An efficient bi-objective optimization framework for statistical chip-level yield analysis under parameter variations

With shrinking technology, the increase in variability of process, voltage, and temperature (PVT) parameters significantly impacts the yield analysis and optimization for chip designs. Previous yield estimation algorithms have been limited to predicting either timing or power yield. However, neglecting the correlation between power and delay will result in significant yield loss. Most of these approaches also suffer from high computational complexity and long runtime. We suggest a novel bi-objective optimization framework based on Chebyshev affine arithmetic (CAA) and the adaptive weighted sum (AWS) method. Both power and timing yield are set as objective functions in this framework. The two objectives are optimized simultaneously to maintain the correlation between them. The proposed method first predicts the guaranteed probability bounds for leakage and delay distributions under the assumption of arbitrary correlations. Then a power-delay bi-objective optimization model is formulated by computation of cumulative distribution function (CDF) bounds. Finally, the AWS method is applied for power-delay optimization to generate a well-distributed set of Pareto-optimal solutions. Experimental results on ISCAS benchmark circuits show that the proposed bi-objective framework is capable of providing sufficient trade-off information between power and timing yield.     

非一致性条件下城市设计洪水的计算方法

在分析城市化后产流变化的基础上,可采用平均洪量模数增量修正设计洪峰频率曲线的均值,进而推算城市化后的设计洪峰流量,以宝象河流域为实例进行了验证。结果表明:该算法具有合理性,以实测洪水资料为基础进行的非一致性条件下的设计洪水计算结果比基于设计暴雨推求设计洪水的误差更小。     

仙居抽水蓄能电站下水库事故闸门井深井开挖技术

仙居抽水蓄能电站下水库泄放洞事故闸门井开挖施工作业面狭窄、安全隐患大,经方案比选,采用"先导井后扩挖"方式进行开挖。其中导井开挖采用VCR法,具有作业安全、施工进度快、爆破成型效果好等优点,取得了较好的经济效益。     

基于河道径流可变区间的河流水资源可开发利用率分析

为了确定水电开发活动对河流水资源的可开发利用率,建立分期展布的河道径流可变区间核算方法,其中河道径流包括河道最小生态需水和河道最大洪流,并以西藏拉萨河为例进行核算。结果表明:拉萨河河道最小生态需水和最大洪流年内动态变化分别为29.5~328.3 m3/s和95.1~1 673.4 m3/s。与河道最小生态需水约束相比,河道径流可变区间约束使得拉萨河年调节型水电开发的水资源可开发利用率从60.2%下降到18.7%。指出对于径流丰枯特征十分明显的季节性河流,大型水利工程在平衡径流季节分布的过程中,应该受河道径流可变区间约束,尤其是枯水期最大洪流约束下河道径流量的可增加空间。     

Optimal Terminal Iterative Learning Control for the Automatic Train Stop System

The train stop control is a typical set‐point control task, where only the final state (i.e., the terminal train stop position) is of concern and specified. For such a control problem, an optimal terminal iterative learning control (TILC) approach is presented in this paper, where the stopping position and initial braking speed are chosen as the terminal system output and the control input, respectively. The controller design only depends on the measured input/output (I/O) data without requiring any modeling information of the train operation system, and the learning gain is updated by the system I/O data iteratively to accommodate the system uncertainties. The monotonic convergence of the terminal tracking error is guaranteed by rigorous mathematical analysis. Extensive simulation results are provided to show the applicability and effectiveness of the proposed approach.     

Synchronization of Instantaneous Coupled Harmonic Oscillators With Communication and Input Delays

This paper investigates the synchronization issue of instantaneous coupled harmonic oscillators with communication and input delays. A distributed synchronization algorithm is proposed for such oscillator systems, and some general algebraic criteria on exponential convergence are established for the algorithm. The main contributions of the present investigations include: (i) the directed network topology is first considered in the case of instantaneous interaction; (ii) both the time‐varying communication and input delays are simultaneously addressed; (iii) the effects of communication and input delays on synchronization performance of coupled harmonic oscillators are discussed. It is shown the communication delays have a more important impact than the input delays on determining synchronization dynamics of coupled harmonic oscillators. Explicitly, in absence of communication delays, coupled harmonic oscillators can achieve synchronization oscillatory motion, whereas, so long as communication delays are nonzero at infinite multiple impulsive times, its synchronization (or consensus) state is zero. Finally, numerical examples demonstrate the obtained theoretical results.     

An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach

In this paper, we propose an actor-critic neuro-control for a class of continuous-time nonlinear systems under nonlinear abrupt faults, which is combined with an adaptive fault diagnosis observer (AFDO). Together with its estimation laws, an AFDO scheme, which estimates the faults in real time, is designed based on Lyapunov analysis. Then, based on the designed AFDO, a fault tolerant actor- critic control scheme is proposed where the critic neural network (NN) is used to approximate the value function and the actor NN updates the fault tolerant policy based on the approximated value function in the critic NN. The weight update laws for critic NN and actor NN are designed using the gradient descent method. By Lyapunov analysis, we prove the uniform ultimately boundedness (UUB) of all the states, their estimation errors, and NN weights of the fault tolerant system under the unpredictable faults. Finally, we verify the effectiveness of the proposed method through numerical simulations.