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| 1 | Leader-following consensus protocols for formation control of multi-agent network显示文摘Two protocols are presented,which can make agents reach consensus while achieving and preserving the desired formation in fixed topology with and without communication timedelay for multi-agent network.First,the protocol without considering the communication time-delay is presented,and by using Lyapunov stability theory,the sufficient condition of stability for this multi-agent system is presented.Further,considering the communication time-delay,the effectiveness of the protocol based on Lyapunov-Krasovskii function is demonstrated.The main contribution of the proposed protocols is that,as well as the velocity consensus is considered,the formation control is concerned for multi-agent systems described as the second-order equations.Finally,numerical examples are presented to illustrate the effectiveness of the proposed protocols. | Xiaoyuan Luo Nani Han Xinping Guan | 2011 | Journal of Systems Engineering and Electronics2011，22，6： | 10 |
| 2 | Experimental investigation on active acoustic flutter control显示文摘Experimenial studies on active acoustic fiutter control are carried out successfully in wind-tunnel after the theoretical study The experdrients verify the theory presented in the reference[1] and give valuable experimeotal results which predict a prondsing future of applying new techology and new ideas to the area of vibration induced by flow. | YANG Jun(Institute of Acoustics, Academic Sinica Beijing 100080)(State Key Lab. of Modern Acoustics, Naniing Universitg Naning 210093)HAN Fei QIU Xiaojun and SHA Jiazheng(State Key Lab. of Modern Acoustics, Nanjing Universitg Naning 210093) | 1997 | Chinese Journal of Acoustics1997，16，1： | 3 |
| 3 | An ε-domination based two-archive 2 algorithm for many-objective optimization显示文摘The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals in DA are selected based on the traditional Pareto dominance which decreases the selection pressure in the high-dimensional problems.The traditional algorithm even cannot converge due to the weak selection pressure.Meanwhile,Two_Arch2 adopts DA as the output of the algorithm which is hard to maintain diversity and coverage of the final solutions synchronously and increase the complexity of the algorithm.To increase the evolutionary pressure of the algorithm and improve distribution and convergence of the final solutions,an ε-domination based Two_Arch2 algorithm(ε-Two_Arch2) for many-objective problems(MaOPs) is proposed in this paper.In ε-Two_Arch2,to decrease the computational complexity and speed up the convergence,a novel evolutionary framework with a fast update strategy is proposed;to increase the selection pressure,ε-domination is assigned to update the individuals in DA;to guarantee the uniform distribution of the solution,a boundary protection strategy based on I_(ε+) indicator is designated as two steps selection strategies to update individuals in CA.To evaluate the performance of the proposed algorithm,a series of benchmark functions with different numbers of objectives is solved.The results demonstrate that the proposed method is competitive with the state-of-the-art multi-objective evolutionary algorithms and the efficiency of the algorithm is significantly improved compared with Two_Arch2. | WU Tianwei AN Siguang HAN Jianqiang SHENTU Nanying | 2022 | Journal of Systems Engineering and Electronics2022，33，1： | 1 |
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