A computational method of constraint stabilization and correction is introduced. The method is based on the Baumgart＇s one-step method. Constraint conditions are addressed to stabilize and correct the solution. Two e...A computational method of constraint stabilization and correction is introduced. The method is based on the Baumgart＇s one-step method. Constraint conditions are addressed to stabilize and correct the solution. Two examples are given to illustrate the results of the method.展开更多
By redefining the multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, say, u2_i, i=1, 2, ..., m, nonnegative constraints imposed on inequality constra...By redefining the multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, say, u2_i, i=1, 2, ..., m, nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed. For constructing the Lagrange neural network and Lagrange multiplier method, it is no longer necessary to convert inequality constraints into equality constraints by slack variables in order to reuse those results dedicated to equality constraints, and they can be similarly proved with minor modification. Utilizing this technique, a new type of Lagrange neural network and a new type of Lagrange multiplier method are devised, which both handle inequality constraints directly. Also, their stability and convergence are analyzed rigorously.展开更多
The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equa...The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.展开更多
The novel aircraft engine-off taxi towing system featuring aircraft power integration has demonstrated significant advantages,including reduced energy consumption,diminished emissions,and enhanced efficiency.However,t...The novel aircraft engine-off taxi towing system featuring aircraft power integration has demonstrated significant advantages,including reduced energy consumption,diminished emissions,and enhanced efficiency.However,the aircraft engine-off taxi towing system lacks the consideration of attendant constraints in the trajectory generation process,which can potentially lead to ground accidents and constrain the improvement of traction speed.Addressing this challenge,the present work investigates the optimal control problem of trajectory generation for the taxiing traction system in the complex stochastic environment in the airport flight area.For the stochastic constraints,a strategy of deterministic processing is proposed to describe the stochastic constraints using random constraints.Furthermore,an adaptive pseudo-spectral method is introduced to transform the optimal control problem into a nonlinear programming problem,enabling its effective resolution.Simulation results substantiate that the generated trajectory can efficiently handle the stochastic constraints and accomplish the given task towards the time-optimization objective,thereby effectively enhancing the stability and efficiency of the taxiing traction system,ensuring the safety of the aircraft system,and improving the ground access capacity and efficiency of the airport.展开更多
为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorith...为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorithm,FPEA).该算法的繁殖算子是由Aitken加速的不动点迭代模型导出的二次多项式,其整体框架继承传统演化算法(如差分演化算法)基于种群的迭代模式.试验结果表明:在基准函数集CEC2014、CEC2019上,本文算法的最优值平均排名在所有比较算法中排名第1;在4个工程约束设计问题上,FPEA与CSA、GPE等多个算法相比,能以较少的计算开销获得最高的求解精度.展开更多
现有全脉冲结构波形与处理方法,如相位编码波形匹配处理存在多普勒容忍度差的固有缺陷,线性调频(linear frequency modulation,LFM)波形加窗处理降低了距离分辨率和信噪比(signal-to-noise ratio,SNR)增益,难以适应高速多目标探测的任...现有全脉冲结构波形与处理方法,如相位编码波形匹配处理存在多普勒容忍度差的固有缺陷,线性调频(linear frequency modulation,LFM)波形加窗处理降低了距离分辨率和信噪比(signal-to-noise ratio,SNR)增益,难以适应高速多目标探测的任务需求。为此,本文提出了一种面向高速目标探测的多子脉冲结构波形设计与处理方法。首先,构建具有多子脉冲结构波形的回波模型,利用分段子脉冲压缩处理和子脉冲间相参处理方法,导出多子脉冲结构波形的距离-多普勒响应函数;然后,根据感兴趣的目标距离速度区间,建立恒模约束下以最小化加权积分距离-多普勒旁瓣电平为目标函数的多子脉冲结构波形优化设计问题;最后,引入坐标下降(coordinate descent,CD)优化框架,将高维非凸约束优化问题的求解转变为多个一维优化问题的迭代求解,且推导出这些低维问题的闭式解。仿真表明,所设计的多子脉冲结构波形具有较好的多普勒容忍度和较低的局部距离-多普勒旁瓣电平,且在高速多目标认知探测场景下,相比于LFM波形、模糊函数优化波形和LFM-noise波形具有更好的高速目标探测能力。展开更多
R-DSP(Radar Digital Signal Processor)芯片中BSU(Branch Shift Unit)运算部件具有较大的设计规模和复杂度,传统Verilog验证平台难以满足其验证需求问题。针对该问题,文中采用UVM(Universal Verification Methodology)方法对BSU运算部...R-DSP(Radar Digital Signal Processor)芯片中BSU(Branch Shift Unit)运算部件具有较大的设计规模和复杂度,传统Verilog验证平台难以满足其验证需求问题。针对该问题,文中采用UVM(Universal Verification Methodology)方法对BSU运算部件进行功能验证。搭建基于SystemVerilog语言实现的UVM验证平台,使用定向测试和带约束的随机测试进行验证,并采用覆盖率驱动的方法指导测试用例的生成,以充分覆盖BSU运算部件的各个功能和代码路径。经过多轮测试激励验证,代码覆盖率接近100%,完成了对BSU运算部件的功能验证。所提方法为R-DSP芯片中的ALU(Arithmetic Logic Unit)、AGU(Address Generation Unit)、MU(Multiplication Unit)等运算部件的验证工作提供了参考和借鉴。展开更多
基金the National Natural Science Foundation of China (10572021 ,10372053)Basic Research Foundation of Beijing Institute of Tech-nology (BIT-UBF-200507A4206)
文摘A computational method of constraint stabilization and correction is introduced. The method is based on the Baumgart＇s one-step method. Constraint conditions are addressed to stabilize and correct the solution. Two examples are given to illustrate the results of the method.
文摘By redefining the multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, say, u2_i, i=1, 2, ..., m, nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed. For constructing the Lagrange neural network and Lagrange multiplier method, it is no longer necessary to convert inequality constraints into equality constraints by slack variables in order to reuse those results dedicated to equality constraints, and they can be similarly proved with minor modification. Utilizing this technique, a new type of Lagrange neural network and a new type of Lagrange multiplier method are devised, which both handle inequality constraints directly. Also, their stability and convergence are analyzed rigorously.
基金Supported by the Navy Equipment Department Foundation under Grant No. 2009(189)
文摘The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.
基金supported by the Fundamental Research Funds for the Central Universities(No.3122024QD06)。
文摘The novel aircraft engine-off taxi towing system featuring aircraft power integration has demonstrated significant advantages,including reduced energy consumption,diminished emissions,and enhanced efficiency.However,the aircraft engine-off taxi towing system lacks the consideration of attendant constraints in the trajectory generation process,which can potentially lead to ground accidents and constrain the improvement of traction speed.Addressing this challenge,the present work investigates the optimal control problem of trajectory generation for the taxiing traction system in the complex stochastic environment in the airport flight area.For the stochastic constraints,a strategy of deterministic processing is proposed to describe the stochastic constraints using random constraints.Furthermore,an adaptive pseudo-spectral method is introduced to transform the optimal control problem into a nonlinear programming problem,enabling its effective resolution.Simulation results substantiate that the generated trajectory can efficiently handle the stochastic constraints and accomplish the given task towards the time-optimization objective,thereby effectively enhancing the stability and efficiency of the taxiing traction system,ensuring the safety of the aircraft system,and improving the ground access capacity and efficiency of the airport.
文摘为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorithm,FPEA).该算法的繁殖算子是由Aitken加速的不动点迭代模型导出的二次多项式,其整体框架继承传统演化算法(如差分演化算法)基于种群的迭代模式.试验结果表明:在基准函数集CEC2014、CEC2019上,本文算法的最优值平均排名在所有比较算法中排名第1;在4个工程约束设计问题上,FPEA与CSA、GPE等多个算法相比,能以较少的计算开销获得最高的求解精度.
文摘现有全脉冲结构波形与处理方法,如相位编码波形匹配处理存在多普勒容忍度差的固有缺陷,线性调频(linear frequency modulation,LFM)波形加窗处理降低了距离分辨率和信噪比(signal-to-noise ratio,SNR)增益,难以适应高速多目标探测的任务需求。为此,本文提出了一种面向高速目标探测的多子脉冲结构波形设计与处理方法。首先,构建具有多子脉冲结构波形的回波模型,利用分段子脉冲压缩处理和子脉冲间相参处理方法,导出多子脉冲结构波形的距离-多普勒响应函数;然后,根据感兴趣的目标距离速度区间,建立恒模约束下以最小化加权积分距离-多普勒旁瓣电平为目标函数的多子脉冲结构波形优化设计问题;最后,引入坐标下降(coordinate descent,CD)优化框架,将高维非凸约束优化问题的求解转变为多个一维优化问题的迭代求解,且推导出这些低维问题的闭式解。仿真表明,所设计的多子脉冲结构波形具有较好的多普勒容忍度和较低的局部距离-多普勒旁瓣电平,且在高速多目标认知探测场景下,相比于LFM波形、模糊函数优化波形和LFM-noise波形具有更好的高速目标探测能力。
