A new method to improve the real-time performance of aero-engine component level model

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Changpeng Cai ◽  
Qiangang Zheng ◽  
Haibo Zhang

AbstractIn order to improve the real-time performance of aero-engine component-level models, an automatic fast positioning interpolation method is proposed. Based on the maximum parameter slope, this method can automatically determine the interpolation cut in point, change the disadvantage of low efficiency of traditional sequential interpolation from the starting point, effectively reduce the interpolation interval, thus greatly improving the efficiency of interpolation. The method is applied to the calculation of gas thermodynamic parameters and the interpolation of the characteristic of rotating parts ,so as to ameliorate the real-time performance of the single-stage flow path calculation of the component-level model. Simulation results show that, compared with the traditional method, the method proposed in this paper improves the fan characteristic calculation efficiency by 47.5%, reduces the time of single complete flow calculation by 74.3% when the dynamic and steady-state accuracy changes are less than 0.4%, which greatly improves the real-time performance of the component-level model.

2014 ◽  
Vol 568-570 ◽  
pp. 1036-1040 ◽  
Author(s):  
Hua Cong Li ◽  
Hong An Zhang ◽  
Xiao Bao Han ◽  
Jiang Feng Fu

Since the solving process of hydraulic dynamic simulation is complex and computational ineffectiveness,the aero-engine actuators real-time modeling is presented in this paper. Combined with the precise model, the convergence of the model and flow coefficient is analyzed. The real-time model operates a number of solving processes in one 20ms simulation cycle and the convergence of fix-step algorithm is guaranteed by adjusting the relevant parameters. The simulation shows that the real-time model can improve the computational efficiency with satisfactory real-time performance and precision.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jiajie Chen ◽  
Zhongzhi Hu ◽  
Jiqiang Wang

Aero-engine real-time models are widely used in control system design, integration, and testing. They can be used as the basis for model-based engine intelligent controls and health management, which is critical to improve engine safety, reliability, economy, and other performance indicators. This article provides an up-to-date review on aero-engine real-time modeling methods, model adaptation techniques, and applications for the last several decades. Besides, future research directions are also discussed, mainly focusing on the following four areas:(1) verification of the aero-engine real-time model over the full flight envelope; (2) better balance between real-time performance and accuracy in simplified methods for the aero-thermodynamic component level models; (3) further improvement in the real-time performance for the identified nonlinear models over the full flight envelope; (4) improvement of hybrid on-board adaptive real-time models combining the advantages of both model-based and data-based on-board adaptive real-time modeling methods.


Author(s):  
Yunlai Wang ◽  
Xi Wang

Abstract Nonlinear model predictive control (NMPC) is a strategy suitable for dealing with highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. Because of the complexity of the algorithm and the real-time performance of the predictive model, it has thus far been infeasible to implement model predictive control in the realtime control system of aircraft engine. In most nonlinear model predictive control, nonlinear interior point methods (IPM) are used to calculate the optimal solution, which iterate to the optimal solution based on the Jacobian and Hessian matrix. Most nonlinear IPM solver, such as MATLAB fmincon and IPOPT, cannot calculate the Jacobian and Hessian matrix precisely and quickly, instead of using numerical differentiation to calculate the Jacobian matrix and BFGS method to approach to the Hessian matrix. From what has been discussed above, we will 1) improve the real-time performance of predictive model by replacing the time-consuming component level model (CLM) with a neural network model, which is trained based on the data of component level model, 2) precisely calculate the Jacobian and Hessian matrix using automatic differentiation, and propose a group of algorithms to make NMPC strategy quicker, which include making use of the structure of predictive model, and the integrity of weighted sums of Hessian matrix in IPM. Finally, considering input and output constraints, the fast NMPC strategy is compared with normal NMPC. Simulation results with mean time of 19.3% – 27.9% of normal NMPC on different platforms, verify that the fast NMPC proposed can improve the real-time performance during the process of acceleration, deceleration for aircraft engine.


2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.


2014 ◽  
Vol 933 ◽  
pp. 584-589
Author(s):  
Zhi Chun Zhang ◽  
Song Wei Li ◽  
Wei Ren Wang ◽  
Wei Zhang ◽  
Li Jun Qi

This paper presents a system in which the cluster devices are controlled by single-chip microcomputers, with emphasis on the cluster management techniques of single-chip microcomputers. Each device in a cluster is controlled by a single-chip microcomputer collecting sample data sent to and driving the device by driving data received from the same cluster management computer through COMs. The cluster management system running on the cluster management computer carries out such control as initial SCM identification, run time slice management, communication resource utilization, fault tolerance and error corrections on single-chip microcomputers. Initial SCM identification is achieved by signal responses between the single-chip microcomputers and the cluster management computer. By using the port priority and the parallelization of serial communications, the systems real-time performance is maximized. The real-time performance can be adjusted and improved by increasing or decreasing COMs and the ports linked to each COM, and the real-time performance can also be raised by configuring more cluster management computers. Fault-tolerant control occurs in the initialization phase and the operational phase. In the initialization phase, the cluster management system incorporates unidentified single-chip microcomputers into the system based on the history information recorded on external storage media. In the operational phase, if an operation error of reading and writing on a single-chip microcomputer reaches a predetermined threshold, the single-chip microcomputer is regarded as serious fault or not existing. The cluster management system maintains accuracy maintenance database on external storage medium to solve nonlinear control of specific devices and accuracy maintenance due to wear. The cluster management system uses object-oriented method to design a unified driving framework in order to enable the implementation of the cluster management system simplified, standardized and easy to transplant. The system has been applied in a large-scale simulation system of 230 single-chip microcomputers, which proves that the system is reliable, real-time and easy to maintain.


Author(s):  
Junyi Hou ◽  
Lei Yu ◽  
Yifan Fang ◽  
Shumin Fei

Aiming at the problem that the mixed noise interference caused by the mixed projection noise system is not accurate and the real-time performance is poor, this article proposes an adaptive system switching filtering method based on Bayesian estimation switching rules. The method chooses joint bilateral filtering and improved adaptive median filtering as the filtering subsystems and selects the sub-filtering system suitable for the noise by switching rules to achieve the purpose of effectively removing noise. The simulation experiment was carried out by the self-developed human–computer interactive projection image system platform. Through the subjective evaluation, objective evaluation, and running time comparison analysis, a better filtering effect was achieved, and the balance between the filtering precision and the real-time performance of the interactive system was well obtained. Therefore, the proposed method can be widely applied to various human–computer interactive image filtering systems.


2016 ◽  
Vol 4 (3) ◽  
pp. 163-181
Author(s):  
Pouria Sarhadi ◽  
Reza Nad Ali Niachari ◽  
Morteza Pouyan Rad ◽  
Javad Enayati

Purpose The purpose of this paper is to propose a software engineering procedure for real-time software development and verification of an autonomous underwater robotic system. High performance and robust software are one of the requirements of autonomous systems design. A simple error in the software can easily lead to a catastrophic failure in a complex system. Then, a systematic procedure is presented for this purpose. Design/methodology/approach This paper utilizes software engineering tools and hardware-inthe-loop (HIL) simulations for real-time system design of an autonomous underwater robot. Findings In this paper, the architecture of the system is extracted. Then, using software engineering techniques a suitable structure for control software is presented. Considering the desirable targets of the robot, suitable algorithms and functions are developed. After the development stage, proving the real-time performance of the software is disclosed. Originality/value A suitable approach for analyzing the real-time performance is presented. This approach is implemented using HIL simulations. The developed structure is applicable to other autonomous systems.


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