Poor Control Effect Research Articles

Fuzzy control system design for landscape lamp of environment art based on multi-function

With the material needs that people constantly meet, the people begin to pursue the spiritual abundance, and the environmental art landscape lamp is thus born. At present, most of the landscape lamp controllers are realized through the full hardware circuit, and there are some defects such as troublesome installation, high maintenance cost and poor control effect. In view of this situation, this study uses the fuzzy control algorithm to establish the fuzzy control system of environmental art landscape lamps, aiming to optimize the accuracy and effect of light control. Firstly, the composition structure and lighting scene mode of the environmental art landscape lamp are researched, and then the intelligent light control system is designed by the adaptive fuzzy control algorithm. The results showed that the control accuracy of adaptive fuzzy control algorithm was above 95, and the running time of the system was within 1 minute. In addition, both experts and users scored above 9.5 in terms of satisfaction with the control system. To sum up, the light fuzzy control system designed in this study has good control performance and certain practical application value.

A Robust Filtered-x Least Mean Square Algorithm with Adjustable Parameters for Active Impulsive Noise Control

In active noise control (ANC) systems, the traditional filtered-x least mean square (FxLMS) algorithm has poor control effect on impulsive noise. To overcome this drawback, a robust cost function was designed in this paper by embedding the cost function of the FxLMS algorithm into the framework of hyperbolic tangent function; this paper thus proposes a robust filtered-x least hyperbolic tangent (FxLHT) algorithm in ANC systems. Moreover, the value of λ in the FxLHT algorithm greatly affects the robustness and convergence performance of the algorithm. Therefore, a variable λ-parameter was proposed to enhance the performance of the FxLHT algorithm. Simulation results show that in the active control of impulsive noise, compared with the FxLMS algorithm and other robust ANC algorithms, the proposed FxLHT algorithm and variable λ-parameter FxLHT algorithm not only exhibit good robustness and noise reduction performance but also have a better tracking ability.

Speed regulation system based on proportional resonance self-coupling PI control

In this paper, an improved self-coupled PI control dual-loop control strategy is proposed for the vector control of permanent magnet synchronous electric speed control system, to improve the poor motor control effect caused by the dead zone of the inverter, the presence of harmonics in the motor magnetic field distribution, and the error in the sampling process of the current. In order to reduce the tracking error of the signal, an acceleration feed-forward method is adopted, and the self-coupled PI controller with an additional Levant differentiator is introduced into the speed loop of the permanent magnet synchronous motor to ensure the accurate derivation of the input signal containing noise to improve the robustness of the system. In addition, this strategy combines the proportional term of the autotuned PI control structure with the standard resonator to form a proportional resonant autotuned PI in the current loop, so that the permanent magnet synchronous motor can better compensate the current in the current loop control to achieve the effect of current harmonic suppression. Finally, the control mechanism of the servo system analyzed, and based on the mathematical model of the controlled object PMSM, the design method of the improved self-coupling PI control structure is given. The experimental results show that the proposed control strategy can reduce the impact of the motor's own parameter changes on the system performance and has a good current harmonic suppression in the low-speed domain, which verifies the effectiveness of the designed improved self-coupled PI controller.

Coordinated control strategy of photovoltaic energy storage power station based on adaptive dynamic programming

In order to solve the problem of variable steady-state operation nodes and poor coordination control effect in photovoltaic energy storage plants, the coordination control strategy of photovoltaic energy storage plants based on ADP is studied. Establish the photovoltaic energy storage power station model including photovoltaic system model, super capacitor system model and battery system model; Set the maximum limit of active power change as the power constraint condition for coordinated control of photovoltaic energy storage station; The optimal control problem of multi voltage and reactive power resource coordination is fully considered, the optimal voltage control model is established by using ADP algorithm, and the optimal coordinated control strategy is obtained by online learning the collected dynamic operation information. The experimental results show that this strategy can improve the coordinated control effect of the photovoltaic energy storage station, ensure the photovoltaic energy storage station in a stable operation state, improve the service life of the energy storage device in the photovoltaic energy storage station, and stabilize the steady-state operating node voltage within the ideal fluctuation range.

Research on temperature control of proton exchange membrane electrolysis cell based on MO‐TD3

AbstractTo solve the problem of temperature control in proton exchange membrane electrolytic cell (PEMEC), this paper presents a temperature control method based on multi‐experience pool probability playback and Ornstein‐Uhlenbeck noise‐twin delay depth deterministic strategy gradient. Firstly, considering the influence of water supply, anode and cathode pressure, and natural heat dissipation on temperature, a refined thermal model of PEMEC is established and transformed into a Markov model under the framework of deep reinforcement learning (DRL). Then, to solve the training instability and poor control effect of DRL caused by inertia delay of the PEMEC temperature control system, multi‐empirical pool probability playback and Ornstein‐Uhlenbeck random process noise techniques are introduced on the basis of the traditional DRL method. Finally, the simulation and hardware‐in‐the‐loop experience results show that the proposed method outperforms other advanced methods.

Study on electromagnetic stirring–braking structure layout design and its synergistic mechanism in electromagnetic metallurgy

During the continuous casting process, electromagnetic stirring (EMS) can control the flow pattern of the molten steel on the meniscus in the slab mould, while it is difficult to effectively control the entire molten steel. To this end, a novel composite magnetic field structure of EMS and electromagnetic braking (EMBr) is proposed, and the EMS–EMBr synergistic mechanism is analysed. The flow field of molten steel without a magnetic field is analysed. The magnetic field regulation strategy required to control the molten steel is clarified. The coil core structure layout of existing EMS is analysed. The action mechanism of EMS is studied through simulation, revealing the poor control effect of EMS on the molten steel under high casting speeds. Thus, a novel EMS–EMBr structure layout is proposed to enable the braking magnetic field to cover the key areas within the slab mould, ensuring that the main flow is effectively suppressed. On this basis, the effects of EMS–EMBr synergy and different process parameters on the flow pattern of molten steel are studied. The results indicate that the EMS–EMBr composite magnetic field structure proposed can more effectively control the molten steel, providing technical support for the development of electromagnetic metallurgical equipment.

Resistance patterns and molecular basis to ACCase-inhibiting herbicides

Abstract Digitaria ciliaris var. chrysoblephara (Fig. & De Not.) R.R. Stewart is an annual xeromorphic weed that severely infests direct-seeded rice fields in China. Herbicide resistance is emerging in D. ciliaris var. chrysoblephara owing to extensive and recurrent use of the acetyl-CoA carboxylase (ACCase)-inhibiting herbicide metamifop. In this study, a total of 53 D. ciliaris var. chrysoblephara populations randomly sampled from direct-seeded rice fields across Jiangsu Province were investigated for metamifop resistance and potential resistance-endowing mutations. Single-dose assays revealed that 17 (32.1%) populations evolved resistance to metamifop and 5 (9.4%) populations were in the process of developing resistance. The resistance index (RI) of metamifop-resistant populations ranged from 2.7 to 32.1. Amino acid substitutions (Ile-1781-Leu, Trp-2027-Cys/Ser, and Ile-2041-Asn) in ACCase genes were detected in resistant D. ciliaris var. chrysoblephara plants and caused various cross-resistance patterns to ACCase-inhibiting herbicides. All of four resistant populations (YC07, YZ09, SQ03, and HA06), with different ACCase mutations, exhibited cross-resistance to the aryloxyphenoxypropionate (APP) herbicides cyhalofop-butyl (RI values: 10.0 to 19.9), fenoxaprop-P-ethyl (RI values: 53.7 to 132.8), and haloxyfop-P-methyl (RI values: 6.2 to 62.6), and the phenylpyrazoline (DEN) pinoxaden (RI values: 2.3 to 5.4), but responded differently to the cyclohexanedione (CHD) herbicides clethodim and sethoxydim. It is noteworthy that four postemergence herbicides used for rice cropping, including bispyribac-sodium, pyraclonil, quinclorac, and anilofos, showed poor control effect against D. ciliaris var. chrysoblephara, suggesting few alternations for managing this weed in rice fields except ACCase inhibitors. In conclusion, this work demonstrated that the D. ciliaris var. chrysoblephara had developed resistance to ACCase-inhibiting herbicides in rice cultivation of China, and target-site amino acid substitutions in ACCase were primarily responsible for metamifop resistance.

Application of histogram of oriented gradient features and support vector machine models in stage lighting control in drama

SummaryThe lighting control of the theatrical stage is directly related to the presentation effect of the program and the audience's experience. With the development of intelligent control technology, the control of lighting effects has been continuously improved. However, the existing stage lighting control lacks intelligence, resulting in poor control effect and weak energy‐saving performance. Based on this, a human contour image classification model using support vector machines (SVM) based on histogram of oriented gradient (HOG) feature extraction method is constructed to achieve stage lighting control. The results show that the revised HOG feature extraction approach achieves recognition performance of 99.6% when the ratio is 0.8. The HOG‐SVM model proposed in the study has the best recognition performance, reaching 99.6%. This indicates that the stage lighting control system based on HOG‐SVM feature extraction constructed in the research can meet the actual needs of stage program performance, which can be applied to stage lighting control to effectively reduce energy consumption.

Primary frequency control optimization of coal-fired power plants with high-low position shafts: Employing a revised strategy with power-decoupling and feedforward-compensating

Coal-fired units play a critical role in peak-shaving and frequency regulation with high penetration of renewable energy. The coal-fired unit arranged by high-low position shafts applied in power stations will participate in these regulation processes. In this study, the dynamic model of the 1100 MW supercritical coal-fired unit is built and verified, dynamic characteristics of the primary frequency regulation process are analyzed and a poor control effect of the original control strategy is illustrated. Then, the dynamic coupling relationship between high and low-level units is obtained, and there is a 14-s time delay between the two power outputs, and a revised regulation strategy that employs load distribution factor and flow-rate feedforward-compensating is proposed. Compared with the original control strategy, the revised control strategy can effectively lower fluctuations of the steam parameters by approximately 50%, and the corrective regulation time decreases from 25.1 s and 15.8 s to 6.9 s and 12.1 s under positive and negative load disturbance, respectively. Moreover, it can improve the control effect of low-level unit, whose regulation time under positive and negative load disturbance decreases from 45.7 s and 27.7 s to 9.4 and 20.6 s, respectively. This research can provide technical guidance for the operation of coal-fired units.

Research on casing damage mechanism and prevention and control under creep behavior of salt-gypsum layer

As a good cap rock, the salt-gypsum layer often contains abundant oil and gas resources, but it has strong plastic flow and creep properties, resulting in frequent casing damage problems. Therefore, a new method is proposed to prevent and control casing failure in creep formation by using solid expandable tubular (SET). Based on the Heard model, the creep behavior of formation was described. The expansion experiment of the SET, the material tensile experiment of casing and SET with different expansion rates were carried out. The three-dimensional mechanical model and finite element model of casing-cement sheath- (SET) -formation were established. Numerical simulation of creep behavior of salt-gypsum layer under non-uniform in-situ stress was carried out. Comparative study of casing damage mechanism in two cases with or without SET prevention and control. The influence of sensitive factors such as SET wall thickness and expansion rate on the failure behavior of casing prevented and controlled by SET were analyzed. The results show that (1) In the direction of the maximum horizontal in-situ stress, the stress on the outer surface of the casing is large. In the direction of the minimum horizontal in-situ stress, the stress on the inner surface of the casing is the largest, and the material yield failure occurs first at this position of the casing. The compression deformation of casing is greater than the tensile deformation. The casing is oval after deformation. (2) By increasing steel grade and wall thickness of casing, the service time of the casing under creep behavior of salt-gypsum layer can be prolonged. However, while increasing cost and reducing diameter, it has not played a role in preventing casing failure. (3) By using the method of SET prevention and control, the casing stress is more evenly distributed, the maximum stress is effectively reduced, the stress growth rate is slowed down, and the external collapse resistance ability is significantly enhanced. The maximum stress of the casing is reduced by up to 24.96 %. The larger the wall thickness of the SET, the better the prevention and control effect, and the longer the service time of the casing. The increase of the ultimate wall thickness of the SET with high expansion rate can effectively make up for its poor prevention and control effect. (4) The new method of adding the SET between salt-gypsum layer and cement sheath has the advantages of increasing casing inner diameter, optimizing wellbore structure, reducing cost and wellbore risk. The research results can provide some reference value for the prevention and control of casing failure in creep salt-gypsum layer.

Slip ratio adaptive control for distributed drive electric vehicle based on wheel speed

Aiming at the problems of poor control effect and poor robustness for distributed drive electric vehicles driving on complex and changeable roads, this paper proposes a slip ratio adaptive control method based on wheel speed. Firstly, an optimal slip ratio estimator considering axle load transfer was developed by analyzing the single-wheel dynamics of the vehicle and based on the Burckhardt tire model. Secondly, a cubic polynomial function is used to fit and optimize the optimal slip ratio-peak adhesion coefficient curve, which effectively improves the accuracy of obtaining the optimal slip ratio. Then, a conditional integral sliding mode controller based on wheel speed is designed in order to enhance the transient characteristics of the sliding mode control, to avoid integral saturation, and to improve the control effect of the sliding ratio controller in the low speed start-up phase. Finally, three typical working conditions, namely single road, flat road, and slip road, were established for simulation and experimental validation. The results show that the method in this paper is able to estimate the optimal slip ratio of the road in real time, realize the wheel slip ratio adaptive control, and improve the dynamic performance and lateral stability of distributed drive electric vehicle.

Nonlinear Adaptive Back-Stepping Optimization Control of the Hydraulic Active Suspension Actuator

The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of the nonlinear ABC are difficult to configure, resulting in a poor control effect. An enhanced particle swarm optimization (PSO) approach integrating crazy particles (CP) and time-varying acceleration coefficients (TVAC) is suggested to optimize the controller settings. Furthermore, in order to obtain satisfactory dynamic characteristics of the transition process, the absolute value of the error time integral performance index is used as the minimum performance index function of parameter selection, and the square term of the control input is added to the performance index function to prevent excessive controller energy. Finally, it can be observed from the simulation results of the highest value emax of the displacement tracking error, the average value eμ of error, and the standard deviation eσ of error that the performance of the ABC parameters optimized by PSO+CP+ATVC is superior to the manually given ABC parameters. Therefore, this control method significantly improves the stability and speed of the control system. It provides a new research idea for the parameter optimization of controllers.

Plugging Characteristics and Evaluation Predicting Models by Controllable Self-Aggregation Nanoparticles in Pore Throat Microcapillaries.

Injecting nanoparticle profile agents into low-permeability heterogeneous reservoirs to plugging water breakthrough channels is a widely used technical method to enhance oil recovery. However, insufficient research on the plugging characteristics and prediction models of nanoparticle profile agents in the pore throat has led to a poor profile control effect, short profile control action time, and poor injection performance in the actual reservoir. This study uses controllable self-aggregation nanoparticles with a diameter of 500 nm and different concentrations as profile control agents. Microcapillaries of different diameter sizes were used to simulate the pore throat structure and flow space of oil reservoirs. Based on a large number of cross-physical simulation experimental data, the plugging characteristics of controllable self-aggregation nanoparticles in the pore throat were analyzed. Gray correlation analysis (GRA) and gene expression programming algorithm (GEP) analysis were used to determine the key factors affecting the resistance coefficient and plugging rate of profile control agents. With the help of GeneXproTools, the evolutionary algebra 3000 was selected to obtain the calculation formula and prediction model of the resistance coefficient and plugging rate of the injected nanoparticles in the pore throat. The experimental results show that the controllable self-aggregation nanoparticles will achieve effective plugging when the pressure gradient is greater than 100 MPa/m in the pore throat, and when the injection pressure gradient is 20-100 MPa/m, the nanoparticle solution will be in the aggregation to breakthrough state in the pore throat. The main factors affecting the injectability of nanoparticles, from strong to weak, are as follows: injection speed > pore length > concentration > pore diameter. The main factors affecting the plugging rate of nanoparticles, from strong to weak, are as follows: pore length > injection speed > concentration > pore diameter. The prediction model can effectively predict the injection performance and plugging performance of controllable self-aggregating nanoparticles in the pore throat. The prediction accuracy of the injection resistance coefficient is 0.91, and the accuracy of the plugging rate is 0.93 in the prediction model.

Study on failure behaviors and control technology of surrounding rock in a weakly cemented soft rock roadway: A case study

During coal mining, the deformation and failure of a weakly cemented soft rock roadway roof could cause difficulties for roadway support. In this paper, a combination of on-site measurement and theoretical analysis is used to solve this issue. Firstly this paper investigates the in situ deformation and failure behaviors of a soft rock roadway in a mine in Western China. Then, the failure mechanism and corresponding support principles are discussed and given. Third, various support schemes (bolt and cable reinforcement optimization, grouting, and single prop + top beam combined reinforcement) are proposed and tested. Results show the support capacity can meet the requirements after optimizing the bolt and cable reinforcement support. Due to the development of roof cracks and low grouting pressure, the grouting slurry did not completely fill the roof cracks, resulting in a poor roof control effect. The passive support of a “single prop + top beam” can effectively control the roof subsidence and achieve good application results.

Design and validation of a novel adaptive motion control for a pendulum spherical robot

AbstractSpherical robots (SRs) have the characteristics of nonholonomic constraints, underactuation, nonchain, and strong coupling, which increase the difficulty of modeling and motion control compared with traditional robots. In this study, we develop an adaptive motion control scheme for a nonholonomic SR, in which an omnidirectional dynamic model is carried out by using the Euler–Lagrange method to describe the omnidirectional motion of the SR more accurately. Furthermore, to facilitate the design of the motion controller, the dynamic model is simplified to obtain the state space expression of the SR. Aiming at the problem of poor control effect caused by the change of system model parameters which are influenced by dynamic model reduction, an adaptive motion control law of SR is designed based on MRAC. And the coefficient adjustment of the controller is obtained by the Lyapunov method, with the guaranteed stability of the closed-loop system. Finally, the controller designed in this thesis is compared with four controllers including linear quadratic regulator, Fuzzy PID, PSO-ADRC, and hierarchical SMC. The experimental comparison proves that the control scheme proposed in this study still has good control ability when the motion parameters are disturbed.

Residual stress control of hot-rolled strips during run-out table cooling

The strips with good flatness after finish rolling will have flatness defects such as edge wave after run-out table cooling. These defects are caused by the residual stress due to inhomogeneous thermal and microstructural behaviors during the cooling stage. The traditional residual stress control methods rely too much on experience, resulting in poor control effect and poor universality. Therefore, this study proposed two residual stress control methods based on model calculation: water flow central crown and center wave compensation control. The former is mainly based on controlling the uniformity of strip transverse temperature and microstructure. The latter is mainly controlled by mutual compensation of internal stresses. In this paper, the mathematical models of water flow central crown cooling and critical center wave compensation stress were established, respectively. Meanwhile, a post-buckling model of hot-rolled strip was established to calculate the aim flatness value at exit of finishing mill under critical compensation stress. Furthermore, a fully coupled finite element model based on temperature, phase transitions, and stress was developed and it was verified using experimental data. Finally, the above two residual stress control methods were realized in the finite element model. The results showed that the two methods can reduce the residual stress and improve the flatness, and the application of center wave compensation control is more effective.

Screening of Effective Insecticides Against Diaghania Pyloalis in Mulberry Fields

In recent years, with the rapid development of the sericulture industry, the pests of mulberry trees are also increasing. Diaghania pyloalis Walker is one of the main pests of mulberry trees, has strong fecundity and very large food intake, especially in Sichuan and Chongqing areas. In order to find out the insecticides which can effectively control D. pyloalis, the screening test of high-efficiency control efficacy was carried out. In the summer of 2020, the 3rd instar larvae of D. pyloalis were selected as the test objects, and the indoor bioassay of 10 insecticides on D. pyloalis was carried out, and the results of the indoor bioassay were tested by field experiments in the autumn. The results show that 2000 times liquid of Dursban, Spinetoram, Chlorantraniliprole, and 1000 times liquid of Dichlorvos and Phoxim had the best control effect on D. pyloalis. Secondly, 2000 times liquid of Imidacloprid and Chlorfenapyr had the better control effect on D. pyloalis. Finally 2000 times liquid of Pymetrozine and Cyromazine had poor control effect, and 1000 times liquid of Azadirachtin had the worst control effect on D. pyloalis. To control D. pyloalis, 2000 dilution of Dursban and Spinetoram, and 1000 times liquid of Dichlorvos can be used in sericultural production. When using Chlorantraniliprole to control D. pyloalis, the leaves of mulberry should be picked with long interval to avoid affecting the quality of cocoons, and it is not recommended to use Cyromazine, Azadirachtin to control D. pyloalis.

Energy-efficiency-oriented optimal control for electrical environmental control system based on advanced neural network

Electric environmental control system (EECS) adopts the unique architecture of electric compressor bleed air and multi-stage expansion refrigeration. The state of EECS is regulated by the electric compressor and multiple regulation valves together, resulting in flow and temperature of each node strongly coupled. Traditional methods use a single valve to control each objective without considering the effect of control scheme on energy efficiency, which will not only lead to poor control effect, but also limit the coefficient of performance (COP) of EECS. This paper proposes an energy-efficiency-oriented optimal control strategy to improve the COP and control performance simultaneously. Part of the regulation valves are regarded as optimization variables and the corresponding control objectives are regarded as constraints to maximize COP. On this basis, an advanced control algorithm is proposed to further improve the control effect. The COP prediction model is developed with an offline trained neural network and the optimal valve openings are solved by the differential evolution algorithm. The controller is developed with another neural network online trained by adaptive learning rate algorithm to adapt to complex conditions. The results show that the COP and control performance of EECS are significantly improved. Compared to other strategies, the optimal control strategy can increase COP by up to 61.14%. This study provides an effective solution to the optimal control problem of systems with similar structure to EECS.

Construction of Power Supply Stability Control Model for Wind Connected Power Grid

There are many problems in the power supply stability control of wind power generation system, such as large fluctuations, poor control effect and so on. Therefore, a new stability control model of wind power grid connected is designed. Determine the DC grid connection mode when the wind farm is connected, convert the DC power into AC power through the converter station, and transmit it to the final AC system to realize the grid connection of wind power and power grid; According to the determined wind power access mode, calculate the mechanical operation power, mechanical torque and wind energy utilization coefficient collected by the wind turbine, complete the best collection of wind energy, and determine the shafting according to the mass block model of the wind turbine and generator, so as to realize the research on the mathematical model of wind power generation. By analyzing the power flow direction of the stator and rotor of the wind turbine generator set, the unstable state of the power supply voltage of the wind turbine generator set after grid connection is determined. The PV curve method is used to calculate the steady-state voltage stability of grid connected wind turbines, and a power supply stability control model based on the voltage stability of grid connected wind turbines is established. The nonlinear objective function method is used to optimize the critical point of power supply stability, calculate the maximum load and maximum power of the system, establish the static power supply and transient power supply stability model after wind power grid connection, and realize the power supply stability control research of grid connected wind power through the analysis of power supply characteristics. The experimental results show that the model is closer to the stability of the actual power supply in the test of improving the stability of the power supply, ensuring the quality of power supply, while the test results of the other two methods have large fluctuations. In the analysis of the change of power supply after grid connection, the experimental results obtained by the model are very close to the actual data values. Therefore, this method can effectively improve the performance of power system.

Urban Rail Transit Network Planning Based on Particle Swarm Optimization Algorithm

In order to solve the problem that the urban rail transit network is affected by a large number of signals, resulting in poor control effect, and improve the living comfort of residents near urban rail transit, a study on urban rail transit network planning based on particle swarm optimization algorithm is proposed. The learning factor is dynamically adjusted according to the inertia weight parameters, and the particle swarm optimization parameters are selected in combination with the setting of the maximum velocity parameters. The individual optimal particle is selected by using the dominant relationship between the individual particles, and the optimization of the optimal particle is completed by combining the selection requirements of the global optimal particle. We design the v2x communication implementation scheme, obtain the traffic flow information of urban rail transit, build the signal input and output model based on particle swarm optimization algorithm, obtain the output feedback signal, and determine the planning scale of urban rail transit network, so as to build the urban rail transit network planning model and complete the urban rail transit network planning. The experimental results show that the proposed method can improve the utilization rate of urban rail transit network planning, effectively control the change of network signal amplitude, and reduce the repetition rate of urban rail transit network planning.