A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a ...A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.展开更多
This paper deals with fault isolation in nonlinear analog circuits with tolerance under an insufficient number of independent voltage measurements.A neural network-based L1-norm optimization approach is proposed and u...This paper deals with fault isolation in nonlinear analog circuits with tolerance under an insufficient number of independent voltage measurements.A neural network-based L1-norm optimization approach is proposed and utilized in locating the most likely faulty elements in nonlinear circuits.The validity of the proposed method is verified by both extensive computer simulations and practical examples.One simulation example is presented in the paper.展开更多
In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory opti...In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory optimization (MORTO) approach via generalized varying domain (GVD) is proposed. Using the direct collocation approach, the trajectory optimization problem involving multiple objectives is discretized into a nonlinear multi-objective programming with priorities. In terms of fuzzy sets, the objectives are fuzzified into three types of fuzzy goals, and their constant tolerances are substituted by the varying domains. According to the principle that the objective with higher priority has higher satisfactory degree, the priority requirement is modeled as the order constraints of the varying domains. The corresponding two-side, single-side, and hybrid-side varying domain models are formulated for three fuzzy relations respectively. By regulating the parameter, the optimal reentry trajectory satisfying priorities can be achieved. Moreover, the performance about the parameter is analyzed, and the algorithm to find its specific value for maximum priority difference is proposed. The simulations demonstrate the effectiveness of the proposed method for hypersonic vehicles, and the comparisons with the traditional methods and sensitivity analysis are presented.展开更多
For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in ...For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.展开更多
电-气综合能源系统(integrated energy system,IES)的发展有助于提高能源效率并支撑可持续能源转型。电力网络和天然气网络通常隶属于不同的运营主体,这制约了IES的能源利用效率和多能互济协同。在此背景下,提出一种各能源子系统独立优...电-气综合能源系统(integrated energy system,IES)的发展有助于提高能源效率并支撑可持续能源转型。电力网络和天然气网络通常隶属于不同的运营主体,这制约了IES的能源利用效率和多能互济协同。在此背景下,提出一种各能源子系统独立优化的分布式最优调度方法。建立了电力网络潮流约束、天然气网络管网约束、电-气耦合约束下的IES集中式控制模型,并利用凸松弛技术和大M法对非凸约束进行了转化;基于交替方向乘子法(alternating direction method of multipliers,ADMM)对集中式控制模型进行解耦,使其转化为电力网络和天然气网络独立优化的分布式协同控制模型,并给出了电-气IES分布式控制方法的实施流程;用算例系统对所提方法的可行性和有效性做了验证。展开更多
随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与...随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与运行策略。首先,建立电动汽车可调充电功率灵活性聚合模型,提出基于Louvain算法的改进模块度指标配电网分布式集群划分方法;其次,基于历史数据信息生成电动汽车多时间尺度充电场景,提出考虑电动汽车充电灵活性的分布式集群协同优化模型;最后,采用同步交替方向乘子法(synchronous alternating direction multiplier method,SADMM)实现各集群优化模型的分布式求解。仿真结果表明,利用电动汽车充电灵活性参与配电网协同运行可有效提高分布式光伏利用率,并且在满足电动汽车用户充电需求的同时保证了配电网电压运行安全。展开更多
为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束...为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。展开更多
基金This project was supported by the National Natural Science Foundation of China (90405011).
文摘A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.
文摘This paper deals with fault isolation in nonlinear analog circuits with tolerance under an insufficient number of independent voltage measurements.A neural network-based L1-norm optimization approach is proposed and utilized in locating the most likely faulty elements in nonlinear circuits.The validity of the proposed method is verified by both extensive computer simulations and practical examples.One simulation example is presented in the paper.
基金supported by the Natural Science Foundation of Tianjin(12JCZDJC30300)the Research Foundation of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201613)the State Scholarship Fund of China
文摘In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory optimization (MORTO) approach via generalized varying domain (GVD) is proposed. Using the direct collocation approach, the trajectory optimization problem involving multiple objectives is discretized into a nonlinear multi-objective programming with priorities. In terms of fuzzy sets, the objectives are fuzzified into three types of fuzzy goals, and their constant tolerances are substituted by the varying domains. According to the principle that the objective with higher priority has higher satisfactory degree, the priority requirement is modeled as the order constraints of the varying domains. The corresponding two-side, single-side, and hybrid-side varying domain models are formulated for three fuzzy relations respectively. By regulating the parameter, the optimal reentry trajectory satisfying priorities can be achieved. Moreover, the performance about the parameter is analyzed, and the algorithm to find its specific value for maximum priority difference is proposed. The simulations demonstrate the effectiveness of the proposed method for hypersonic vehicles, and the comparisons with the traditional methods and sensitivity analysis are presented.
基金This work was supported by the National Natural Science Foundation of China(62073093)the Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province(LBH-Q19098)+1 种基金the Heilongjiang Provincial Natural Science Foundation of China(LH2020F017)the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology.
文摘For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.
文摘电-气综合能源系统(integrated energy system,IES)的发展有助于提高能源效率并支撑可持续能源转型。电力网络和天然气网络通常隶属于不同的运营主体,这制约了IES的能源利用效率和多能互济协同。在此背景下,提出一种各能源子系统独立优化的分布式最优调度方法。建立了电力网络潮流约束、天然气网络管网约束、电-气耦合约束下的IES集中式控制模型,并利用凸松弛技术和大M法对非凸约束进行了转化;基于交替方向乘子法(alternating direction method of multipliers,ADMM)对集中式控制模型进行解耦,使其转化为电力网络和天然气网络独立优化的分布式协同控制模型,并给出了电-气IES分布式控制方法的实施流程;用算例系统对所提方法的可行性和有效性做了验证。
文摘随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与运行策略。首先,建立电动汽车可调充电功率灵活性聚合模型,提出基于Louvain算法的改进模块度指标配电网分布式集群划分方法;其次,基于历史数据信息生成电动汽车多时间尺度充电场景,提出考虑电动汽车充电灵活性的分布式集群协同优化模型;最后,采用同步交替方向乘子法(synchronous alternating direction multiplier method,SADMM)实现各集群优化模型的分布式求解。仿真结果表明,利用电动汽车充电灵活性参与配电网协同运行可有效提高分布式光伏利用率,并且在满足电动汽车用户充电需求的同时保证了配电网电压运行安全。
文摘为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。
