Design Of Real-time Control System Research Articles

Design and Simulation-Based Optimization of an Intelligent Autonomous Cruise Control System

Significant progress has recently been made in transportation automation to alleviate human faults in traffic flow. Recent breakthroughs in artificial intelligence have provided justification for replacing human drivers with digital control systems. This paper proposes the design of a self-adaptive real-time cruise control system to enable path-following control of autonomous ground vehicles so that a self-driving car can drive along a road while following a lead vehicle. To achieve the cooperative objectives, we use a multi-agent deep reinforcement learning (MADRL) technique, including one agent to control the acceleration and another agent to operate the steering control. Since the steering of an autonomous automobile could be adjusted by a stepper motor, a well-known DQN agent is considered to provide the discrete angle values for the closed-loop lateral control. We performed a simulation-based analysis to evaluate the efficacy of the proposed MADRL path following control for autonomous vehicles (AVs). Moreover, we carried out a thorough comparison with two state-of-the-art controllers to examine the accuracy and effectiveness of our proposed control system.

An analytical and experimental study on adaptive active vibration control of sandwich beam

A novel composite sandwich beam with adaptive active control system is proposed for low-frequency vibration reduction, and the experimental investigation on adaptive closed-loop vibration control is carried out. The macro fiber composite (MFC) piezoelectric patches and filtered-x least mean square (Fx-LMS) algorithm are employed to construct the adaptive closed-loop control system. An improved analytical model considering the effects of MFC piezoelectric patches is proposed to calculate the vibration characteristics of the composite sandwich beam. It provides a theoretical basis for the design of adaptive control scheme. The accuracy of present analytical model is verified by the results of experiment and numerical simulation. The adaptive vibration control is implemented analytically and experimentally, and the results demonstrate that the low-frequency vibration of the composite sandwich beam can be greatly and quickly suppressed by the proposed adaptive closed-loop control system. Moreover, vibrations induced by complex multi-frequency excitation with different amplitudes can be effectively reduced by using the proposed adaptive control system. The novelty of this work lies in the proposed adaptive closed-loop vibration control system and improved analytical method for piezoelectric composite sandwich beam. The study provides a novel design of real-time control system for the low-frequency vibration of composite sandwich structures.

Design of Real-Time Temperature Monitoring and Control System for Multimodal Ablation

Design of Real-Time Temperature Monitoring and Control System for Multimodal Ablation

Control-Oriented Modeling for Nonlinear MIMO Turbofan Engine Based on Equilibrium Manifold Expansion Model

This paper investigates the control-oriented modeling for turbofan engines. The nonlinear equilibrium manifold expansion (EME) model of the multiple input multiple output (MIMO) turbofan engine is established, which can simulate the variation of high-pressure rotor speed, low-pressure rotor speed and pressure ratio of compressor with fuel flow and throat area of the nozzle. Firstly, the definitions and properties of the equilibrium manifold method are presented. Secondly, the steady-state and dynamic two-step identification method of the MIMO EME model is given, and the effects of scheduling variables and input noise on model accuracy are discussed. By selecting specific path, a small amount of dynamic data is used to identify a complete EME model. Thirdly, modeling and simulation at dynamic off-design conditions show that the EME model has model accuracy close to the nonlinear component-level (NCL) model, but the model structure is simpler and the calculation is faster than that. Finally, the linearization results are obtained based on the properties of the EME model, and the stability of the model is proved through the analysis of the eigenvalues, which all have negative real parts. The EME model constructed in this paper can meet the requirements of real-time simulation and control system design.

Preliminary design of real-time plasma control system for CFETR

The China Fusion Engineering Test Reactor (CFETR), aiming at demonstrating fusion energy production in self-sufficient burning in different advanced operation scenarios, has entered the stage of engineering design and R&D (research and development). The real-time plasma control system (PCS), as a critical system controlling the evolution of plasma parameters that are necessary to operate CFETR, is designed synchronously. The CFETR PCS is composed of system architecture, integrated control algorithms, and two assistant tools PCS-SDP (Software Development Platform) and PCS-VP (Verification Platform) for algorithm development and verification. Taking the steady-state operation and machine safety into account, the requirement and conceptual design of the system architecture of CFETR PCS is introduced in this paper. PCS-SDP, a visual algorithm development platform, has completed the preliminary design and a prototype has been built to validate the design and technical feasibility with the control algorithm development for EAST. PCS-VP is under preliminary design taking ITER PCSSP (Plasma Simulation Platform) design as reference. These two tool platforms will strongly support and accelerate the development of CFETR PCS.

Control and Real-Time Data Acquisition of an Experimental Platform for Stored Grain Aeration Study.

Aeration is one of the most important methods to keep stored grain safe and maintain its quality. Experimental platforms are used for stored grain aeration study in a laboratory-scale. The purpose of this paper was to provide the real-time data acquisition and control system design of a new experimental platform with multifunction for stored grain study. Requirements of the aeration experiments were analyzed, and multi running modes were designed. The aeration inlet air conditions were designed to be adjustable and multi variables need to be controlled simultaneously, which was a key problem to be solved for the platform. An ON/OFF-PID based multivariable cooperative control method was proposed, and two control loops were formed where inlet air temperature and humidity were considered separately while could be controlled simultaneously with a logic judgement strategy. Real-time data needed to be monitored was acquired with different sensors and displayed intuitively. Experiments were carried out to test the static and dynamic characteristics of the control method and three inlet air flow rates of 0.03, 0.08 and 0.13 m·s−1were used. Performance of the data acquisition system was also tested. The results showed that, the inlet air conditions control error was within ±1 °C and 10% for temperature and relative humidity, respectively. The real-time data acquisition of multi parameters during aeration process was realized. The experimental platform can be used for studies of different aeration objectives.

The Electronics Design of Real-Time Feedback Control System in KTX

A feedback control system has been designed for Keda Torus eXperiment (KTX) to achieve the following goals: 1) 3-D plasma stability control and 2) improvement of plasma discharge quality. The real-time electronics system which is the key unit of this feedback control system helps to resolve the lack of high-speed transmission and real-time processing capability of the previous data acquisition (DAQ) system. The electronics system is implemented in PXI Express using a modular, distributed architecture. Field-programmable gate array (FPGA) is the core component of the electronics system. This article describes in detail the reasons for the choice in the hardware components. Optical communication has been evaluated for real-time communication by using the Aurora protocol. Measurements have been executed on a prototype system. Results from several tests comparing the performance of different solutions are also provided. 2-D spatial Fourier analysis based on FPGA is first used on the reversed field pinch (RFP) fusion device. Results indicate that the system can control the whole process and calculation in low latency.

Model and design of real-time control system for aerial variable spray.

The dosage sprayed upon per unit area is an important index to measure the effects of pesticide application. Owing to the fact that parameters such as flight height, flight speed, and spray swath can change at any given time, it is impossible to ensure a consistent amount of pesticide application per unit area during the course of aerial variable spray. In order to ensure a consistent amount of pesticide application per unit area, a set of control models of aerial variable spray using an unmanned aerial vehicle (UAV) was proposed, and the corresponding control system was developed based on the technology of aerial variable spray. According to the change of flight parameters, this system was able to adjust the opening degree of solenoid valve through the control model of aerial variable spray. After that, the amount per unit time would change to ensure a consistent amount of pesticide application per unit area, which effectively avoided the phenomenon of uneven pesticide application and improved the accuracy. According to the actual demand for the area in need of pesticide application, the operator can manually control the amount of pesticide applied and change the dosage sprayed upon per unit area to achieve a better effect. Through field tests, it was verified that the system has high accuracy of variable control. The deviation range was between 0.11% and 9.79%, which met the demands of agricultural aviation pesticide application. Furthermore, the system had strong stability for working continuously for more than 6 h at 30°C to meet the environmental requirements of pesticide application via UAV. All the data related to the pesticide application were stored in this system, which provided a reference for the further study of the precision technology in pesticide application. The model proposed in this paper also provided a theoretical basis for the technology development of aerial variable spray.

Data regarding dynamic performance predictions of an aeroengine.

The design of aeroengine real-time control systems needs the implementation of machine learning based techniques. The lack of in-flight aeroengine performance data is a limit for the researchers interested in the development of these prediction algorithms. Dynamic aeroengine models can be used to overcome this lack.This data article presents data regarding the performance of a turbojet that were predicted by the dynamic engine model that was built using the Gas turbine Simulation Program (GSP) software.The data were also used to implement an Artificial Neural Network (ANN) that predicts the in-flight aeroengine performance, such as the Exhaust Gas Temperature (EGT).The Nonlinear AutoRegressive with eXogenous inputs (NARX) neural network was used. The neural network predictions have been also given as dataset of the present article.The data presented here are related to the article entitled “MultiGene Genetic Programming - Artificial Neural Networks approach for dynamic performance prediction of an aeroengine” [1].

Hybrid MultiGene Genetic Programming - Artificial neural networks approach for dynamic performance prediction of an aeroengine

Dynamic aeroengine models have an important role in the design of real-time control systems. Modelling of aeroengines using dynamic performance simulations is a key step in the design process in order to reduce costs and the development period. A dynamic model can provide a numerical counterpart for the development of control systems and for the study of the engine behaviour in both steady and unsteady scenarios. The latter situation is particularly felt in the military field. The Viper 632-43 engine analysed in this work is a military turbojet, so it was necessary to develop a model that would replicate its behaviour as realistically as possible. The model was built using the Gas turbine Simulation Program (GSP) software and validated both in steady and transient conditions.Once the engine model was validated, different machine learning techniques were used to estimate (data mining) and predict an engine parameter; the Exhaust Gas Temperature (EGT) has been chosen as the key parameter. A MultiGene Genetic Programming (MGGP) technique has been used to derive simple mathematical relationships between different input parameters and the EGT. These, then, can be used to calculate the EGT value of a real Viper 632-43 engine knowing a priori the input parameters and in any operating condition.Finally, the EGT estimated by this algorithm has been added to the dataset used for the one-step-ahead EGT prediction by Artificial Neural Network (ANN). A time-series ANN was used for the EGT prediction, i.e. the Nonlinear AutoRegressive with eXogenous inputs (NARX) neural network. This network recognizes the input data as a real time series and is therefore able to predict the output in the next time step. It was chosen to use, as forecasting method, the one-step-ahead technique which allows to predict the EGT in the immediately next time step.

Proposal of a Feedback Control System for a Thermally Driven High-Power-Density Actuator

Shape memory alloy (SMA) actuators can generate force via the phase transition of the SMA, related to its temperature variations. The amount of force and the response duration length are approximately proportional to the SMA’s volume and mass. The higher-power actuator, which consists of a single SMA tube, has mechanical simplicity and high reliability; however, it has a relatively long driving duration, and actuation timing uncertainties caused by the environmental temperature variations. Because of its huge heat capacity, the environment temperature variations affect the actuator’s temperature, the phase transformation uncertainties, and force generation profiles, resulting in differences in the actuation timing that are tens of seconds. This paper proposes a suitable feedback control system consisting of two methods. One is the construction of a physical model for SMA tube thermomechanical coupling response that has suitable complexity for the real-time control system design by the limited application condition. The other is a reference trajectory generation and tracking method by using the model predictive control method with a constructed physical model, resulting in a possible drive timing uncertainty reduction. The effectiveness of the proposed methods was verified by specific test piece system identification and control simulations performed both numerically and experimentally. In addition, the effectiveness of the online control system itself was confirmed by comparing the results of a traditional control system using the proportional integral derivative method. The result indicates the potential of the possible application system for SMA actuators.

A neural-network enhanced modeling method for real-time evaluation of the temperature distribution in a data center

The thermal predicting/evaluating model of data centers is pivotal in designing their thermal control systems. The existing modeling methods are based on the computational fluid dynamics (CFD) simulations, which is accurate in modeling for a steady-state flow pattern but considerably time-consuming. Besides, the corresponding parameters of CFD have to be re-identified with the deviation of the flow field, which makes it extremely inefficient in real-time thermal control system design of data centers. This paper proposed a machine learning method to derive the fast-temperature evaluation model with a constructed artificial neural network. It learns the relationship between the flow patterns and model parameters based on the system thermal–physical analysis, which replaces the time-consuming CFD-based parameter identifying process. Then, the temperature evaluation is implemented under different flow patterns with the proposed neural-network enhanced modeling method. In the learning process, multi-type of neural networks, i.e., backpropagation network, radial basis function network and extreme learning machine, are considered and compared. The accuracy of the proposed model is validated by comparing with the pure CFD results as the satisfactory standard. With the efficiency and accuracy, the proposed modeling method is more suitable to design real-time controllers for data centers with changing flow fields.

Overview of recent advances of process analysis and quality control in resistance spot welding

Resistance spot welding (RSW) is frequently employed in current industrial occasions. However, the process is multi-field coupled and highly nonlinear, and full of uncertainties and disturbances. This paper presents recent primary advances and progress in process analysis and quality control of the RSW operations. Online welding process analysis, and relative online quality estimation for the welding products, are very important because they can help to save energy and improve the efficiency during actual production. It should deeply interpret the process characteristics, and then reasonable relations between selected monitoring process variables, such as dynamic resistance or electrode displacement, and quality criteria, such as nugget size or tensile-shear strength, can be established. Apart from online process analysis using mathematical tools, using different kinds of auxiliary measuring signals from external sensors and intrinsic process variables to monitor the process and obtain the quality information of the weld is presented and discussed. Then various process control works are reviewed. Besides the various parameters optimization methods, kinds of controllers, including feedback controllers, intelligent controllers and comprehensive controllers which combined the online quality estimation and control strategy application together, for obtaining welds with satisfactory quality, are respectively discussed. It can be seen that the establishment of general models to online process analysis, quality estimation and real time control system design for obtaining welds with satisfactory quality still remains a big challenge in reality. This work can provide references and enlightens for current academic researches or actual production in RSW relative area.

소형 웨어러블 카메라의 효율적인 동작을 위한 실시간 해상도 조절 시스템의 설계 및 구현

소형 웨어러블 카메라의 효율적인 동작을 위한 실시간 해상도 조절 시스템의 설계 및 구현

Design of a fast real-time LPV model predictive control system for semi-active suspension control of a full vehicle

This article is concerned with the control of a Semi-Active suspension system of a 7DOF Full Vehicle model, equipped with four Electro Rheological (ER) dampers, taking into account their incipient dissipativity constraints. Herein, a real-time, fast, advanced control structure is presented within the Model Predictive Control framework for Linear Parameter Varying (LPV) systems. The control algorithm is developed to provide a suitable trade-off between comfort and handling performances of the vehicle in a very limited sampling period (Ts=5ms), in view of a possible realtime implementation on a real vehicle. The control structure is tested and compared to other standard fast control approaches. Full nonlinear realistic simulation results illustrate the overall good operation and behaviour of the proposed control approach.

Design of real-time actuated control system for modern tram at arterial intersections based on logic rules

This article is on the purpose of developing an isolated tram signal priority control strategy based on logic rule for modern tram system. The designed method is presented with features that can ensure the intersection operates in a proper manner on the premise of tram priority and avoid vehicle queue overflow when the tram passes. In this study, the new method description consists of two parts: (1) the detector locations are determined, which include the upstream detector, the upstream trigger detector, the downstream detector, and the queuing detector upon entry approach to the intersection; (2) the corresponding priority logical algorithm for signal control is designed. The proposed method is experimentally examined in a tram intersection in Huaian city, China. In the process of the experiment, the detector layout scheme and optimal priority control model are simulated and verified using the VisVAP module of the Vissim simulation software. In the experimental results, the designed scheme significantly decreases average delay than the fixed timing signal control method, while it also can prevent the vehicle queue from overflowing compared to the absolute priority actuated control scheme.

Design and implementation of real‐time monitoring and control system supported with IOS/Android application for industrial furnaces

SCADA (supervisory control and data acquisition) systems have been used widely in the manufacturing process in parallel to the rapid advancement of technology in recent years. The quality of products in these systems depends on direct process monitoring and control. Therefore, in this study, a SCADA‐based scale model is developed for real‐time monitoring and control of an industrial furnace by using Android/IOS‐based smartphones. To achieve the desired temperature in the furnace and to keep the energy saving constant, a PLC‐based SCADA system was designed. In the designed system, the furnace temperature is measured continuously by sensors and the furnace voltage is set as analog in order to reach the desired temperature as soon as possible. Different PID parameters are used to achieve this aim. Thus, the product quality is increased and energy efficiency is achieved. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Design of AGV 3D Real-Time Simulation Control System Based on Wireless Network

For most of the AGV superior control system is planar two-dimensional, poor visibility and lack of equipment operating efficiency statistics, A three-dimensional AGV simulation control system based on wireless communication and Flexsim logistics simulation software is proposed.. Through the socket socket connection zigbee wireless transmission module serial port and Flexsim software completes the data communication between the processes, thus establishes AGV and Flexsim data communication. Build the 3D system simulation model of AGV and write the control algorithm through Flexsim. At the same time, call the SQL database data to complete the real-time simulation and analyze the running status in real time. Mainly studied the data communication interaction between the AGV wireless communication module and Flexsim, using the AGV of the college laboratory to conduct field tests. The results show that the design program basically achieves the expected functions and effects.

Active coupling suppression and real-time control system design and implementation for three-axis electronic flight motion simulator

Modelling of a three-axis electronic flight motion simulator with U-O-O structure is achieved in this paper, based on recursive Newton–Euler equations. To overcome the shortcomings of passive decoupling control methods, an active coupling torque suppression method is proposed using velocity internal feedback by analysing the influence of the coupling torque. Detailed control software and hardware implementation is given for the real-time control system. Experimental tests show the designed flight motion simulator system performs good dynamic and static performances.

Real Time Pressure Control in Pneumatic Actuators

This paper explains the design of real-time control system for drives which use a pneumatic artificial muscles. Described is the design of hardware and software equipment, as well as design of these components involvement in the experimental facility with artificial muscles. In this paper are referred experimental measurements on the device aimed at monitoring the changes in observed PAMs characteristics caused by pressure changes in artificial muscles during their operation.