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Matrix Power Control Algorithm for Multi-input Multi-output Random Vibration Test 认领 引用 被引量：13
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作者 CUI Xuli CHEN Huaihai +1 位作者 HE Xudong JIANG Shuangyan 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2011年第6期741-748,共8页
Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output(MIMO)random vibration test.During the control process with the difference control algorithm(DCA),a lower triangular m... Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output(MIMO)random vibration test.During the control process with the difference control algorithm(DCA),a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix.The diagonal elements of the lower triangular matrix(DELTM)may become negative.These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control.A proportional root mean square control algorithm(PRMSCA)provides another method to avoid the divergence caused by negative values of DELTM,but PRMSCA cannot control the cross-power spectrum.A new control algorithm named matrix power control algorithm(MPCA)is proposed in the paper.MPCA can guarantee that DELTM is always positive in the auto-power spectrum control.MPCA can also control the cross-power spectrum.After these three control algorithms are analyzed,three-input three-output random vibration control tests are implemented on a three-axis vibration shaker.The results show the validity of the proposed MPCA. 展开更多
关键词 multi-input multi-output environmental testing vibration control random vibration auto-power spectrum cross-power spectrum
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Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration 认领 引用 被引量：12
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作者 Ronghui ZHENG Huaihai CHEN Xudong HE 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2017年第6期1895-1906,共12页
A control method for Multi-Input Multi-Output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified ... A control method for Multi-Input Multi-Output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well. 展开更多
关键词 Cross spectra Kurtosis control Multi-input multi-output Non-Gaussian Random vibration test
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Multi-input multi-output random vibration control using Tikhonov filter 认领 引用 被引量：4
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作者 Cui Song Chen Huaihai +1 位作者 He Xudong Zheng Wei 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2016年第6期1649-1663,共15页
Noises always disturb the control effect of an environment test especially in multi-input multi-output(MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces w... Noises always disturb the control effect of an environment test especially in multi-input multi-output(MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces will be amplified and the response spectral lines may awfully exceed their tolerances. Most of the major biases between the response spectra and the reference spectra are produced by the amplified noises. However, ordinary control algorithms can hardly reduce the level of noises. The influences of the noises on both the auto- and cross-power spectra are analyzed in this paper. As a conventional frequency domain method on the inverse problem, the Tikhonov filter is adopted in the environment test to suppress the exceeding spectral lines. By altering regularization parameters gradually, the auto-power spectra can be improved in a closed control loop. Instead of using the traditional way of selecting regularization parameters, we observe the coherence change to estimate noise eliminations. Incidentally, the requirement of coherence control can be realized. The errors of the phase are then studied and a phase control algorithm is introduced at the end as a supplement of cross-power spectra control. The Tikhonov filter and the proposed phase control algorithm are tested numerically and experimentally. The results show that the noises in the vicinity of lightly damped resonant peaks are more stubborn. The response spectra are able to be greatly improved by the combination of these two methods. 展开更多
关键词 Coherence Environmental testing Multi-input multi-output(MIMO) Noise Phase control Tikhonov filter
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Set-point-related Indirect Iterative Learning Control for Multi-input Multi-output Systems 认领 引用 被引量：1
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作者 Huo, Zhen-Yu Yang, Zhu Pang, Yan-Jun 《International Journal of Automation and computing》 2012年第3期266-273,共8页
A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a su... A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser s system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results. 展开更多
关键词 Iterative learning control (ILC) indirect ILC multi-input multi-output (MIMO) 2-dimensional system asymptotical stability linear matrix inequality (LMI).
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Design of Decentralized Multi-input Multi-output Repetitive Control Systems 认领 引用
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作者 Edi Kurniawan Zhen-Wei Cao +1 位作者 Maria Mitrevska Zhi-Hong Man 《International Journal of Automation and computing》 CSCD 2016年第6期615-623,共9页
This paper presents the design of decentralized repetitive control （RC） for multi-input multi-output （MIMO） systems. An optimization method is used to obtain a RC compensator that ensures system stability and good... This paper presents the design of decentralized repetitive control （RC） for multi-input multi-output （MIMO） systems. An optimization method is used to obtain a RC compensator that ensures system stability and good tracking performance. The designed compensator is in the form of a stable, low order, and causal filter, in which the compensator can be implemented separately without being merged with the RC internal model. This will reduce complexity in the implementation. Simulation results and comparison study are given to demonstrate the effectiveness of the proposed design. The novelty of design is also verified in experiments on a 2 degrees of freedom （DOF） robot. 展开更多
关键词 Repetitive control （RC） compensator multi-input multi-output （MIMO） decentralized optimization two degrees of freedom robot.
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APPLICATION OF FRF ESTIMATOR BASED ON ERRORS-IN-VARIABLES MODEL IN MULTI-INPUT MULTI-OUTPUT VIBRATION CONTROL SYSTEM 认领 引用
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作者 GUAN Guangfeng CONG Dacheng +1 位作者 HAN Junwei LI Hongren 《Chinese Journal of Mechanical Engineering》 EI CAS 2007年第4期101-105,共5页
The FRF estimator based on the errors-in-variables(EV)model of multi-input multi-output(MIMO)system is presented to reduce the bias error of FRF HI estimator.The FRF HI estimator is influenced by the noises in the inp... The FRF estimator based on the errors-in-variables(EV)model of multi-input multi-output(MIMO)system is presented to reduce the bias error of FRF HI estimator.The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF.The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation.The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF(degree-of-freedom)hydraulic vibration table.The result shows that it is favorable to improve the control precision of the MIMO vibration control system. 展开更多
关键词 Multi-input multi-output(MIMO)system Errors-in-variables(EV)model 6-DOF hydraulic vibration table Waveform replication
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Dynamic Modeling and Closed-loop Control of Hybrid Grid-connected Renewable Energy System with Multi-input Multi-output Controller 认领 引用 被引量：4
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作者 Mahdi Salimi Fereshteh Radmand Mansour Hosseini Firouz 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2021年第1期94-103,共10页
In this study, a novel approach for dynamic modeling and closed-loop control of hybrid grid-connected renewable energy system with multi-input multi-output(MIMO) controller is proposed. The studied converter includes ... In this study, a novel approach for dynamic modeling and closed-loop control of hybrid grid-connected renewable energy system with multi-input multi-output(MIMO) controller is proposed. The studied converter includes two parallel DC-DC boost converters, which are connected into the power grid through a single-phase H-bridge inverter. The proposed MIMO controller is developed for maximum power point tracking of photovoltaic(PV)/fuel-cell(FC) input power sources and output power control of the grid-connected DC-AC inverter. Considering circuit topology of the system, a unique MIMO model is proposed for the analysis of the entire system. A unique model of the system includes all of the circuit state variables in DCDC and DC-AC converters. In fact, from the viewpoint of closed-loop controller design, the hybrid grid-connected energy system is an MIMO system. The control inputs of the system are duty cycles of the DC-DC boost converters and the amplitude modulation index of DC-AC inverters. Furthermore, the control outputs are the output power of the PV/FC input power sources as well as AC power injected into the power grid. After the development of the unique model for the entire system, a decoupling network is introduced for system input-output linearization due to inherent connection of the control outputs with all of the system inputs. Considering the decoupled model and small signal linearization, the required linear controllers are designed to adjust the outputs. Finally, to evaluate the accuracy and effectiveness of the designed controllers, the PV/FC based grid-connected system is simulated using the MATLAB/Simulink toolbox. 展开更多
关键词 Multi-input multi-output(MIMO)converter maximum power point tracking grid-connected inverter conversion function matrix
Transfer-learning multi-input multi-output equalizer for mode-division multiplexing systems 认领 引用
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作者 Tianfeng Zhao Feng Wen +3 位作者 Mingming Tan Baojian Wu Bo Xu Kun Qiu 《Chinese Optics Letters》 SCIE EI CAS CSCD 2024年第7期12-18,共7页
We propose a transfer-learning multi-input multi-output(TL-MIMO)scheme to significantly reduce the required training complexity for converging the equalizers in mode-division multiplexing(MDM)systems.Based on a built ... We propose a transfer-learning multi-input multi-output(TL-MIMO)scheme to significantly reduce the required training complexity for converging the equalizers in mode-division multiplexing(MDM)systems.Based on a built three-mode(LP01,LP11a,and LP11b)multiplexed experimental system,we thoughtfully investigate the TL-MIMO performances on the three-typed data,collecting from different sampling times,launching optical powers,and inputting optical signal-to-noise ratios(OSNRs).A dramatic reduction of approximately 40%–83.33%in the required training complexity is achieved in all three scenarios.Furthermore,the good stability of TL-MIMO in both the launched powers and OSNR test bands has also been proved. 展开更多
关键词 mode division multiplexing multi-input multi-output transfer learning training complexity
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Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output 认领 引用
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作者 Shang LIU Ishtiaq AHMAD +1 位作者 Ping ZHANG Zhi ZHANG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2018年第5期674-684,共11页
This paper discusses transmission performance and power allocation strategies in an underlay cognitive radio （CR） network that contains relay and massive multi-input multi-output （MIMO）. The downlink transmission ... This paper discusses transmission performance and power allocation strategies in an underlay cognitive radio （CR） network that contains relay and massive multi-input multi-output （MIMO）. The downlink transmission performance of a relay-aided massive MIMO network without CR is derived. By using the power distribution criteria, the kth user＇s asymptotic signal to interference and noise ratio （SINR） is independent of fast fading. When the ratio between the base station （BS） antennas and the relay antennas becomes large enough, the transmission performance of the whole system is independent of BS-to-relay channel parameters and relates only to the relay-to-users stage. Then cognitive transmission performances of primary users （PUs） and secondary users （SUs） in an underlay CR network with massive MIMO are derived under perfect and imperfect channel state information （CSI）, including the end-to-end SINR and achievable sum rate. When the numbers of primary base station （PBS） antennas, secondary base station （SBS） antennas, and relay antennas become infinite, the asymptotic SINR of the kth PU and SU is independent of fast fading. The interference between the primary network and secondary network can be canceled asymptotically.Transmission performance does not include the interference temperature. The secondary network can use its peak power to transmit signals without causing any interference to the primary network. Interestingly, when the antenna ratio becomes large enough, the asymptotic sum rate equals half of the rate of a single-hop single-antenna K-user system without fast fading. Next, the PUs＇ utility function is defined. The optimal relay power is derived to maximize the utility function. The numerical results verify our analysis. The relationships between the transmission rate and the antenna nunber, relay power, and antenna ratio are simulated. We show that the massive MIMO with linear pre-coding can mitigate asymptotically the interference in a multi-user underlay CR network. The primary and secondary networks can operate independently. 展开更多
关键词 Massive multi-input multi-output Cognitive radio Relay network Tiansmission rate Power analysis
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A benchmark system to investigate the non-minimum phase behaviour of multi-input multi-output systems 认领 引用
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作者 SaeedReza Tofighi Farshad Merrikh-Bayat 《Journal of Control and Decision》 EI 2018年第3期300-317,共18页
In this paper,the problem of designing a multi-input multi-output(MIMO)systemfor studying the non-minimum phase(NMP)behaviour is considered.For this purpose,a NMP MIMO circuit is proposed and studied under different c... In this paper,the problem of designing a multi-input multi-output(MIMO)systemfor studying the non-minimum phase(NMP)behaviour is considered.For this purpose,a NMP MIMO circuit is proposed and studied under different conditions.The main reason for designing this circuit is the lack of a simple and flexible benchmark for examining different control methods.Due to the simple structure and capability of showing different NMP characteristics,our proposed system is a suitable choice to study the behaviour of these systems.Also,our proposed system can be extended by series and parallel connections to generate more complicated benchmarks.The other advantages of this system are the large number of tunable parameters,adjustable interaction,variable number of poles and zeros,and inexpensive cost.Moreover,this benchmark can be used as a tool for hardware simulation.Finally,an optimal H∞decoupling control is applied to this benchmark to verify its effectiveness. 展开更多
关键词 Non-minimum phase system multi-input multi-output optimal H∞decoupling control transmission zero Smith–McMillan form
Data-based neural controls for an unknown continuous-time multi-input system with integral reinforcement 认领 引用
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作者 Yongfeng Lv Jun Zhao +1 位作者 Wan Zhang Huimin Chang 《Control Theory and Technology》 EI CSCD 2025年第1期118-130,共13页
Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.Ho... Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.However,solving the Hamilton-Jacobi-Bellman(HJB)equations for nonlinear systems requires precise and complicated dynamics.Moreover,the research and application of IRL in continuous-time(CT)systems must be further improved.To develop the IRL of a CT nonlinear system,a data-based adaptive neural dynamic programming(ANDP)method is proposed to investigate the optimal control problem of uncertain CT multi-input systems such that the knowledge of the dynamics in the HJB equation is unnecessary.First,the multi-input model is approximated using a neural network(NN),which can be utilized to design an integral reinforcement signal.Subsequently,two criterion networks and one action network are constructed based on the integral reinforcement signal.A nonzero-sum Nash equilibrium can be reached by learning the optimal strategies of the multi-input model.In this scheme,the NN weights are constantly updated using an adaptive algorithm.The weight convergence and the system stability are analyzed in detail.The optimal control problem of a multi-input nonlinear CT system is effectively solved using the ANDP scheme,and the results are verified by a simulation study. 展开更多
关键词 Adaptive dynamic programming Integral reinforcement Neural networks Heuristic dynamic programming Multi-input system
Using a Multi-Output Neural Network Model to Standardize Heterogeneous Fisheries Data 认领 引用
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作者 XU Zhenqi LIU Yang WANG Jintao 《Journal of Ocean University of China》 SCIE CAS CSCD 2025年第5期1373-1385,I0667-I0676,共13页
Biological data in fishery ecology have complex structures and are highly heterogeneous.Catch per unit effort(CPUE)estimated from fishery-dependent data are often used to characterize abundance indices(AI)of fish spec... Biological data in fishery ecology have complex structures and are highly heterogeneous.Catch per unit effort(CPUE)estimated from fishery-dependent data are often used to characterize abundance indices(AI)of fish species,which is critical in fish stock assessment.However,additional considerations need to be undertaken to ensure robust estimation because of the latently complicated structures in fishery-dependent data.Here,we elaborated the process of constructing multi-output artificial neural network models to standardize CPUE for heterogeneous fishing operations and applied it to the skipjack tuna(Katsuwonus pelamis)in the western and central Pacific Ocean(WCPO).Seasonal,spatial,and environmental factors were input variables,and the CPUE of four types of skipjack tuna fisheries were set as output variables.The optimal structure for multi-output neural network was evaluated by systematic comparison in 100 runs hold-out cross-validation.The results showed that the final multi-output neural network model with high accuracy can predict the spatial and temporal trends of skipjack tuna abundance. 展开更多
关键词 western and central Pacific Ocean skipjack tuna BP neural network multi-output model CPUE standardization ENSO
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A multi-input and multi-output design on automotive engine management system 认领 引用
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作者 翟禹嘉 孙研 +1 位作者 钱科军 LEE Sang-hyuk 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第12期4687-4692,共6页
Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotiv... Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069. 展开更多
关键词 neural network spark-ignition engine dynamical system modeling system identification multi-input and mult-output(MIMO) control system
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Kinematically Coupled Multi-Output Component Mechanism Design for Rehabilitation Robots 认领 引用
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作者 Ye Zhang Hui Bian +2 位作者 Bokang Yin Jiale Ge Tieshi Zhao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第4期132-145,共14页
Aiming at the innovative design requirements of rehabilitation robots with multiple kinematically coupled components and the current absence of systematic processes in the design of such mechanisms,this paper presents... Aiming at the innovative design requirements of rehabilitation robots with multiple kinematically coupled components and the current absence of systematic processes in the design of such mechanisms,this paper presents the concept of a multi-output component mechanism(MOCM).A classification methodology for the MOCM is proposed based on the operational coupling between the actuators and the output components within closedloop mechanisms.Building on the classification results,a design methodology for a kinematically coupled MOCM(KCMOCM)is proposed based on the actuation distribution within the closed-loop sub-mechanisms.First,the number and relative kinematic characteristics of the output components are determined based on the application environment of the mechanism.These components are then grouped and classified according to motion similarity principles,followed by the design of closed-loop sub-mechanisms with actuators for each group,ultimately forming a complete KCMOCM.Taking the sit-stand-lie-bed mechanism in a spinal cord injury lower-limb rehabilitation robot as an example,this study comprehensively considers the multi-posture transition task requirements and spatial constraint characteristics of lower-limb rehabilitation training to design the mechanism.By applying the mechanism design methodology,six practical novel configurations are developed with established evaluation criteria,and kinematic analysis and experimental validation are performed on the optimized configuration.The results demonstrate that the optimized configuration satisfies the multi-posture rehabilitation training requirements for lower limbs.This validates the efficacy of the design methodology.Furthermore,the scalability of the design methodology is validated through the development of a robotic finger rehabilitation mechanism. 展开更多
关键词 Kinematically coupled multi-output component mechanism Mechanism design Rehabilitation robots
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地下水预冷新风的地源热泵空调系统动态特性研究 认领 引用
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作者 王林 龙滨 +3 位作者 李修真 谈莹莹 冯森 陈森 《工程热物理学报》 EI CAS CSCD 北大核心 2026年第7期2209-2219,共11页
地下水预处理新风的地源热泵空调系统节能效果显著,但因负荷波动和多输入多输出特性使得系统动态响应特性预测精度偏低。为此,基于实验验证建立地下水预处理新风的地源热泵空调系统状态空间模型,评估了地下水温度、地下水流量及新风温... 地下水预处理新风的地源热泵空调系统节能效果显著,但因负荷波动和多输入多输出特性使得系统动态响应特性预测精度偏低。为此,基于实验验证建立地下水预处理新风的地源热泵空调系统状态空间模型,评估了地下水温度、地下水流量及新风温度扰动对系统动态性能的影响。结果表明:地下水温度、地下水流量及新风温度等关键参数扰动对系统动态性能有显著影响,且导致热泵机组COPτ增幅呈线性变化;地下水温度扰量递增1~5°C,热泵机组COPτ增幅最终维持在-0.048~-0.24,响应时间为130 s;地下水流量扰量递增0.01~0.1 kg/s,热泵机组COPτ增幅维持在0.047~0.47,响应时间为110 s;新风温度扰量递增1~5°C,热泵机组COPτ增幅维持在-0.047~-0.215,响应时间为225 s。研究结果可为新系统高效运行调控提供理论指导。 展开更多
关键词 地源热泵 状态空间方法 多输入多输出 动态性能 性能系数 响应时间
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CNN-based multi-output regression model to estimate infrastructural surface crack dimensions adopting a generalised patch size and FWHM-based width quantification 认领 引用
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作者 Sudipta Debroy Arjun Sil 《Digital Twins and Applications》 2025年第1期75-102,共28页
To cater the need for real-time crack monitoring of infrastructural facilities,a CNN-regression model is proposed to directly estimate the crack properties from patches.RGB crack images and their corresponding masks o... To cater the need for real-time crack monitoring of infrastructural facilities,a CNN-regression model is proposed to directly estimate the crack properties from patches.RGB crack images and their corresponding masks obtained from a public dataset are cropped into patches of 256 square pixels that are classified with a pre-trained deep convolution neural network,the true positives are segmented,and crack properties are extracted using two different methods.The first method is primarily based on active contour models and level-set segmentation and the second method consists of the domain adaptation of a mathematical morphology-based method known as FIL-FINDER.A statistical test has been performed for the comparison of the stated methods and a database prepared with the more suitable method.An advanced convolution neural network-based multi-output regression model has been proposed which was trained with the prepared database and validated with the held-out dataset for the prediction of crack-length,crack-width,and width-uncertainty directly from input image patches.The pro-posed model has been tested on crack patches collected from different locations.Huber loss has been used to ensure the robustness of the proposed model selected from a set of 288 different variations of it.Additionally,an ablation study has been conducted on the top 3 models that demonstrated the influence of each network component on the pre-diction results.Finally,the best performing model HHc-X among the top 3 has been proposed that predicted crack properties which are in close agreement to the ground truths in the test data. 展开更多
关键词 ablation CNN convolution neural network crack crack patch estimation FWHM length multi-output regression segmentation uncertainty width
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A Dynamic Matrix Controller with Feedforward for Flow Field in Intermittent Transonic Wind Tunnels 认领 引用
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作者 DU Ning ZHU Wenjie +2 位作者 YAO Dan ZOU Xinlei QIN Jianhua 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2026年第1期55-72,共18页
Intermittent transonic wind tunnels demand high-precision and stable control of Mach number and stagnation pressure during the variation of model angle of attack,while the traditional proportional integral derivative(... Intermittent transonic wind tunnels demand high-precision and stable control of Mach number and stagnation pressure during the variation of model angle of attack,while the traditional proportional integral derivative(PID)control strategy fails to achieve the Mach number control error target of 0.001 and is inept at resisting flow field disturbances caused by rapid changes in angle of attack.Aiming at this problem,this study takes the intermittent transonic wind tunnel of China Aerodynamics Research and Development Center as the research object and optimizes the wind tunnel control system for its characteristics of multi-input multi-output(MIMO),large time delay and nonlinearity.First,the control system structure is reconstructed by introducing ejection pressure as a controlled variable to reduce the time lag from the main pressure regulating valve to the test section,and selecting static pressure instead of Mach number as a controlled variable to weaken the nonlinear coupling between Mach number and static pressure.Second,based on the first-order plus dead time process model of the wind tunnel,a MIMO dynamic matrix controller(DMC)for wind tunnel flow field is designed.Considering the predictable nature of angle-of-attack changes,a feedforward compensation strategy is integrated into the DMC to mitigate the pressure disturbance in the test section caused by the variation of angle of attack.Third,a complete tuning strategy for DMC parameters including sampling time,prediction horizon,control horizon and weight coefficients is formulated according to the wind tunnel model parameters under different Mach numbers.Experimental validations through practical blowing tests are carried out at Mach numbers of 0.578,0.675,0.714 and 0.822 to compare the control performance of the proposed feedforward DMC strategy with the traditional PID control and DMC without feedforward compensation.The results show that the proposed strategy stably controls the Mach number error within 0.001,and significantly improves the stagnation pressure control accuracy and anti-disturbance capability of the wind tunnel flow field.Moreover,the strategy exhibits excellent repeatability and robustness under different Mach number conditions.This study effectively solves the problem of high-precision flow field control under the rapid change of angle of attack in intermittent transonic wind tunnels,and provides a technical reference for the flow field control of complex fluid test devices such as hypersonic wind tunnels. 展开更多
关键词 intermittent transonic wind tunnel flow field control dynamic matrix controller(DMC) feedforward compensation multi-input multi-output(MIMO)system parameter tuning
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基于多级注意力机制的滑坡位移多步预测方法 认领 引用
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作者 任冯 肖慧 +2 位作者 冯沂萱 吴雨洁 艾玉洁 《电子测量技术》 北大核心 2026年第1期40-49,共10页
针对土质滑坡位移多步预测方法的缺乏以及在多时间步长下预测误差较大的问题,本文提出了一种基于多级注意力机制并行模型的滑坡位移多步预测方法。采用多输入多输出的预测策略,通过含有多头注意力机制的Transformer编码器网络分支以及... 针对土质滑坡位移多步预测方法的缺乏以及在多时间步长下预测误差较大的问题,本文提出了一种基于多级注意力机制并行模型的滑坡位移多步预测方法。采用多输入多输出的预测策略,通过含有多头注意力机制的Transformer编码器网络分支以及经全局注意力机制(GAM)优化的双向门控循环单元(BiGRU)网络分支,两个网络分支并行处理滑坡历史监测数据,之后对并行网络提取到的滑坡特征信息通过交叉注意力机制(CAM)进行特征融合后输出预测的滑坡多步位移值。实验结果表明,多级注意力机制模型在滑坡位移多步预测中平均绝对误差(MAE)、均方根误差(RMSE)分别为2.17 mm、3.05 mm,决定系数(R2)为0.9689,相较于其他模型误差最低,决定系数结果最优,在长时间步下的预测效果更加稳定,有利于提前预知滑坡发展动向,为滑坡的预防与治理提供了重要的技术支持。 展开更多
关键词 滑坡位移多步预测 多级注意力机制 Transformer编码器 双向门控循环单元 多输入多输出策略
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Local Partial Least Squares Based Online Soft Sensing Method for Multi-output Processes with Adaptive Process States Division 认领 引用 被引量：8
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作者 邵伟明 田学民 王平 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第7期828-836,共9页
Local learning based soft sensing methods succeed in coping with time-varying characteristics of processes as well as nonlinearities in industrial plants. In this paper, a local partial least squares based soft sensin... Local learning based soft sensing methods succeed in coping with time-varying characteristics of processes as well as nonlinearities in industrial plants. In this paper, a local partial least squares based soft sensing method for multi-output processes is proposed to accomplish process states division and local model adaptation,which are two key steps in development of local learning based soft sensors. An adaptive way of partitioning process states without redundancy is proposed based on F-test, where unique local time regions are extracted.Subsequently, a novel anti-over-fitting criterion is proposed for online local model adaptation which simultaneously considers the relationship between process variables and the information in labeled and unlabeled samples. Case study is carried out on two chemical processes and simulation results illustrate the superiorities of the proposed method from several aspects. 展开更多
关键词 Local learning Online soft sensing Partial least squares F-test Multi-output process Process state division
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Relationship between Multi-Output Partially Bent Functions and Multi-Output Bent Functions 认领 引用 被引量：2
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作者 ZHAO Yaqun JU Guizhi WANG Jue 《Wuhan University Journal of Natural Sciences》 EI CAS 2006年第6期1887-1890,共4页
In this paper, the definition of multl-output partially Bent functions is presented and some properties are discussed. Then the relationship between multi-output partially Bent functions and multi-output Bent function... In this paper, the definition of multl-output partially Bent functions is presented and some properties are discussed. Then the relationship between multi-output partially Bent functions and multi-output Bent functions is given in Theorem 4, which includes Walsh spectrum expression and function expression. This shows that multi-output partially Bent functions and multi-output Bent functions can define each other in principle. So we obtain the general method to construct multi-output partially Bent functions from multi-output Bent functions. 展开更多
关键词 multi-output partially Bent functions multi-output Bent functions Walsh spectrum constructing
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