Practical Control Method Research Articles

An Improved Artificial Electric Field Algorithm for Determining the Maximum Length of Gravel Packing in Deep-Water Horizontal Well

Gravel packing in deep-water horizontal wells is an effective and practical sand control method, which is a key technical method to ensure efficient exploitation of deep-water oil and gas. To ensure the successful implementation of gravel packing in deep water horizontal wells, it is crucial to carry out effective optimization design of packing parameters. This paper proposes a novel optimization design approach for gravel packing in deep-water horizontal wells. In the proposed approach, an optimization model is proposed for gravel packing in deep-water horizontal wells, in which the gravel packing length is regarded as the objective function. Then, an improved artificial electric field algorithm (IAEFA) is introduced for optimizing the key gravel packing parameters so as to determine the maximum gravel packing length. For a specific case study, we conducted optimization calculations for gravel packing in a deep-water horizontal well. Results of the case study demonstrate that the optimization design approach based on the IAEFA algorithm can effectively address the parameter optimization problem of deep-water horizontal well gravel packing. For the target well of the case study, the maximum packing length obtained by the IAEFA algorithm could reach 1000.22 m, and the corresponding 3 sets of optimal packing parameters were also obtained. In the scenario of optimal packing parameters, the total time of gravel packing in target well is 566.6 min, and the total amount of sand consumption is 54,050.94 lbs. The bottom hole pressure during the injection stage remains stable with about 9780 psi, then slowly rises from 9788 psi to 9837 psi in the α-wave packing stage, and rapidly increases from 9837 psi to 9986 psi in the β-wave packing stage. The proposed approach provides an efficient and practical optimization tool for the optimal design of gravel packing in deep water horizontal wells.

Robust controller design and experimental validation based on bounded uncertainty for collaborative industrial robots.

In this paper, derived from the proportional-derivative control and robust control, a novel practical robust control method based on a dynamic feedforward model is established by taking six-axis motion cooperative industrial robots as the research object. The nonlinear friction, parameter uncertainty, and external disturbance are taken into consideration while establishing the dynamic model of the cooperative industrial robot. The method includes a proportional-derivative control and a robust control. Lyapunov theory is used to analyze the proposed controller, and it is shown that this method can guarantee uniformly bounded and uniformly final bounded systems. Simulation and experiment results show that the proposed controller is better than proportional-integral-derivative control and mode-based proportional-derivative control in stability tracking performance and robustness. In addition, the CSPACE platform for rapid controller prototyping may reduce the arduous programming effort and offer a lot of ease for the trials.

Discrete-Time Visual Servoing Control with Adaptive Image Feature Prediction Based on Manipulator Dynamics.

In this paper, a practical discrete-time control method with adaptive image feature prediction for the image-based visual servoing (IBVS) scheme is presented. In the discrete-time IBVS inner-loop/outer-loop control architecture, the time delay caused by image capture and computation is noticed. Considering the dynamic characteristics of a 6-DOF manipulator velocity input system, we propose a linear dynamic model to describe the motion of a robot end effector. Furthermore, for better estimation of image features and smoothing of the robot's velocity input, we propose an adaptive image feature prediction method that employs past image feature data and real robot velocity data to adopt the prediction parameters. The experimental results on a 6-DOF robotic arm demonstrate that the proposed method can ensure system stability and accelerate system convergence.

Biological Control Options for the Management of Tadpole Shrimp (Triops longicaudatus (LeConte)) in California Rice

Tadpole shrimp (Triops longicaudatus) has become a major pest for California rice farmers. Currently, management relies solely on the insecticide lambda-cyhalothrin. However, resistance to this pyrethroid was confirmed in 2016; thus, identifying an effective and practical biological control method for TPS is a priority. Field trials were conducted from 2017 to 2018 to (1) evaluate the efficacy of the predatory fish Gambusia affinis and the predatory beetles, Laccophilus maculosus (Say) and Tropisternus lateralis (Fabricius), in controlling TPS, (2) test the efficacy of several inoculation rates of Gambusia affinis at controlling TPS and (3) to explore early indicators of TPS activity and damage as monitoring tools. Both Gambusia affinis and the predatory beetle treatments were not significantly different from the commercial standard (lambda-cyhalothrin). Both four and five Gambusia per 1 m2 controlled TPS as well as lambda-cyhalothrin, and we observed that Gambusia affinis was able to reproduce in the field. Water turbidity was significantly correlated with TPS counts (R = 0.85, N = 20, p < 0.0001 (2017); R = 0.58, N = 30, p = 0.0007 (2018)). The number of dislodged seedlings was less reliably correlated with TPS count; in 2017, correlations were significant (R = 0.84, N = 20, p < 0.0001); however, in 2018, correlations were not significant (R = 0.18, N = 30, p = 0.35). With further refinement, water turbidity could play a valuable role in monitoring TPS populations.

Practical Method for Voltage Control in Active Distribution Network Based on Sensitivity

Abstract The access of a large number of distributed photovoltaic power stations makes the voltage problem of the distribution network more prominent, but also provides controllable resources for the distribution network. In order to exploit the regulation potential of distributed photovoltaic power stations in active distribution networks, a practical method for voltage control based on sensitivity is proposed. The adjustment nodes and adjustment amounts are determined according to sensitivity. Based on the power flow equation, the voltage sensitivity calculation is appropriately simplified to reduce the amount of calculation. By combining forecast data and network topology, a control architecture for parallel calculation of sensitivity analysis, reactive power regulation capacity analysis, and real-time voltage control is proposed. This architecture decouples sensitivity calculation from real-time regulation and control, improving the processing speed and reliability of real-time voltage regulation and control. A case study based on a 10kV distribution network in a certain area shows that although the proposed sensitivity calculation method has some deviation, it can meet the requirements of engineering practicality and effectively achieve voltage over-limit control.

Selected aspects of the operation of Dual Active Bridge DC/DC converters

This review paper discusses the concept of a bidirectional Dual Active Bridge (DAB) DC/DC converter. Practical applications and control methods are explored, and various types of DAB converters are introduced and characterized. Aspects of operation are discussed, enriched by the results of theoretical analyses, simulations, and experimental measurements of the original authors works.

Efficient Quality Control of Peptide Pools by UHPLC and Simultaneous UV and HRMS Detection

Peptide pools consist of short amino acid sequences and have proven to be versatile tools in various research areas in immunology and clinical applications. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products which makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. Usually, this would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, worsening the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector at 214 nm for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF advanced, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein–Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

Practical fixed-time neural control for MIMO non-strict feedback nonlinear systems: an adaptive neural network approach

ABSTRACT This paper studies the non-singular practical fixed-time neural adaptive control issues for multi-input and multi-output (MIMO) nonlinear systems with non-strict feedback form. Neural networks (NN) are used to estimate the unknown nonlinearities and deal with the problem of an algebraic loop. Under the framework of the backstepping control design, a practical fixed-time adaptive NN control method is developed by using the adding power integration technology. According to the Lyapunov function theory, it is proved that the closed-loop system is practical fixed-time stable, and the system can track the desired reference signal within a fixed time. Finally, the proposed practical fixed-time control method is applied to a multi-motor control platform, which proves the effectiveness of the control method.

Research on fluidic thrust vector technology based on passive secondary flow with dual inclined walls under low subsonic speed

The application of fluidic thrust vector technology enables active flow control to deflect the jet. At present, hysteresis and abrupt jump phenomena have been found in the control law of fluidic thrust vector technology based on the Coanda effect. To weaken the abrupt jump and eliminate hysteresis phenomena, a new fluidic thrust vectoring nozzle based on passive secondary flow with dual inclined walls (PSDW) was developed. In this paper, the flow thrust vectoring characteristics of the the new fluidic thrust vectoring nozzle were studied by experimental method. By using PSDW, the flow vectoring angle could reach up to 29° and the thrust vectoring angle could be controlled continuously from 0° to 25°. The linearity of vectoring control over the first and the second inclined wall were 65% and 79%, respectively. There were no obvious hysteresis phenomena in the control process. The abrupt jump and hysteresis phenomenon could be eliminated in the thrust vector control law by PSDW, which provides a practical control method for jet deflection.

Learning Hybrid Policies for MPC with Application to Drone Flight in Unknown Dynamic Environments

In recent years, drones have found increased applications in a wide array of real-world tasks. Model predictive control (MPC) has emerged as a practical method for drone flight control, owing to its robustness against modeling errors/uncertainties and external disturbances. However, MPC’s sensitivity to manually tuned parameters can lead to rapid performance degradation when faced with unknown environmental dynamics. This paper addresses the challenge of controlling a drone as it traverses a swinging gate characterized by unknown dynamics. This paper introduces a parameterized MPC approach named hyMPC that leverages high-level decision variables to adapt to uncertain environmental conditions. To derive these decision variables, a novel policy search framework aimed at training a high-level Gaussian policy is presented. Subsequently, we harness the power of neural network policies, trained on data gathered through the repeated execution of the Gaussian policy, to provide real-time decision variables. The effectiveness of hyMPC is validated through numerical simulations, achieving a 100% success rate in 20 drone flight tests traversing a swinging gate, demonstrating its capability to achieve safe and precise flight with limited prior knowledge of environmental dynamics.

Assessment of Soil Erosion Susceptibility, Spatial Sediment Delivery Processes and Control Strategies at the Nzoia River Catchment in Kenya

The Nzoia basin is among the most densely populated regions in Western Kenya, with an average density of up to 450 people per square kilometre. Cereal farming accounts for over half of the land usage in the basin. The massive conversion of land from forest to cropland and grassland in the region has significantly impacted soil erosion and reduced soil fertility. Several studies have been undertaken in the catchment, principally on potential soil loss; however, no extensive research has been conducted on the spatial sediment delivery processes or on establishing the best land management practices for the catchment. This study simulates the basin’s susceptibility to erosion using the RUSLE model, examines the spatial sediment delivery process, and undertakes scenario analysis to establish the best erosion control practices for the catchment. The RUSLE factors were combined in ILWIS GIS to create functions for soil erosion and sediment transport capacity, which were applied to compute the potential annual soil loss for each pixel. The formulated sediment routing algorithm directed the sediments toward the river and the lake. The results from the study show that potential annual soil loss varied from 0.00 in the lowlands to 4,577 tonnes/ha/year in the highland areas, with the catchment’s total potential soil loss estimated at 8,380,000 tonnes/year. The basin’s sediment yield at Lake Victoria was 2,494,575 tons/year, translating to a sediment delivery ratio of about 29%. The cropland regions were the dominant contributors of eroded sediments. The scenario analysis applied practical agronomic and mechanical erosion control methods to croplands, demonstrating that adopting multiple soil erosion control strategies could effectively reduce soil loss across the catchment. Areas with high erosion are primarily found in the sloping regions of the catchment, especially around Mt. Elgon, Chereng’anyi Hills, Kipkaren, and Kapsokwony. The spatial soil erosion and deposition hazard maps generated in this study should be used as practical guides for combating land degradation in the Nzoia River catchment.

A strength model for cement-stabilized mud subjected to various curing temperatures and its early-stage quality control

The influence of curing temperature on the strength development of cement-stabilized mud has been well documented in terms of strength-increase rate and ultimate strength. However, the strength development model is not mature for the extremely early stages. In addition, there is a lack of studies on quality control methods based on early-stage strength development. This paper presents a strength model for cement-stabilized mud to address these gaps, considering various curing temperatures and early-stage behaviors. In this study, a series of laboratory experiments was conducted on two types of muds treated with Portland blast furnace cement and ordinary Portland cement under four different temperatures. The results indicate that elevated temperatures expedite strength development and lead to higher long-term strength. The proposed model, which combines a three-step conversion process and a hyperbolic model at the reference temperature, enables accurate estimate of the strength development for cement-treated mud with any proportions cured under various temperatures. With this model, a practical early quality control method is introduced for applying cement-stabilized mud in field projects. The back-analysis parameters obtained from a 36-h investigation at temperature of 60 °C demonstrated a sufficient accuracy in predicting strength levels in practical applications.

A new distributed voltage control method for MVDC electric railway systems with renewable energy sources

The medium voltage DC (MVDC) electric railway system is one of the most interesting options for future high-speed rail (HSR) lines. The dc voltage control is one of the most critical challenges of MVDC electric railway systems due to various reasons such as simultaneous, continuous and considerable changes in the power and location of trains, regenerative brake energy of trains, long power lines, the application of ESS’s and RES’s. In this paper, a voltage control, i.e., the optimal-voltage voltage-power (OVVP) control method, is presented for MVDC electric railway systems. OVVP control method is a practical, reliable, automatic, and modular distributed voltage control method. The proposed voltage control method satisfies the nearest voltage to the nominal value in each node and the smoothest voltage profile in different MVDC electric railway systems. Although the analyses carried out in this paper analytically prove the significant performance of the presented voltage control method, different challenging scenarios are considered to verify OVVP control method more. In addition, the results of the proposed voltage control method are successfully validated by GAMS software.

Robust trajectory tracking control design for the robotic arm with uncertainty and experimental validation

The robotic arm is a complicated system with multiple inputs and outputs, strong coupling, containing uncertainties and nonlinearities. This study proposes a new practical robust control method based on the dynamics model and tracking error, including a model- and error-based proportional-differential feedback term and an error-based robust term. Specifically, the dynamics of the system are modeled using the Lagrangian method. Uncertainties are presumed to be time-varying but limited. Based on the Lyapunov method, the proposed controller has theoretically demonstrated the controlled system with uniform boundedness (UB) and uniform ultimate boundedness (UUB). Furthermore, the radius of the ultimately bounded hypersphere is arbitrarily small based on selecting appropriate design parameters. Based on the two-degree-of-freedom (2-DOF) planar robotic arm experimental platform, the self-developed rapid controller prototype CSPACE-RT is intended to eliminate tedious programming or debugging, significantly simplifying the experimental process. Finally, numerical simulation and experiment results verified the excellent control performance of the suggested controller.

Genome-Wide Association Mapping of Bacterial Leaf Streak Resistance in Two Elite Barley Breeding Panels.

Bacterial leaf streak (BLS), caused chiefly by the pathogen Xanthomonas translucens pv. translucens, is becoming an increasingly important foliar disease of barley in the Upper Midwest. The deployment of resistant cultivars is the most economical and practical method of control. To identify sources of BLS resistance, we evaluated two panels of breeding lines from the University of Minnesota (UMN) and Anheuser-Busch InBev (ABI) barley improvement programs for reaction to strain CIX95 in the field at St.Paul and Crookston, MN, in 2020 and 2021. The percentage of resistant lines in the UMN and ABI panels with mid-season maturity was 1.8% (6 of 333 lines) and 5.2% (13 of 251 lines), respectively. Both panels were genotyped with the barley 50K iSelect SNP array, and then a genome-wide association study was performed. A single, highly significant association was identified for BLS resistance on chromosome 6H in the UMN panel. This association was also identified in the ABI panel. Seven other significant associations were detected in the ABI panel: two each on chromosomes 1H, 2H, and 3H and one on chromosome 5H. Of the eight associations identified in the panels, five were novel. The discovery of resistance in elite breeding lines will hasten the time needed to develop and release a BLS-resistant cultivar.

Preventing the Progression of Myopia in Children-A Review of the Past Decade.

The growing incidence of myopia worldwide justifies the search for efficient methods of myopia prevention. Numerous pharmacological, optical, and lifestyle measures have already been utilized, but there remains a need to explore more practical and predictable methods for myopia control. This paper presents a review of the most recent studies on the prevention of myopia progression using defocus-incorporated multiple-segment spectacle lenses (DIMSsl), repeated low-level red-light (RLRL) therapy, and a combination of low-dose atropine (0.01%) with orthokeratology lenses.

Identification of sex pheromone in Macdunnoughia crassisigna Warren (Lepidoptera: Noctuidae) and field optimization of the sex attractant.

Sex pheromones have proven to be a viable tool for monitoring and controlling pests and is an important part of integrated pest management (IPM). The noctuid moth Macdunnoughia crassisigna Warren poses a significant threat as a defoliator pest, impacting soybean and cruciferous vegetable production and quality in East Asia. However, a lack of comprehensive knowledge about its sexual chemical signaling hampers the development of semiochemical-based IPM approaches for M. crassisigna. We first determined the mating rhythms of M. crassisigna. We then collected pheromones from the sex glands of virgin females at the mating peak and analyzed their components using gas chromatography-electroantennogram detection analysis. The results showed that three components elicited significant electrophysiological responses in male antennae. Gas chromatography-mass spectrometry analysis characterized these components as (Z)-7-dodecene acetate (Z7-12:OAc), (Z)-9-tetradecene acetate (Z9-14:OAc), and (Z)-11-hexadecen-1-ol (Z11-16:OH). Further field experiments indicated that the mixture of Z7-12:OAc and Z9-14:OAc at a ratio of 3:1 displayed significant attractivity to males, confirming its role as a putative sex pheromone of M. crassisigna. Long-term monitoring tests showed that traps baited with these pheromone lures effectively mirrored the population dynamics of M. crassisigna. This study successfully identified and validated the sex pheromone released by female M. crassisigna and formulated potent sex lures for field-based pest monitoring. These findings enriched our understanding of chemical communication in Noctuidae and laid a foundation for developing practical monitoring and control methods against M. crassisigna. © 2023 Society of Chemical Industry.

Fixed-Time Cooperative Tracking Control for Double-Integrator Multiagent Systems: A Time-Based Generator Approach.

In this article, both the fixed-time distributed consensus tracking and the fixed-time distributed average tracking problems for double-integrator-type multiagent systems with bounded input disturbances are studied. First, a new practical robust fixed-time sliding-mode control method based on the time-based generator is proposed. Second, two fixed-time distributed consensus tracking observers for double-integrator-type multiagent systems are designed to estimate the state disagreement between the leader and the followers under undirected and directed communication, respectively. Third, a fixed-time distributed average tracking observer for double-integrator-type multiagent systems is designed to measure the average value of multiple reference signals under undirected communication. Note that all the proposed observers are constructed with time-based generators and can be trivially extended to that for high-order integrator-type multiagent systems. Furthermore, by combining the proposed fixed-time sliding-mode control method with the information provided by the fixed-time observers, the fixed-time controllers are designed to solve the fixed-time distributed consensus tracking and the distributed average tracking problems. Finally, a few numerical simulations are shown to verify the results.

Adaptive Robust Time-Varying Formation Control of Quadrotors under Switching Topologies: Theory and Experiment

This paper investigates a practical time-varying formation control method for quadrotors subjected to disturbances, uncertainties, and switching-directed topologies. A fully distributed formation control scheme is proposed using a linear-velocity independent position controller (LVIPC) and a nonsingular terminal sliding mode attitude controller (NTSMAC). A distributed observer is adopted to eliminate the measurement of linear-velocity states, and only local neighbor states are needed to realize formation flight. A time-varying nonsingular terminal sliding mode manifold is designed to suppress the reaching phase and ensure the finite-time convergence. Adaptive estimators are employed to remove the reliance on the prior knowledge of the upper bound of lumped uncertainties. It is then proven that all the closed-loop signals are bounded under the proposed method. Comparative experimental results based on a practical outdoor hardware solution are presented to confirm the effectiveness of the suggested control algorithm.

Practical Methods for Optimal Control Using Nonlinear Programming, Third Edition [Bookshelf

Practical Methods for Optimal Control Using Nonlinear Programming, Third Edition [Bookshelf