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| 1 | SOFT SENSING MODEL BASED ON SUPPORT VECTOR MACHINE AND ITS APPLICATION显示文摘Soft sensor is widely used in industrial process control.It plays an important role to improve the quality of product and assure safety in production.The core of soft sensor is to construct soft sensing model.A new soft sensing modeling method based on support vector machine (SVM) is proposed.SVM is a new machine learning method based on statistical learning theory and is powerful for the problem characterized by small sample, nonlinearity, high dimension and local minima.The proposed methods are applied to the estimation of frozen point of light diesel oil in distillation column.The estimated outputs of soft sensing model based on SVM match the real values of frozen point and follow varying trend of frozen point very well.Experiment results show that SVM provides a new effective method for soft sensing modeling and has promising application in industrial process applications. | YanWeiwu ShaoHuihe WangXiaofan | 2004 | Chinese Journal of Mechanical Engineering2004，17，1： | 3 |
| 2 | Drifting model approach to modeling based on weighted support vector machines显示文摘This paper proposes a novel drifting modeling (DM) method. Briefly, we first employ an improved SVMs algorithm named weighted support vector machines (W.SVMs), which is suitable for locally learning, and then the DM method using the algorithm is proposed. By applying the proposed modeling method to Fluidized Catalytic Cracking Unit (FCCU), the simulation results show that the property of this proposed approach is superior to global modeling method based on standard SVMs. | FengRui SongChunlin ShaoHuihe | 2004 | Journal of Systems Engineering and Electronics2004，15，4： | 1 |
| 3 | Nonlinear fault diagnosis method based on kernel principal component analysis显示文摘To ensure the system run under working order, detection and diagnosis of faults play an important role in industrial process. This paper proposed a nonlinear fault diagnosis method based on kernel principal component analysis (KPCA). In proposed method, using essential information of nonlinear system extracted by KPCA, we constructed KPCA model of nonlinear system under normal working condition. Then new data were projected onto the KPCA model. When new data are incompatible with the KPCA model, it can be concluded that the nonlinear system isout of normal working condition. Proposed method was applied to fault diagnosison rolling bearings. Simulation results show proposed method provides an effective method for fault detection and diagnosis of nonlinear system. | 阎威武 ZhangChunkai ShaoHuihe | 2005 | High Technology Letters2005，11，2： | 1 |
| 4 | SoftsensingofFCCUreactionconversionandyieldswithmechanismanalysis[J]显示文摘 | LuoChenzhong(路晨钟) WuJunsheng(吴俊生) ShaoHuihe(邵惠鹤) | | 化工自动化及仪表0，，： | 1 |
| 5 | Robust stability analysis of uncertain discrete-time systems with state delay显示文摘The sufficient conditions of stability for uncertain discrete-time systems with state delay have been proposed by some researchers in the past few years, yet these results may be conservative in application. The stability analysis of these systems is discussed, and the necessary and sufficient condition of stability is derived by method other than constructing Lyapunov function and solving Riccati inequality. The root locations of system characteristic polynomial, which is obtained by augmentation approach and Laplace expansion, determine the stability of uncertain discrete-time systems with state delay, the system is stable if and only if all roots lie within the unit circle. In order to analyze robust stability of system characteristic polynomial effectively, Kharitonov theorem and edge theorem are applied. Example shows the practicability of these methods. | RenZhengyun ZhangLiqun ShaoHuihe | 2004 | Journal of Systems Engineering and Electronics2004，15，2： | 0 |
| 6 | Optimal closed-loop identification test design for internal model control显示文摘In this paper, optimal closed-loop test design for control is studied. The identified model is used for controller design. The control scheme used is internal model control (IMC) and the design constraint is the power of the process output or that of the reference signal. The measure of performance is the variance of the error between the output of the ideal closed-loop system (with the ideal controller) and that of the actual closed-loop system (with the controller computed from the identified model). Optimal spectrum formulae can be used to determine the PRBS signal in industrious identification. | ZhangLiqun ShaoHuihe DaiDan | 2004 | Journal of Systems Engineering and Electronics2004，15，4： | 0 |
| 7 | Traffic control based on dahlin algorithm and neural network prediction in TAM networks显示文摘The propagation delay in networks has a great adverse effect on rote-based traffic control. This paper proposes the composite control based on Dahlin algorithm feedback control and neural network feedforward predictive compensation online for ABR (available bit rate) communication in ATM (asynchronous transfer mode) networks, which can overcome the adverse effect caused by the delay on the control rapidity and stability better. The theoretical analysis and simulation research show that the scheme can make sources respond to the changes of network status rapidly, avoid the congestion effectively and utilize the bandwidth sufficiently. Compared with PID (proportional-integral-derivative) control, cell loss rate is much lower, link utilization rate is much higher, and required buffer capacity is much smaller. | ShenWei FengRui ShaoHuihe | 2004 | Journal of Systems Engineering and Electronics2004，15，4： | 0 |
| 8 | Predictive PI control and its robust stability analysis显示文摘It is difficult to analyze robust BIBO stability of predictive PI (PPI) control system due to the time delay of process. A novel technique for stability analysis of this kind of system is proposed in this paper. The state space form of PPI control system is given, and its characteristic polynomial is derived by a simple method, so the robust BIBO stability analysis of this kind of system is also the analysis of corresponding characteristic polynomial. Applying Kharitonov theorem and edge theorem, the BIBO stability can be judged for arbitrarily given process parameter intervals. The system robust stability with variable process parameters is described respectively, and some beneficial conclusions for the design of PPI controller are obtained. | RenZhengyun ZhangHong ShaoHuihe | 2005 | High Technology Letters2005，11，1： | 0 |
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