control strategy for WECs using Gaussian process regression is experimentally validated. The control strategy aimed to maximize energy absorption while satisfying physical constraints without a WEC dynamic model. In this study, the Gaussian process regression model represents a WEC dynamic model using an approximation function based on the input/output data. Experimental validation results confirmed that the proposed data-driven reactive control strategy effectively controlled the WEC and improved its performance using the Gaussian model. Moreover, performance was improved under different wave conditions compared to those used during training. The control strategy can be useful in situations where conventional methods cannot realize ideal control parameters, such as when substantial model errors exist or the WEC dynamic model changes over time. The data-driven approach that uses Gaussian process regression reduces learning costs compared to other machine-learning methods. It also has stable control performance because it is independent of the training dataset. The potential of data-driven approaches for optimizing WEC control strategies was highlighted.

Treatment with Sacubitril/Valsartan Effectively Manages Hypertension and Ameliorates Left Ventricular Hypertrophy in Hemodialysis Patients

Introduction: The aim of this study was to investigate the role of sacubitril/valsartan in managing hypertension and cardiac remodeling in patients undergoing hemodialysis. Methods: Hemodialysis patients with stable blood pressure control were enrolled in the study. Sacubitril/valsartan was prescribed to replace previously used angiotensin-converting enzyme inhibitor/angiotensin receptor blocker or other antihypertensive drugs. During a 6-month follow-up period, pre-dialysis blood pressure, routine biochemical markers, and N-terminal pro-brain natriuretic peptide levels were measured. Volume status was assessed using bioelectrical impedance analysis. Endothelial damage was evaluated by measuring asymmetric dimethylarginine expression, while echocardiography and life quality assessed by Short Form-12 Health Survey were conducted at baseline and after treatment. Results: The median daily dose of sacubitril/valsartan in 32 participants was 200 mg, and no obvious adverse reactions were reported. The defined daily dose of other antihypertensive drugs (baseline 2.00 ± 1.18, end point 1.46 ± 1.30, t = 3.216, p = 0.003) reduced significantly. After treatment with sacubitril/valsartan, left ventricular ejection fraction significantly increased from 64.81 ± 8.16% to 67.55 ± 5.85% (t = −4.022, p ≤ 0.001) and the thickness of posterior wall of the left ventricle reduced from 1.05 ± 0.14 cm to 1.00 ± 0.11 cm (t = 2.063, p = 0.048). The interventricular septal thickness (baseline 1.08 ± 0.16 cm, endpoint 1.02 ± 0.12 cm, t = 2.260, p = 0.031) remarkably reduced by the end of follow-up. The tricuspid regurgitation pressure gradient decreased from 28.47 ± 8.26 mm Hg at baseline to 23.79 ± 6.61 mm Hg (t = 2.531, p = 0.020) after treatment. Conclusion: Sacubitril/valsartan effectively manages hypertension in hemodialysis patients and may also independently improve left ventricular hypertrophy and systolic function, regardless of changes in the blood pressure or the volume load.

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.