分布式机载机电综合管理系统时滞预估控制器的设计

通过分析分布式系统中由于网络数据传输的时滞现象而带来的前向通道和反馈时滞环节对系统控制性能的影响,设计了基于Smith预估原理的预估控制器。通过简化得到等效的滞后校正环节并进行了修正。根据滞后校正环节的频率特性进一步简化,得到工程实用的PI控制器模型。最后对设计的预估控制器进行仿真验证,表明所设计的PI控制器具有较好的控制效果和对时滞变化的鲁棒性,能够应用于机载分布式机电综合管理系统。     

Adaptive smoothness evaluation and multiple asymmetric histogram modification for reversible data hiding

In this paper, an adaptive reversible data hiding (RDH) algorithm based on multiple asymmetric histograms is proposed by making full use of the image content. Different from existing multiple prediction error histogram (PEHs) modification methods that directly cluster all the pixels of a cover image into multiple categories, we firstly utilize a smoothness threshold to exclude as many pixels in complex regions as possible for reducing unnecessary pixel shifting, and then exploit fuzzy C-means with multiple deliberately-designed features to construct multiple sharply-distributed categories, which helps in increasing the subsequent embedding performance. Two asymmetric PEHs for each class are generated using a pair of asymmetric predictors, and the short part of each asymmetric PEH is modified to reduce the number of invalid modifications. The improved discrete particle swarm optimization is used to adaptively select the best bin while reducing computational complexity. The experimental results show that the proposed method outperforms several state-of-the-art RDH methods.     

Application of single-step single nucleotide polymorphism best linear unbiased predictor model with unknown-parent groups for type traits in Japanese Holsteins

The objectives of this study were to investigate the computational performance and the predictive ability and bias of a single-step SNP BLUP model (ssSNPBLUP) in genotyped young animals with unknown-parent groups (UPG) for type traits, using national genetic evaluation data from the Japanese Holstein population. The phenotype, genotype, and pedigree data were the same as those used in a national genetic evaluation of linear type traits classified between April 1984 and December 2020. In the current study, 2 data sets were prepared: the full data set containing all entries up to December 2020 and a truncated data set ending with December 2016. Genotyped animals were classified into 3 types: sires with classified daughters (S), cows with records (C), and young animals (Y). The computing performance and prediction accuracy of ssSNPBLUP were compared for the following 3 groups of genotyped animals: sires with classified daughters and young animals (SY); cows with records and young animals (CY); and sires with classified daughters, cows with records, and young animals (SCY). In addition, we tested 3 parameters of residual polygenic variance in ssSNPBLUP (0.1, 0.2, or 0.3). Daughter yield deviations (DYD) for the validation bulls and phenotypes adjusted for all fixed effects and random effects other than animal and residual (Y_adj) for the validation cows were obtained using the full data set from the pedigree-based BLUP model. The regression coefficients of DYD for bulls (or Y_adj for cows) on the genomic estimated breeding value (GEBV) using the truncated data set were used to measure the inflation of the predictions of young animals. The coefficient of determination of DYD on GEBV was used to measure the predictive ability of the predictions for the validation bulls. The reliability of the predictions for the validation cows was calculated as the square of the correlation between Y_adj and GEBV divided by heritability. The predictive ability was highest in the SCY group and lowest in the CY group. However, minimal difference was found in predictive abilities with or without UPG models using different parameters of residual polygenic variance. The regression coefficients approached 1.0 as the parameter of residual polygenic variance increased, but regression coefficients were mostly similar regardless of the use of UPG across the groups of genotyped animals. The ssSNPBLUP model, including UPG, was demonstrated as feasible for implementation in the national evaluation of type traits in Japanese Holsteins.     

Observer-based control for high order delayed systems with an unstable pole and a pole at the origin

Time delays in dynamical systems are challenging when trying to control them. One of the most common techniques consists in estimating one or more signals of interest before they are delayed, in order to use them in the control stage. In this work, an observer-based control strategy for unstable linear systems with a pole at the origin and delay is suggested. Also, the proposed observer is extended to be used in the case of a high order unstable delayed system. Likewise, the conditions to ensure the existence of the proposed observer-predictor are presented. A methodology is introduced to obtain the observer parameters. The proposed observer scheme makes use of a Proportional-Integral-Derivative control that makes it possible to ensure the tracking of step-type references and the rejection of disturbances of the same type in the closed-loop system.     

Robust consensus of heterogeneous multiagent systems with switching topologies: A time-delay case

The robust leader-following consensus of heterogeneous multiagent systems under switching communication topologies is investigated in this paper. Especially, the input delay is considered in each follower. In order to access the information of leader through time-varying communication, a type of distributed dynamic compensator is proposed for every follower firstly, which get rid of the dependence on the global spectrum information and is proved that it can be viewed as a asymptotic observer of the leader. Then combined with the internal model principle, two types of distributed control law are proposed based on the compensator. By applying the truncated predictor feedback scheme to synthesize the closed-loop systems, it is proved that the consensus can be achieved by both of the control laws despite the existence of the input delay and the plant parameters perturbations. Finally, numerical simulations are illustrated to demonstrate the results.     

Disturbance rejection based tracking control design for fuzzy switched systems with time-varying delays and disturbances

The disturbance rejection and tracking problem of T-S fuzzy switched systems with uncertainties, input time-varying delays and disturbances is addressed in this article. For that cause, a modified repetitive control protocol based on the improved-equivalent-input-disturbance (IEID) estimator and extended Smith predictor approach has been proposed, which guarantees the perfect disturbance estimation and tracking performances with high precision. Specifically, by incorporating the transfer function of main feedback path in conventional Smith predictor block, the input time-varying delays are effectively compensated. In the direction of estimating the disturbances, an active disturbance rejection technique called IEID estimator approach is precisely considered. By exploiting the output of the IEID estimator and parallel distributed compensation strategy, the fuzzy rule based modified repetitive control system is formulated. Further, by making use of Lyapunov method together with average dwell-time approach, a set of sufficient conditions in the form of matrix inequalities are established. More respectively, by solving the developed matrix inequalities, the controller and observer gain matrices are determined. At last, the method proposed in this work is validated in terms of presenting the simulation results of two numerical examples, including boiler-turbine system.