设计了一款应用于有源相控阵雷达T/R组件的X波段功率放大器,放大器采用单端两级放大的共源共栅结构,包括输入与输出匹配网络,偏置电路采用自适应线性化技术,实现高增益和高线性的输出。基于IBM 0.18μm Si Ge Bi CMOS 7WL工艺流片,测试...设计了一款应用于有源相控阵雷达T/R组件的X波段功率放大器,放大器采用单端两级放大的共源共栅结构,包括输入与输出匹配网络,偏置电路采用自适应线性化技术,实现高增益和高线性的输出。基于IBM 0.18μm Si Ge Bi CMOS 7WL工艺流片,测试结果表明,在3.3 V电源电压下,在8.5 GHz时增益为21.8 d B,1 d B压缩点输出功率为10.4 d Bm,输入输出匹配良好,芯片面积为1.4 mm×0.8 mm。芯片面积较小,实现了与整个T/R芯片的集成。展开更多
In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonli...In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonlinear systems, direct adaptive control schemes are presented to achieve bounded tracking. The proposed control schemes are robust with respect to the uncertainties in interconnection structure as well as subsystem dynamics. A numerical example is given to illustrate the efficiency of this method.展开更多
This paper discusses causes of the rate ripple in inertia guidance test equipment IGET, systematically analyses their effects an the rate ripple in IGTE. The analysis result shows： The rate ripple caused by the perio...This paper discusses causes of the rate ripple in inertia guidance test equipment IGET, systematically analyses their effects an the rate ripple in IGTE. The analysis result shows： The rate ripple caused by the periodic errors of inductosyn and angular encoder is higher at high speed than that caused by magnetic ripple torque and friction torque, and it cannot be eliminated by adjusting control parameters of the system. And based on the nonlinear adaptive control system theory, the paper puts forward a new control system scheme to eliminate the rate ripple caused by the periodic errors of inductosyn and angular encoder, develops the adaptive control rules and makes simulation and test. Experimental result shows a significant improvement on those tables for the period disturbs under the system scheme designed. By this plan, with the input of rate 200°/s, the rate ripple falls from 5°/s to 0. 4°/s within about 6s adaptive adjustment time, being a twelfth of before adaptation, which can not be reached by common classical controls. The experimental results conform with the simulation, which proves the validity and practicability of the plan.展开更多
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa...In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.展开更多
Aiming at the unsatisfactory dynamic performances of conventional model predictive control (MPC) in a highly nonlinear process, a scheme employed the fuzzy neural network to realize the nonlinear process is proposed. ...Aiming at the unsatisfactory dynamic performances of conventional model predictive control (MPC) in a highly nonlinear process, a scheme employed the fuzzy neural network to realize the nonlinear process is proposed. The neuro-fuzzy predictor has the capability of achieving high predictive accuracy due to its nonlinear mapping and interpolation features, and adaptively updating network parameters by a learning procedure to reduce the model errors caused by changes of the process under control. To cope with the difficult problem of nonlinear optimization, Pepanaqi method was applied to search the optimal or suboptimal solution. Comparisons were made among the objective function values of alternatives in initial space. The search was then confined to shrink the smaller region according to results of comparisons. The convergent point was finally approached to be considered as the optimal or suboptimal solution. Experimental results of the neuro-fuzzy predictive control for drier application reveal that the proposed control scheme has less tracking errors and can smooth control actions, which is applicable to changes of drying condition.展开更多
This work presents two different methods-nonlinear control method and adaptive control approach to achieve the modified projective synchronization of a new hyperchaotic system with known or unknown parameters.Based on...This work presents two different methods-nonlinear control method and adaptive control approach to achieve the modified projective synchronization of a new hyperchaotic system with known or unknown parameters.Based on Lyapunov stability theory,nonlinear control method is adopted when the parameters of driving and response systems are known beforehand;when the parameters are fully unknown,adaptive controllers and parameters update laws are proposed to synchronize two different hyperchaotic system and identify the unknown parameters.Moreover,the rate of synchronization can be regulated by adjusting the control gains designed in the controllers.The corresponding simulations are exploited to demonstrate the effectiveness of the proposed two methods.展开更多
文摘研究了将自适应局部线性化方法应用于较强余震间隔时间的预测。首先对余震间隔时间数据进行预处理;再利用自适应局部线性化法找出合适的嵌入维数,并计算出待估计参数。最后用待估计参数预测余震间隔时间。对汶川地震发生后4.0级(含4.0级)以上的余震间隔时间数据进行了预测。实验结果表明,自适应局部线性化方法预测的余震间隔时间的平均均方根误差和平均绝对偏离明显低于标准局部线性化方法;自适应局部线性化方法预测的余震间隔时间绝对误差比标准局部线性化方法和最小二乘拟合方法的预测结果分别减少了7 d和20 d.
文摘设计了一款应用于有源相控阵雷达T/R组件的X波段功率放大器,放大器采用单端两级放大的共源共栅结构,包括输入与输出匹配网络,偏置电路采用自适应线性化技术,实现高增益和高线性的输出。基于IBM 0.18μm Si Ge Bi CMOS 7WL工艺流片,测试结果表明,在3.3 V电源电压下,在8.5 GHz时增益为21.8 d B,1 d B压缩点输出功率为10.4 d Bm,输入输出匹配良好,芯片面积为1.4 mm×0.8 mm。芯片面积较小,实现了与整个T/R芯片的集成。
文摘In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonlinear systems, direct adaptive control schemes are presented to achieve bounded tracking. The proposed control schemes are robust with respect to the uncertainties in interconnection structure as well as subsystem dynamics. A numerical example is given to illustrate the efficiency of this method.
文摘This paper discusses causes of the rate ripple in inertia guidance test equipment IGET, systematically analyses their effects an the rate ripple in IGTE. The analysis result shows： The rate ripple caused by the periodic errors of inductosyn and angular encoder is higher at high speed than that caused by magnetic ripple torque and friction torque, and it cannot be eliminated by adjusting control parameters of the system. And based on the nonlinear adaptive control system theory, the paper puts forward a new control system scheme to eliminate the rate ripple caused by the periodic errors of inductosyn and angular encoder, develops the adaptive control rules and makes simulation and test. Experimental result shows a significant improvement on those tables for the period disturbs under the system scheme designed. By this plan, with the input of rate 200°/s, the rate ripple falls from 5°/s to 0. 4°/s within about 6s adaptive adjustment time, being a twelfth of before adaptation, which can not be reached by common classical controls. The experimental results conform with the simulation, which proves the validity and practicability of the plan.
基金Supported by the Major State Basic Research Development Program of China (2012CB720500)the National Natural Science Foundation of China (Key Program: U1162202)+1 种基金the National Natural Science Foundation of China (General Program:61174118)Shanghai Leading Academic Discipline Project (B504)
文摘In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
基金Sponsored by the National Electric Power Corporation Foundation of China(Grant No.SPKJ010-27)
文摘Aiming at the unsatisfactory dynamic performances of conventional model predictive control (MPC) in a highly nonlinear process, a scheme employed the fuzzy neural network to realize the nonlinear process is proposed. The neuro-fuzzy predictor has the capability of achieving high predictive accuracy due to its nonlinear mapping and interpolation features, and adaptively updating network parameters by a learning procedure to reduce the model errors caused by changes of the process under control. To cope with the difficult problem of nonlinear optimization, Pepanaqi method was applied to search the optimal or suboptimal solution. Comparisons were made among the objective function values of alternatives in initial space. The search was then confined to shrink the smaller region according to results of comparisons. The convergent point was finally approached to be considered as the optimal or suboptimal solution. Experimental results of the neuro-fuzzy predictive control for drier application reveal that the proposed control scheme has less tracking errors and can smooth control actions, which is applicable to changes of drying condition.
基金National Natural Science Foundation of China(No.60874113)
文摘This work presents two different methods-nonlinear control method and adaptive control approach to achieve the modified projective synchronization of a new hyperchaotic system with known or unknown parameters.Based on Lyapunov stability theory,nonlinear control method is adopted when the parameters of driving and response systems are known beforehand;when the parameters are fully unknown,adaptive controllers and parameters update laws are proposed to synchronize two different hyperchaotic system and identify the unknown parameters.Moreover,the rate of synchronization can be regulated by adjusting the control gains designed in the controllers.The corresponding simulations are exploited to demonstrate the effectiveness of the proposed two methods.
