Numerical Study of Co-flow Jet Control on Corner Separation in Compressor Cascade

The design objectives of modern aircraft engines include high load capacity,efficiency,and stability.With increasing loads,the phenomenon of corner separation in compressors intensifies,affecting engine performance and stability.Therefore,the adoption of appropriate flow control technology holds significant academic and engineering significance.This study employs the Reynolds-averaged Navier-Stokes(RANS)method to investigate the effects and mechanisms of active/passive Co-flow Jet(CFJ)control,implemented by introducing full-height and partial height jet slots between the suction surface and end wall of a compressor cascade.The results indicate that passive CFJ control significantly reduces the impact of corner separation at small incidence,with partial-height control further enhancing the effectiveness.The introduction of active CFJ enables separation control at large incidence,improving blade performance under different operating conditions.Active control achieves this by reducing the scale of corner separation vortices,effectively reducing the size of the separation region and enhancing blade performance.

Model Predictive Control for Cascaded H-Bridge PV Inverter with Capacitor Voltage Balance

We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc-ing control methods,the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control.Besides,the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking.A cost function was con-structed to achieve the high-precision grid-connected control of the CHB inverter.Finally,the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules.

基于Open CASCADE的拱桥建模研究

几何引擎是三维BIM建模软件中的核心组件,对软件的性能、准确性、互操作性和用户体验等方面有着重要影响。商业软件的几何引擎虽然经过了多年的发展和优化具有较好的性能和稳定性,但常受限于软件厂商提供的API接口和商业软件所需要的系统环境,无法对底层数据进行访问或修改,灵活性较差,且不具备完全自主商业版权。基于开源几何引擎的应用在很多领域已有相关的研究成果,但在桥梁工程领域较少,基于开源几何引擎Open CASCADE对桥梁工程领域的模型构建技术进行探索,实现自主可控的桥梁工程三维建模平台,以拱桥为研究对象,结合几何引擎的模型构建技术,实现拱桥模型的创建。探索开源几何引擎在桥梁工程领域的建模实现能力,为实现更多桥型的三维建模以及基于模型更进一步的衍生应用积累经验,并为打造自主可控的桥梁工程建模软件提供参考。

Simulation of Greenhouse Heating System Using Fuzzy Smith Cascade Compound Control

Aiming at characteristic of time delay, time-varying parameters and much disturb in glass greenhouse heating system, fuzzy smith cascade compound control policy based on typical PID cascade compound control policy is proposed. Simulation results show that it is effective to overcome the influence of time delay on stability of control system and the system possesses strong robust and good dynamic performance..

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Synchronous tracking control of 6-DOF hydraulic parallel manipulator using cascade control method

The synchronous tracking control problem of a hydraulic parallel manipulator with six degrees of freedom (DOF) is complicated since the inclusion of hydraulic elements increases the order of the system.To solve this problem,cascade control method with an inner/outer-loop control structure is used,which masks the hydraulic dynamics with the inner-loop so that the designed controller takes into account of both the mechanical dynamics and the hydraulic dynamics of the manipulator.Furthermore,a cross-coupling control approach is introduced to the synchronous tracking control of the manipulator.The position synchronization error is developed by considering motion synchronization between each actuator joint and its adjacent ones based on the synchronous goal.Then,with the feedback of both position error and synchronization error,the tracking is proven to guarantee that both the position errors and synchronization errors asymptotically converge to zero.Moreover,the effectiveness of the proposed approach is verified by the experimental results performed with a 6-DOF hydraulic parallel manipulator.

Cascade control based on minimum sensitivity in outer loop for processes with time delay

A new cascade control program was proposed based on modified internal model control to handle stable,unstable and integrating processes with time delay.The program had totally four controllers of which the secondary loop had two controllers and the primary loop had two controllers.The two secondary loop controllers were designed using IMC technique.They were decoupled completely and could be adjusted independently,which avoided the undesirable influence on performance of the primary controllers.The main controller in the primary loop was devised as a PID using the method of minimum sensitivity,which could guarantee not only the nominal performance but also the robust stability of the system.A setpoint filter was added in the primary loop to improve the tracking performance.All the controllers of the two closed-loops were designed analytically,and could be adjusted and optimized by single parameter respectively.Simulations were carried out on three various processes with time delay,and the results show that the proposed method can provide a better performance of both set-point tracking and disturbance rejection and robustness against parameters perturbation.

Adaptive Cascade Generalized Predictive Control

Cascade control is one of the most popular structures for process control as it is a special architecture for dealing with disturbances. However, the drawbacks of cascade control are obvious that primary controller and secondary controller should be tuned together, which influences each other. In this paper, a new Adaptive Cascade Generalized Predictive Controller (ACGPC) is introduced. ACGPC is a method issued from GPC and the inner and outer controllers of a cascade system are replaced by one cascade generalized predictive controller, where both loops model are updated by Recursive Least Squares method. Compared with existing methods, the new method is simpler and yet more effective. It can be directly integrated into commercially available industrial auto-tuning systems. Some examples are given to illustrate the effectiveness and robustness of the proposed method.

融合注意力机制的Cascade R-CNN田间害虫检测方法

为解决测报灯采集图像中害虫依赖人工识别及统计结果可靠性低和准确性差的问题,本研究提出一种改进型Cascade R-CNN田间害虫检测算法。该算法以Cascade R-CNN为基础框架,采用ResNeSt-50作为主干网络,融合了跨通道注意力机制;使用统一目标检测头(unifying object detection heads with attentions,DyHead),并融合尺度感知、空间位置感知和任务感知。此外,采用简单复制-粘贴(simple copy-paste,SCP)方法进行了数据增强。研究共采集到20类害虫总计1 500张图像,制作了符合MS COCO格式(microsoft common objects in context 2017,MS COCO 2017)的测报灯田间害虫数据集。结果显示,本研究提出的方法的F1分数(F1-score)达到了86.2%。当交并比(intersection over union,IoU)为0.5时,其F1-分数与经典Cascade R-CNN、Faster R-CNN和YOLOv4相比,分别提升了2.8、5.8和8.2个百分点。表明该方法满足测报灯害虫检测任务对判别能力和实时性的要求,实现了害虫的高精度自动识别与计数,可直接应用于田间害虫检测。

DISOPE distributed model predictive control of cascade systems with network communication

A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.

Nonlinear cascade control of single-rod pneumatic actuator based on an extended disturbance observer

Precise position tracking control of the single-rod pneumatic actuator is considered and a nonlinear cascade controller is developed.The proposed controller comprises an extended disturbance observer(EDOB)and a nonlinear robust control law synthesized by the backstepping method.The EDOB is designed to estimate not only the influence of disturbances but also the parameter uncertainties.With the use of parameter and disturbance estimates,the nonlinear cascade controller,which consists of an outer position tracking loop and an inner load pressure loop,is further designed to attenuate the effects of parameter and disturbance estimation errors.The stability of the closed-loop system is proven by means of Lyapunov theory.Extensive comparative experimental results obtained verify the effectiveness of the proposed nonlinear cascade controller and its performance robustness to parameter and external disturbance variations in practical implementation.

Cascade adaptive control of uncertain unified chaotic systems

The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point. Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required. By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.

A hybrid stochastic fractal search and pattern search technique based cascade PI-PD controller for automatic generation control of multi-source power systems in presence of plug in electric vehicles

A hybrid Stochastic Fractal Search plus Pattern Search （hSFS-PS） based cascade PI-PD controller is suggested in this paper for Automatic Generation Control （AGC） of thermal, hydro and gas power unit based power systems in presence of Plug in Electric Vehicles （PEV）. Firstly, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral （I） controller is optimized by Stochastic FractaI Search （SFS） algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, differential evolution and teaching learning based optimization techniques is demonstrated by comparing simulation results for the identical power system. To improve the system performance further, Pattern Search （PS） is subsequently employed. The study is further extended for different controllers like PI, PID, and cascaded PI-PD controller and the superiority of cascade PI-PD controller over conventional controllers is demonstrated. Then, cascade PI- PD controller parameters of AGC searched using the proposed hSFS-PS algorithm in presence of plug in electric vehicles. The study is also extended to an interconnected power system. It is seen from the comparative analysis that hSFS-PS tuned PI-PD controller in single and multi-area with multi sources improves the system frequency stability in complicated situations. Lastly, a three area interconnected system with PEVs with dissimilar cascade PI-PD controller in each area is considered and proposed hSFS- PS algorithm is used to tune the controller parameters in presence of nonlinearities like rate constraint of units, dead zone of governor and communication delay.

Fault diagnosis using robust cascade observers with application to spacecraft attitude control

This paper proposes a new gyro and star sensor fault diagnosis architecture that designs two groups of cascade H∞ optimal fault observers using LMI for spacecraft attitude control systems.The basic idea of the approach is to identify the gyro fault to good effect first and then makes a further diagnosis for the star sensor based on the former.The H∞ optimal fault observer in design has the robustness with respect to model uncertainties and diagnosis uncertainties.Its robustness to unknown inputs is as a special study in frequency domain.Finally,simulation results demonstrate the effectiveness and feasibility of the proposed control algorithm.

Monte-Carlo based cascade control approach with focus on real overactuated space systems

The present research relies on a cascade control approach through the Monte-Carlo based method in the presence of uncertainties to evaluate the performance of the real overactuated space systems.A number of potential investigations in this area are first considered to prepare an idea with respect to state-of-the-art.The insight proposed here is organized to present attitude cascade control approach including the low thrust in connection with the high thrust to be implemented,while the aforementioned Monte-Carlo based method is carried out to guarantee the approach performance.It is noted that the investigated outcomes are efficient to handle a class of space systems presented via the center of mass and the moments of inertial.And also a number of profiles for the thrust vector and the misalignments as the disturbances all vary in its span of nominal variations.The acquired results are finally analyzed in line with some well-known benchmarks to verify the approach efficiency.The key core of finding in the research is to propose a novel 3-axis control approach to deal with all the mentioned uncertainties of space systems under control,in a synchronous manner,as long as the appropriate models in the low-high thrusts are realized.

Decentralized closed-loop identification and controller design for a kind of cascade processes

A new decentralized closcd-loop identification and predictive controller design method for a kind of cascade processes composed of several sub-processes is studied. This kind of cascade processcs has the characteristies of one-way connection. The process is divided into several two-input-two-output （TITO） sub-systems. The parameters of the first-order plus dead-time models for the transfer function matrices can be obtained using least squares method. Hence a distributed model predictive contn,ller is designed based on the coupling models of each sub-process. Simulation results on the temperature control of a reheating furnace are given to show the efficiency of the algorithm.

THD Analysis of Cascaded H-Bridge Inverter with Fuzzy Logic Controller

In recent days, the multilevel inverter technology is widely applied to domestic and industrial applications for medium voltage conversion. But, the power quality issues of the multilevel inverter limit the usage of much sensitive equipment like medical instruments. The lower distortion level of the output voltage and current can generate a quality sinusoidal output voltage in inverters and they can be used for many applications. The harmonics can cause major problems in equipments due to the nonlinear loads connected with the power system. So, it is necessary to minimize the losses to raise its overall efficiency. In this paper, a new topology of seven level asymmetrical cascaded H-bridge multilevel inverter with a Fuzzy logic controller had been implemented to reduce the Total Harmonic Distortion (THD) and to improve the overall performance of the inverter. The proposed model is well suited for use with a solar PV application. In this topology, only six IGBT switches are used with three different voltage ratings of PV modules (1:2:4). The lower number of semiconductor switches leads to minimizing overall di/dt ratings and voltage stress on each switches and switching losses. The gate pulses generated by Sinusoidal Pulse Width Modulation (SPWM) technique with a Fuzzy logic controller are also introduced. A buck-boost converter is used to maintain the constant PV voltage level integrated by an MPPT technique followed by Perturb and Observer algorithm is also implemented. The MPPT is used to harness the maximum power of solar radiations under its various climatic conditions. The new topology is evaluated by a Matlab/Simulink model and compared with a hardware model. The results proved that the THD achieved by this topology is 1.66% and realized that it meets the IEEE harmonic standards.

Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

This paper presents a combined control and modulation technique to enhance the power quality(PQ)and power reliability(PR)of a hybrid energy system(HES)through a single-phase 11-level cascaded H-bridge inverter(11-CHBI).The controller and inverter specifically regulate the HES and meet the load demand.To track optimum power,a Modified Perturb and Observe(MP&O)technique is used for HES.Ultra-capacitor(UCAP)based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell conditions.For an improved PQ and PR,a two-way current control strategy such as the main controller(MC)and auxiliary controller(AC)is suggested for the 11-CHBI operation.MC is used to regulate the active current component through the fuzzy controller(FC),and AC is used to regulate the dc-link voltage of CHBI through a neural network-based PI controller(ANN-PI).By tracking the reference signals fromMC and AC,a novel hybrid pulse widthmodulation(HPWM)technique is proposed for the 11-CHBI operation.To justify and analyze the MATLAB/Simulink software-based designed model,the robust controller performance is tested through numerous steady-state and dynamic state case studies.

Research on Double Cascade Control Algorithm for Self-Balancing Two-Wheeled Vehicle

To solve the problem of self-balancing two-wheeled vehicle, this article presents double cascade PID control algorithm. This method reduces the coupling of balance control, speed control and direction control, because of the special system structure. This article successfully solved the sensor fusion of gyroscope and accelerometer by using Kalman filtering algorithm, and adding in fuzzy PID algorithm to improve the flexibility of the steering system, thus greatly improving the accuracy and response rate of the system.