【正文】 alue) and small overshoot (almost invisible), but with a small steady error (not so smooth in a steady state). COMPARATWE STUDY OF FUZZY CONTROL FIGURE 2 The control effect of fuzzy control to the demo model. 3 PID CONTROL In the PID control, it is difficult to control VL and VS separately like the previous fuzzy control with a good control result, because the integration term of the PID control needs some time, and this will result in an oscillation when switching control signal between VL and VS. From this point of view the PID control is worse than the fuzzy control. Therefore, in our tests, VL and VS have to be controlled by the same signal. We use the following formula: By substitution, where U(I): control value to VL and VS at time r。 When D is small, we use FLC2 to control VS (finetuning). We choose D and DD as inputs of the fuzzy logic con troller, and VL or VS as the output of the fuzzy logic controller. D and DD must be fuzzified before fuzzy inference. Suppose the universes of discourse (or input variables39。 Ruan and van der Wal, 1998). In the framework of this project, we find that although there are already many fuzzy logic control applications, it is difficult to select the most sui table for testing and parison of our algorithms. Moreover, due to the safety regulations of the nuclear reactor, it is not realistic to perform many experiments in BRl. In this situation, we have to conduct part of the preprocessing experiments outside the reactor, ., parisons of different methods and the preliminary choices of the parameters. One solution is to make a simulation programme in a puter, but this has the disadvantage that in which, however, the real time property cannot be well reflected. Therefore another solution has adopted, that is, we designed and made a waterlevel control system, referred to as the demo model, which is suitable for our testing and experiments. In particular, this demo model (Fig. 1) is designed to simulate the power control principle of BRl (Li et al., 1996a,b。 Ruan and Li, 1997。 Matsuoka, 1990). The main reason is that it is impossible to do experiments in nuclear engineering as easily as in other industrial areas. For example, a reactor is usually not available to any individual. Even for specialists in nuclear engineering, an official licence for doing any online test is necessary. That is why we are still conducting projects such as fuzzy logic control application in BRl (the first nuclear reactor in Belgium) (Li and Ruan, 1997a。 Hah and Lee, 1994。 fuzzy adaptive control。附錄CONTROL, PID CONTROL, AND ADVANCED FUZZY CONTROL FOR SIMULATING A NUCLEAR REACTOR OPERATION XIAOZHONG LI and DA RUAN* elgian Nuclear Research Centre (SCKoCENBoeretang 200, 82400 Mol, Belgium (Received 15 March 1999) Based on the background of fuzzy control applications to the first nuclear reactor in Belgium (BRI) at the Belgian Nuclear Research Centre (), we have made a real fuzzy logic control demo model. The demo model is suitable for us to test and pare some new algorithms of fuzzy control and intelligent systems, which is advantageous because it is always difficult and timeconsuming, due to safety aspects, to do all experiments in a real nuclear environment. In this paper, we first report briefly on the construction of the demo model, and then introduce the results of a fuzzy control, a proportionalintegralderivative (PID) control and an advanced fuzzy control, in which the advanced fuzzy control is a fuzzy control with an adaptive function that can Selfregulate the fuzzy control rules. Afterwards, we present a parative study of those three methods. The results have shown that fuzzy control has more advantages in terms of flexibility, robustness, and easily updated facilities with respect to the PID control of the demo model, but that PID control has much higher regulation resolution due to its integration term. The adaptive fuzzy control can dynamically adjust the rule base,therefore it is more robust and suitable to those very uncertain occasions.Keywords: Fuzzy control。 PID control。 nuclear reactor I INTRODUCTION Today the techniques of fuzzy logic control are very mature in most engineering areas, but not in nuclear engineering, though some research has been done (Bernard, 1988。 Lin et al. 1997。 Ruan, 1995。 1998。 Li and Ruan, 1997b). In this demo model, our goal was to control the water level in tower TI at a desired level by means of tuning VL (the valve for large control tower T2) and VS (the valve for small control tower T3). The pump keeps on working to supply water to T2 and T3. All taps are for manual tuning at this time. VI and V2 valves are used to control the water levels in T2 and T3 respectively. For example, when the water level in T2 is lower than photoelectric switch sensor 1 then the onoff valve V, will be opened (on), and when the water level in T2 is higher than photoelectric switch sensor 2 then the onoff valve Vl will be closed (off). The same is true of V2. Only when both VI and V2 are closed V3 will be opened, because it can decrease the pressure of the pump and thereby prolong its working life. The pressure sensor is used to detect the height of water level in TI. So for TI, it is a dynamic system with two entrances and one exit for water flow. COMPARATIVE STUDY OF FUZZY CONTROL The Demo Model Structure FIGURE 1 The working principle of the demo model. BRI is a 42year old research reactor, in which the control method is the simple onoff method. Many methods called traditional meth