Two-level optimal output feedback stabilizer design

The paper addresses the design of two-level power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interactions. The effectiveness of this controller is evaluated and a multimachine system is given as an example to illustrate the advantages of the proposed method. Responses of the system with a two-level scheme and an optimal reduced order scheme are included for comparative analysis.     

化工企业环境因素的评价

化工企业环境因素评价是建立环境管理体系的核心任务，化工企业生产过程的特点决定了其环境因素数量多、环境影响大、识别评价难、控制难度大。本文介绍了化工企业环境因素评价的技术方法和过程，可以为提高环境因素评价的科学性、客观性和充分性提供参考。     

煤矿矿井水检测质量控制措施探讨

探讨了影响煤矿矿井水检测质量的主要因素,按照全过程、全要素控制的理念提出了检测前、检测中和检测后的控制措施。     

肝单光子发射计算机断层若干物理因素的讨论

我们于1985年对我院1984年开展肝单光子发射计算机断层以来的52例肝病人进行了分析总结。结果表明,肝单光子发射断层在诊断肝内占位性病变方面比普通肝静态γ照相有许多优点。需要指出的是,肝单光予发射断层的若干优点及诊断的准确性是与物理条件的正确选择和应用密切相关的。本文根据至今积累的近100例断层经验,从技术方面介绍了影响单     

A stochastic maximum principle for systems with jumps, with applications to finance

We consider a stochastic control problem with linear dynamics with jumps, convex cost criterion, and convex state constraint, in which the control enters the drift, the diffusion, and the jump coefficients. We allow these coefficients to be random, and do not impose any L^p-bounds on the control.

We obtain a stochastic maximum principle for this model that provides both necessary and sufficient conditions of optimality. This is the first version of the stochastic maximum principle that covers the consumption–investment problem in which there are jumps in the price system.     

Lyapunov‐stable discrete‐time model reference adaptive control

Discrete‐time model reference adaptive control (MRAC) is considered with both least squares and projection algorithm parameter identification. For both cases complete Lyapunov proofs are given for stability and convergence. The results extend the approach of Johansson (Int. J. Control 1989; 50 (3):859–869) to include Lyapunov stability for MRAC when the normalized projection algorithm is used for parameter identification. Copyright © 2005 John Wiley & Sons, Ltd.     

Quantitative evaluation of generator power control effect of FACTS controllers for power system stabilization

The advancement of power electronics technologies has significantly developed the power system stabilizing controllers. Quantitative as well as qualitative evaluation of their effectiveness in power systems is a matter of great importance for the feasibility investigation of these apparatus. In this paper, the possible control region of FACTS controllers with series and/or shunt configuration in a single machine to infinite bus system is formulated in the powerangle curve with a set of algebraic equations. The effectiveness of TCPST (Thyristor‐Controlled Phase Shifting Transformer), SSSC (Static Synchronous Series Compensator), and TCSC (Thyristor‐Controlled Series Compensator) for the improvement of the transient stability is evaluated quantitatively as a numerical example. The correctness of the proposed method has been confirmed by analysis based on the electromagnetic transients simulation with a detailed system model. © 2001 Scripta Technica, Electr Eng Jpn, 138(3): 43–51, 2002     

Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

Sensorless control of synchronous reluctance motors using on‐line parameter identification method not affected by position estimation accuracy

This paper presents a novel on‐line parameter identification method for sensorless control of Synchronous Reluctance Motors (SynRMs). Although conventional sensorless control methods based on mathematical models usually need some complex measurements of motor parameters in advance, the proposed identification method does not require them and can be realized on‐line. The proposed method identifies motor parameters under sensorless control, so rotor position and velocity cannot be used to identify these parameters. However, the proposed method does not need rotor position and velocity, and identified parameters are not affected by these estimation errors. The sensorless control using identified motor parameters is realized, and the effectiveness of the proposed method is verified by experimental results. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(3): 62–69, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20258