基于粒子群优化的交叉口公交优先控制研究

以四相位单交叉口为研究对象,计算推导交叉口的延误计算模型,包括公交优先相位减少的延误以及非公交优先相位增加的延误。模型以减少人总延误最大为控制目标,采用粒子群算法优化求解,从而得到最优的绿信比,并通过仿真算例验证算法的有效性。     

电液负载模拟器的二次型最优控制算法

电液负载模拟器属于被动式加载系统,受载对象的自主运动和加载装置的运动相互耦合,所产生的位置扰动会引起多余力。为抑制多余力建立了电液负载模拟器的状态空间模型,利用线性二次型最优控制理论设计了最优控制算法,算法具有最优状态反馈、最优前馈补偿和外扰补偿,使得电液负载模拟器的性能有明显提高。电液负载模拟器的仿真计算结果表明,利用最优控制算法设计的电液负载模拟器较好地抑制了多余力,从而较好地跟踪力指令。     

State feedback control of continuous-time T-S fuzzy systems via switched fuzzy controllers

This paper studies the problem of state feedback control of continuous-time T-S fuzzy systems. Switched fuzzy controllers are exploited in the control design, which are switched based on the values of membership functions, and the control scheme is an extension of the parallel distributed compensation (PDC) scheme. Sufficient conditions for designing switched state feedback controllers are obtained with meeting an H_∞ norm bound requirement and quadratic D stability constraints. It is shown that the new control design method provides less conservative results than the corresponding ones via the parallel distributed compensation (PDC) scheme. A numerical example is given to illustrate the effectiveness of the proposed method.     

Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.      

Decentralised control of chromatographic simulated moving bed processes based on wave front reconstruction

The behaviour of chromatographic simulated moving bed processes is described by the movement of concentration profiles through a circle of separation columns. A closed-loop control manipulates the profiles in order to meet demands concerning specified product purity and disturbance attenuation. If steep wave fronts of the concentration profiles occur, the controlled variables undergo fast changes in case of a transient of the process. In this case, a reconstruction of the wave fronts is necessary for a successful control.A simple and effective decentralised controller structure is proposed based on cascaded discrete-time PI controllers. On-line product purity measurements and the reconstructed wave fronts are used for control purposes. Two kinds of process models are used: a rigorous model for dynamic simulations, and strongly simplified plant models for the design of the wave front reconstruction and the controller. The latter models are identified based on experimental step tests with the reference plant and numerical simulations. The performance of the control system is evaluated by numerical simulations.     

A generalized autocovariance least-squares method for Kalman filter tuning

This paper discusses a method for estimating noise covariances from process data. In linear stochastic state-space representations the true noise covariances are generally unknown in practical applications. Using estimated covariances a Kalman filter can be tuned in order to increase the accuracy of the state estimates. There is a linear relationship between covariances and autocovariance. Therefore, the covariance estimation problem can be stated as a least-squares problem, which can be solved as a symmetric semidefinite least-squares problem. This problem is convex and can be solved efficiently by interior-point methods. A numerical algorithm for solving the symmetric is able to handle systems with mutually correlated process noise and measurement noise.     

Design of observer based nonlinear model predictive controller for a continuous stirred tank reactor

Model predictive control (MPC) schemes are now widely used in process industries for the control of key unit operations. Linear model predictive control (LMPC) schemes which make use of linear dynamic model for prediction, limit their applicability to a narrow range of operation (or) to systems which exhibit mildly nonlinear dynamics.

In this paper, a nonlinear observer based model predictive controller (NMPC) for nonlinear system has been proposed. An approach to design NMPC based on fuzzy Kalman filter (FKF) and augmented state fuzzy Kalman filter (ASFKF) has been presented. The efficacy of the proposed NMPC schemes have been demonstrated by conducting simulation studies on the continuous stirred tank reactor (CSTR). The analysis of the extensive dynamic simulation studies revealed that, the NMPC schemes formulated produces satisfactory performance for both servo and regulatory problems. Simulation results also include an inferential control case, where the reactor concentration is not measured but estimated from temperature measurement and used in the NMPC based on FKF and ASFKF formulations.     

Web应用程序的用户非预期行为测试模型的研究

现有Web应用程序测试模型默认前提是将Web应用程序软件行为等同于其他传统软件,而忽略了Web应用程序中用户的非预期行为将可能影响软件应有的逻辑,导致软件行为失效,针对这一问题,本文在分析现有测试模型,测试策略与算法的基础上,提出一种基于扩展有限状态机(EFSM)的UUBTM测试模型来生成非预期行为的测试序列UTSEQ,实验证明该序列可以有效检测Web应用程序中存在的缺陷.     

Design and analysis of switching reduced-order observer and separation principle for T-S fuzzy system

This paper designs and analyzes switching fuzzy reduced-order observer and proves that the corresponding separation principle does hold. A numerical simulation and comparison with smooth fuzzy full-order observer are given to assess switching fuzzy reduced-order observer and the validity of the separation principles. Supported by the National Laboratory of Space Intelligent Control and Open Foundation (Grant No. SIC07010202), and the National Natural Science Foundation of China (Grant Nos. 60604010, 90716021, 60736023)     

广义时滞系统的降维观测器设计

讨论广义时滞系统的降维观测器的设计方法．通过引入矩阵的广义逆矩阵,给出在一定条件下降维观测器的具体形式,然后分别利用广义逆矩阵及Lyapunov函数方法给出这些条件成立的具体条件及验证方法。最后给出一个例子来说明方法的有效性。