温度测控技术在中药加速仪中的应用

本文介绍了中药加速仪利用单片机和热敏电阻设计低成本温度测控系统的一种温度测量比值查表方法和温度脉冲加热控制法,并对硬件系统原理和软件设计流程作了简要描述。     

Local multi-valued logics in modular expert systems

Abstract

Abstract. In this paper we describe an approach to the problem of dealing with uncertainty by means of finite multi-valued logics in modular expert systems, and the results obtained. The modularity of the systems allows us to address two main characteristics of human problem-solving: the adaptation of general knowledge to particular problems and the dependency of the management of uncertainty on the different subtasks being implemented in the modules of the system, i.e. different modules can have different local multiple-valued logics as part of their local deductive mechanisms. Although the results obtained are general, we use, throughout the paper, examples of a medical expert system that has been designed using a modular language called MILORD-II, that implements them showing the practical interest of the theoretical concepts involved.     

Some results on the improvement of adaptation transients

A technique to improve the adaptation transient in discrete-time model reference adaptive control (MRAC) systems is given on the basis of applying classical optimization techniques to an equivalent near-linear system to the whole adaptive scheme. The resulting optimization is finally translated into modifications of one of the parameters entering the adaptation algorithm. This permits computation of a posteriori values of the adaptive controller parameters before generation of the input to the plant.     

Compensation of uncertain continuous systems by using the internal model control principle

In this paper the design of compensators for uncertain continuous plants is investigated. The standard derived compensators are based on the application of the internal model control (IMC) method. The required a priori knowledge on the plant is rather weak, namely, an upper bound of the plant relative order, the numbers of the strictly unstable and critically unstable plant poles being integrators and upper and lower bounds of the amplitude-versus-frequency plot over the low frequency band in the case of minimum-phase open-loop systems. If the open-loop system has unstable zeros and/or poles then the above bounds are required to be known for a modified magnitude plot which substitutes the unstable zeros (poles) by stable poles (zeros) which are their complex-conjugate reflections on the left-hand plane. An absolute upper bound of the open-loop phase plot is obtained on a finite frequency interval which allows the closed-loop system to guarantee a prescribed relative stability in many practical situations. The method is dependent on the alternative design of phase lead/lag classical compensators and to indirect adaptive control situations where the adaptive identifier is used for the parametrization of the adaptive controller.     

Matrix formulae for open and closed-loop approximate model matching in frequency domain

This paper concerns model matching of SISO systems in the frequency domain. The matching uses Pade coefficients and Markov parameters of a reference model of which the final system will be an approximation. Because the matching is approximate, constraints on the structures of both the reference model and the final system can be somewhat relaxed. In this paper an easy-to-implement matrix formulation is derived for both open- and closed-loop matching problems. Some results concerning pole-zero cancellations are presented, along with a number of numerical examples provided to illustrate the usefulness and simplicity of the approach.     

Continuous mobile robot localization by using structured light and a geometric map

A mobile robot needs to know its position and orientation with accuracy in order to decide the control actions that permit it to finish the entrusted tasks successfully. To obtain this information, dead-reckoning-based systems have been used, and more recently inertial navigation systems. However, these systems have some errors that grow bigger as time goes by, therefore a moment comes when the information provided is useless. Because of this, there should be a periodic process that updates the robot position and orientation of the vehicle. The process to determine the robot position and orientation by using information originated from the external sensors is defined as the mobile robot relocalization. It is obvious that the greater the frequency of this process, the better the knowledge of its position the robot will have, and therefore its movements will be better directed to the point it must reach. The algorithm to achieve this can be classified in two large groups: relocalization through an a priori map of the environment and relocalization through the detection of landmarks present in that environment. The algorithm presented in the paper belongs to the first case. The sensor used is a combination of a laser diode and a CCD camera. The sensorial information is modelled as straight lines that will be matched with an a priori map of the environment. With this, the position of the mobile robot is estimated. The matching process is accomplished within an extended Kalman filter. The algorithm is able to work in real time, and it actualizes the position of the robot in a continuous way.     

Application of iterative suboptimal strategies for improving adaptation transients in adaptive systems

Some solutions which involve iterative optimization techniques are given to improve adaptation transients in adaptive systems. Two suboptimal controllers are developed and applied to an equivalent discrete-time system valid for describing the behaviour of a recent adaptive control scheme when one of the (time-varying) parameters entering the adaptation algorithm varies within a closed domain admissible from a convergence point of view. The resulting suboptimal control strategies are translated into corrections of this parameter in order to recompute the adaptation algorithm over a finite horizon. Some numerical simulations illustrate the usefulness of the proposed scheme.     

Min-max optimal instrumental variable estimation method for multivariate linear time-series systems

A min-max optimal instrumental variable (IV) estimation method for multivariate linear time-series systems is presented. A Monte Carlo study is performed to assess the merits of the min-max optimal IV method using two different parametrizations of the multivariate time series system. The analysis indicates that the proposed estimation method yields accurate estimation results at modest computational cost.