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     

Minimum switching control for adaptive tracking

The switching adaptive control method has been used for quite a few years to solve the adaptive stabilization and model reference adaptive control problems. However, a serious problem with the switching control method is that the number of ‘candidate’ controllers can potentially be very large, especially for multi‐input–multi‐output systems. In this paper, we consider a class of minimum‐phase multi‐input–multi‐output plants with some mild compactness assumptions. Given any polynomial reference input, we provide a switching control law which guarantees exponentially stability of the closed‐loop system with exponential tracking performance. The main contribution of the paper is that we give the minimum number of candidate controllers required for switching. In particular, the number is equal to 2 for single‐input–single‐output plants (one for each sign of the high‐frequency gain), and is equal to 2^m for m‐input–m‐output plants. That is, the number is independent of the degree and the relative degree of the plant. Copyright © 2006 John Wiley & Sons, Ltd.     

A novel robust current control approach using adaptive line enhancer for three‐phase current‐source active power filter

An effective system control method is presented for applying a three‐phase current‐source PWM converter with a deadbeat controller to active power filters (APFs). In the shunt‐type configuration, the APF is controlled such that the current drawn by the APF from the utility is equal to the current harmonics and reactive current required for the load. To attain the time‐optimal response of the APF supply current, a two‐dimensional deadbeat control scheme is applied to APF current control. Furthermore, in order to cancel both the delay in the two‐dimensional deadbeat control scheme and the delay in DSP control strategy, an Adaptive Line Enhancer (ALE) is introduced in order to predict the desired value three sampling periods ahead. ALE has another function of bringing robustness to the deadbeat control system. Due to the ALE, settling time is made short in a transient state. On the other hand, total harmonic distortion (THD) of source currents can be minimized compared to the case where ideal identification of the controlled system can be made. The experimental results obtained from the DSP‐based APF are also reported. The compensating ability of this APF is very high in accuracy and responsiveness although the modulation frequency is rather low. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 50–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20014     

Process control: An overview and personal perspective

This paper presents an overview and personnal perspective on recent developments and current practice in computer process model. The basic concepts behind conventional process control are reviewed to provide a starting point for the non-control specialist and process engineer. The ensuing sections on Internal Model Control (IMC), Model Predictive Control (MPC) and adaptive control illustrate the evolution of control technology from the traditional multiloop strategies to the modern, multivariable, model-based, computer control systems now being used in industry. The paper does not provide a complete, critical review of process control. However, the discussion and the recommended references should provide a good starting point for anyone wanting to become familiar with current practice and some of the new directions of process control.     

Multivariable controller design in an adaptive control scheme

A multivariable control system design approach in the frequency domain is presented. The issue of control system redesign in an adaptive control scheme is discussed. Expert system techniques have been used for the automated design of controllers for multivariable systems. Design knowledge has been represented using rules, facts and objects. The design process consists of a sequence of operations obtained by heuristics and experience in the the design techniques. An automated design session of a multivariable plant using the expert system demonstrates that the expert system appears to work well in its prototype implementation.     

Pole shifting for matrices over real algebras

Pole shifting of multivariable control system over finite dimensional real algebras is studied. The main results are expressed in terms of the minimal polynomial of A + BF, where F is a feedback.     

Accidents,often the result of an ‘uncontrolled business process’—a study in the (Dutch) chemical industry

Often companies in the (petro‐) chemical industry claim that all possible countermeasures against potential accidents have been taken and therefore accidents are unforeseeable. In this paper we question this statement by analysing the pre‐warning signals (precursors) preceding a number of industrial accidents. 17 accidents that occurred in the (petro‐) chemical industry have been investigated by exploring FACTS, an accident database containing information about industrial accidents worldwide. This paper will demonstrate that the existence of precursor information could have been used to foresee and even prevent these accidents if a proper control action had been initiated. The accidents are analysed further, according to a control model, which was adapted from that of C. Argyris. It demonstrates the ineffectiveness of several elements of business process control loops and that the so‐called ‘double‐loop learning’ cycle is more important than the ‘single‐loop learning’ cycle if one considers safety improvement. Copyright © 2003 John Wiley & Sons, Ltd.