実用的な自己調整付系を開発した.この制御系は, 下層にフィードフォワード・フィードバック器のアルゴリズムと上層には制御性能を評価し, フィードフォワード器のゲインを自己調整する学習アルゴリズムから成る階層構造を持っている.この自己調整器は, フィードフォワード・フィードバック器のそれぞれからの操作量トレンドを比較する学習ルールによりフィードバック器のゲインを適度に調整する.
この系の有効性を確認するためエチレン装置の脱メタン塔に適用した.その結果, いまだうまく制御ができていなかった塔底温度系に対して, 有効であることがわかった.

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Recently fuzzy control has been recognized to be of great usefulness in many engineering fields. However, the adjustment of fuzzy control parameters such as control rules, membership functions has been carried out by trial and error, and the definite design method of fuzzy control systems has not been established yet. In this paper, the influences of fuzzy inference methods on control performances have been examined by the simulations of a first order lag system with dead time. Moreover, the improvement of control performances in case of low-dimensional number of fuzzy labelings has been tried. Main results are as follows : (1)When the number of fuzzy labelings is low-dimension such as 3×3 divisions, control performances are dependent on fuzzy inference methods. Therefore, in case of low-dimensional number of fuzzy labelings, the selection of fuzzy inference methods is important. (2) Even in case of low-dimensional number of fuzzy labelings such as 3×3 divisions, by using the simple method of changing the height of the consequent membership function ZO, the non-linear characteristic of a fuzzy controller can be tuned and its control performances can be improved.

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In recent years, the fuzzy control method has been applied in many practical fields with the development of computer technology. In these applications, it is freqently pointed out that fuzzy control is effective especially for complex or nonlinear systems. This study deals with a hydraulic servo system based on fuzzy reasoning, for the purpose of investigating the applicability of the fuzzy control method. The hydraulic servo system analyzed in this study is one which is composed of a 4-way spool valve and a load cylinder. As a result of experiment and simulation, it was confirmed that the control method could be applied with high accuracy along with high-speed response, in a region of considerably wide system parameters.

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In this study, the temperature control system of an incandescent lamp is used. This system consists of a thermistor, multimeter, microcomputer, D/A converter, variable AC power supply and incandescent lamp. This system is a nonlinear and a first-order lagsystem. Therefore, it is very difficult to control smoothly the system. To cope with this problem, a newly developed fuzzy control is applied. This controller consists of the modules of the fuzzy calculator, the scale's optimizer and the scale's selector. The effectiveness of this method is confirmed and influence on the tuning of the scale of the fuzzy's membership functions according to the environment adaptable-type fuzzy control is examined.

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以上,,ニューロ制御を例に最近の知的制御技術について述べた。
すなわち,制御は万能ではなく,その働きは,機械の本来もつ性能を最大限発揮させるために,それぞれの制御対象がもつ特徴を最大限生かす使い方にある。
は,定性的に性能改善ができることが分かりながら,カテゴリーが異なるため利用できない規則も取り込むことができ,これからも,種々の使い方が期待できる。
ニューロ制御は形状のようなパターンを,パターンの成分量のような,に適用できるスカラー量に変換できるようになり,制御にも新しい側面が生まれた。

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In this study, the continuous and fixed quantity control system that supplies powder in the fine-chemical industry is used. This system consists of a motor, measuring feeder, loadcell, amplifier and controller. This system is the first-order lag system and is controlled by the PI control system formerly. However, it is very difficult to suppress the vibration of the discharged weight's velocity. To cope with this problem, a newly developed fuzzy control is applied. The effectiveness of this method is confirmed and the influence on the dynamic characteristics of the variable-type fuzzy conorol, that transfoms the membership functions by the discharged weight's velocity is examined.

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を用いて制御器を構築する場合に, 規則が制御器に与える影響は大きく, 制御器に合った規則を用いなければ, の結果とその望ましい出力との間の誤差が生じてしまう.器から生じる誤差を低減する方法の一つとして, 規則を修正する方法がある.その際, 試行錯誤を操り返し最適な制御を行なうことができる規則を求めている場合が多い.本論文では, 発生する誤差に着目し, その誤差情報を使って規則の修正量を推定する方法を述べる.器を2つ用いてそれぞれに違う規則の修正量で制御を行う.修正量に対する二乗誤差を比較し, 誤差の小さい規則の修正量とする.出力用制御器と比較するための制御器の規則の修正量は乱数で与える.二乗誤差を比較しながらファジィ規則修正量を選ぶ処理を繰り返すことにより, 誤差の小さい規則の修正量を推定することが可能となる.本論文のシミュレーションでは, 最初にインディシャル応答を求め, 定値制御に規則の修正が有効であることを明らかにする.次に追従制御に規則の修正が有効であることを示す.そして, 追従制御の目的信号の変化として固定された周波数の正弦波を用いる場合に位相ずれの誤差の低減が可能であることを確かめる.また目的信号の変化の方向が徐々に変化する正弦波ではなく, 一定値で増加や減少する場合や, 変化の方向が大きく変化する三角波を用いる場合も誤差の低減が可能であることを確かめる.

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A stochastic fuzzy control method is used to construct a robust servo controller that can remove a steady-state tracking error. The present method is applied to the position control problem of a prismatic link, where the position is assumed to be measured by using a linear potentiometer with a mesurement noise. It is shown from some computer simulations that although the pressent controller basically consists of 1-type servo structure, it is very robust against not only a time-varying distrubance but also random noise, compared to a conventional robust controller.

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Recent studies on an improvement of fuzzy controls have shown that fuzzy variables in the antecedent had better exist successively. Then, fuzzy control rules will act mutually and continuously according to the change of the input data. Therefore, the rules had better not leave a blank to all combination of the fuzzy variables. In order to cope with increasing the number of rules, it becomes necessary to contract fuzzy control rules without changing the original control.
The present method defines the “and” conjunction of the antecedent not with the minimum operation but with the product of the grades of the input data. As the result, fuzzy control rules will cover a wider area respectively.
We apply this technique to the control of a tobacco dryer. The fuzzy PD controller in feedback control is represented by a single plane with 4 rules. In contracting the on-off control rules, we propose a coordinate transformation method of the input variables in order to reduce the number of rules without transforming the shape of the control surface.

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In the conventional fuzzy control method, as the value of a scaling factor in the consequent part is the same in all control areas, improvement of the nonlinear input/output characteristics of a fuzzy controller is limited thus, its control performance cannot be improved markedly. Therefore, a new fuzzy control method, which can markedly improve the control performance compared with the conventional fuzzy control method, is proposed in this paper. In the proposed fuzzy control method, the control performance is improved because the value of the scaling factor in the consequent part is tuned dynamically according to the control area by using the fuzzy inference method. Then, on the basis of the simulation results, in which the first- and second-order lag systems with dead time are set as the controlled system, the effectiveness of the proposed fuzzy control method in improving the control performance is compared with the conventional fuzzy control method.

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現在，に関する研究開発が、多方面で行なわれている。ライントレースロボットや工場などの自動搬送車などの制御方法に，を用いられていることは多い．そこで，ライントレースカーのように，走行速度の速い制御には応用できる．本研究は，ライントレースカーの操舵角とモータの制御に簡略型推論法を用いることで，ジグザグ走行をせずに，滑らかに制御することできると考えられる．構成としては，センサ値を入力として操舵角を求める．次に，出力された操舵角を入力に使い，左右のモータ出力が求まるという，１入力3出力9ルールのファジィ推論で制御をおこなう．

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Koliverらは，器を用いた分散型マルチメディアシステムのQoS適応制御モデルを提案している．しかし，Standardなを用いると計算負荷が大きく実用的でない．そこで本発表では，Takagi-Sugenoファジィモデルを用いたQoS適応制御法を提案し，有効性を調べる．

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One of the important concept in fuzzy control is fuzzy inference, and the “simplified inference method” which is aimed at increasing the speed of the fuzzy inference has recently been used to realize a high-speed fuzzy controller. In designing a fuzzy controller, a high dimension such as 7×7 or 5×5 partitions is frequently used for the number of fuzzy labelings. However, as the number of fuzzy labelings increases, the number of control parameters increases rapidly and tuning of the fuzzy controller becomes difficult. Therefore, a fuzzy controller is required to be partitioned into a low-dimensional number of fuzzy labelings such as 3×3 partitions.
With this in mind, first, a method of improving the control performance for a low-dimensional number of fuzzy labelings using the “simplified inference method” which enables high-speed inference is proposed in this paper. Next, the effectiveness of this improvement method is investigated based on the results of several simulations where a first-order lag system with dead time, which is a representative model for plant characteristics, is used as the controlled system.

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This paper presents an approach to fuzzy model following control. The proposed method is a unified approach that contains the regulation and servo control problems as special cases. A new parallel distributed compensation (PDC) to realize fuzzy model following control is presented. The new PDC fuzzy controller mirrors the structures of Takagi-Sugeno fuzzy models that represent a nonlinear system and a nonlinear reference model. First, we present a linearization technique as a basic result. Conditions to linearize the error system between the feedback system and the nonlinear reference model are obtained in terms of linear matrix inequalities (LMIs). It is remarked that the derived LMI conditions may be sometimes conservative. To overcome the difficulty, we present a relaxed approach that employs relaxed LMI conditions. Design examples are illustrated to show the utility of the fuzzy model following control, particularly, the relaxed approach.

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近年、非線形制御に

が多く用いられており、その設計手法について種々の提案がなされている。制御対象のファジィモデルに基づく設計手法は、制御知識獲得の労力を軽減し、さらにはベテランのいない制御対象に対しても器設計を可能とし、種々の研究が進められている。しかし、の定性的でわかりやすいという特徴を活かし、さらに望ましい制御系の応答を考慮した器の設計手法は提案されていなかった。本論文では、系の挙動の検証に用いられるRule-to-Rule Mappingを器設計に応用し、言語的に与えられた制御系の所望の応答を翻訳した設計仕様と制御対象のファジィモデルから自動的に御器を設計する手法を提案する。倒立振子の振り上げ実験を行い、本手法により容易に器が設計できることを示す。

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The role of the a priori probabilities is unclear for a stochastic fuzzy control with a single vector data described In the first report, because in such a case the number of Gaussian potential functions is equal to the number of Control rules. In addition, as in a conventional fuzzy control based on fuzzy reasoning, it is necessary to clarify the relationships between the fuzzy sets and the control rules. We here consider a static multiple model adaptive control (MMAC) for the initial data distribution, in which it is assumed that a single vector data is partitioned into two subvector data and the hierarchical hypotheses are introduced with respect to each initial data distribution. Then, two kinds of stochastic fuzzy Control are proposed on the basis of such a static MMAC: one Case assigns the a priori probabilities to the fuzzy sest for each subvector data, and the other case assigns the a priori probabilities to the control rules.

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まず、本開発では、研究を展開するにあたっての道具立ての必要性から、直接法はもちろんのこと、高速制御が可能な間接法、とPID制御とのハイブリッド型であるファジィ・PID法といった各種法が容易に実現でき、しかもそれらの制御性能の評価ができる用シミュレータの開発を行った。次に、本研究では、特に現在において要請のあるファジィ分割数の低次元化を目的として、低次ファジィ分割数における制御性能の改善法について一提案を行い、その改善法の有効性を本用シミュレータを適用したシミュレーション結果から検証した。なお、ファジィ推論法としては直接法の一種の水本提案の代数積-加算-重心法を用いた。その結果、開発した用シミュレータの有用性を確認するとともに、低次ファジィ分割数における制御性能の改善に関して有効となるような指針を得た。

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