CN105807615A - Fuzzy feedforward-feedback controller - Google Patents
Fuzzy feedforward-feedback controller Download PDFInfo
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- CN105807615A CN105807615A CN201610317962.9A CN201610317962A CN105807615A CN 105807615 A CN105807615 A CN 105807615A CN 201610317962 A CN201610317962 A CN 201610317962A CN 105807615 A CN105807615 A CN 105807615A
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/0275—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using fuzzy logic only
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
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Abstract
The invention discloses a fuzzy feedforward-feedback controller.A fuzzy feedforward-feedback control algorithm includes the following steps that an original PID controller is replaced with a parameter-self-tuning fuzzy PID controller, the parameter-self-tuning fuzzy PID controller is mainly formed by a fuzzy inference machine and a PID controller, a controlled variable error e and the variable rate ec of the error serve as input of the fuzzy controller, the variable quantities delta KP, delta KI and delta KD of PID control parameters serve as output, the three-parameter variable quantities of the PID controller are subjected to real-time on-line adjustment through the fuzzy control rule summarized by an expert and practice, and the PID parameter self-tuning requirements at different moments are met.A feedforward control link is added into the parameter-self-tuning fuzzy PID controller, when interference appears, before the interference acts, feedforward controlling directly acts on the control system, most of deviation control quantities are eliminated, the residual deviation is eliminated through PID feedback control, the accuracy requirement of feedforward control for a model is met, and the problem that the pure PID controller is not timely is solved.
Description
Art
The present invention relates to a kind of intelligent control algorithm, particularly relate to based on the control algolithm being incorporated on multiple traditional method basis.
Background technology
A lot of systems all have feature non-linear, large dead time, big inertia at present, the PID controller that tradition is simple, although its design is simple, easy to operate, facilitate implementation, but only when have linear characteristic and parameter coupling good just there is good control effect, once deviate operating point farther out or parameter change or there is interference controller and all can not change therewith, make system be difficult to keep its dynamic quality, there is significant limitation.Fuzzy control is a kind of Computer Control Technology controlling rule, fuzzy logic inference based on natural language, and it does not rely on the mathematical model of control system, and available fuzzy control realizes the self-adaptative adjustment process of pid parameter.A lot of control processes are usually associated with substantial amounts of interference now, just introduce the concept of compensation in control theory.The feedforward is applied in the adjustment of bubble water level as far back as nineteen twenty-five, it is based on causing the interference size of controlled Parameters variation to be adjusted, in the system of this control strategy when interference has just occurred and can measure, the feedforward just sends adjustment signal makes adjustment parameter do corresponding change, adjustment effect and interference effect is made to offset in time before controlled parameter produces deviation, simple Front feedback control is a kind of opened loop control, the disturbance quantity specified can only be compensated control, and controlling there is deviation, this brings obstacle to the extensive use of the feedforward.And the deviation that feedback control is a system be adjusted compensate technology, be interference entrance system after a period of time just will reveal whether, which has limited giving full play to of feedback control effect.Generally combine with feedback control composition feed-forward and feedback multiplex control system at present by the feedforward.Such that it is able to multiple technologies combined, improve the comprehensive responding ability of system.Smith Prediction Control has been carried out improving and in conjunction with PID control by useful OPT optimisation strategy, but PID controller and Smith predictor are all based on mathematical models and design, model parameter is changed adaptive capacity poor, and working conditions change is complicated in actual production process, it is difficult to obtain accurate mathematical model, causes that this scheme is still difficult to obtain gratifying control effect.Mostly being it with neutral net or what fuzzy control combined for the optimization of PID controller at present, therefore various composite controllers continue to bring out.What currently used comparison was many is Fuzzy Adaptive PID Control and this two big class of neuronal-acetylcholine receptor.The combination of various new techniques and introducing, promoted the development of intelligent control technology.
Summary of the invention
It is an object of the invention to provide a kind of fuzzy feedforward feedback controller.For in lacking mathematical models and there is non-linear, large dead time, Great inertia system, based on conventional PID controllers Model suitability difference and control problem not in time, it is proposed to a kind of a kind of fuzzy feedforward feedback controller that fuzzy control is combined with Feedforward-feedback control.The program, on the basis of conventional PID controller, replaces traditional PID controller with the fuzzy controller of parameter self-tuning, and introduces feedforward and feedback control concept, and then ensure that the stability of system mode, enhance controller robustness and adaptive ability.This controller decreases controller and model parameter is changed the impact brought, and decreases the overshoot of system, and no matter when interference source or interfering channel exist interference, controller still can obtain and control effect preferably.
In order to achieve the above object, the present invention adopts the following technical scheme that
Fuzzy feedforward feedback control algorithm, comprises the following steps:
(1) fuzzy controller of design parameter self-tuning replaces original PID controller, it is mainly made up of indistinct logic computer and PID controller two parts, using the rate of change ec of controlled variable error e and error as the input of fuzzy controller, with the variation delta K of pid control parameterP、ΔKI、ΔKDAs output, utilize expert and practice summary fuzzy control rule out that three Parameters variation amounts of PID controller are carried out real-time online adjustment, meet not the requirement of pid parameter Self-tuning System in the same time.
(2) in the fuzzy controller of parameter self-tuning, feedforward link is added, when interference occurs, before it is had an effect, direct feedforward control action is in control system, eliminate major part deviation controlled quentity controlled variable, residual deviation then controls to eliminate by PID/feedback, solves the feedforward to the required precision of model and the simple problem non-timely using PID controller.
(3) closed loop transfer function of controlled volume is by the interference described in algorithm:Apply indeformable condition, P (s) ≠ 0, Y (s) ≡ 0, show that the transmission function of feedforward controller is: GPD(s)+Gff(s)GPC(s)=0, namelyCan be seen that model also to change therewith when model or operating mode change from transmission function, being compensated for so needing to add feedback element.The new departure self-adaptive PID controller with fuzzy control replaces traditional PID controller, and introduce feedforward and feedback controlling unit, and then ensure that the stability of system mode, make it that interference to have good following feature and inhibitory action, enhance the controller adaptive ability to interference, there is good stability and robustness, it is adaptable to the control of Large-lag System.
Accompanying drawing explanation
Fig. 1 is the flow chart that fuzzy feedforward feedback controller is formed.
Fig. 2 is the fuzzy feedforward feedback controller when interfering channel adds step interference and feedforward and feedback controller response curve comparison diagram.
Fig. 3 is fuzzy feedforward feedback controller and feedforward and feedback controller response curve comparison diagram when input adds interference signal.
Detailed description of the invention:
Fig. 1 is the flow chart that fuzzy feedforward feedback controller is formed.The intelligent control algorithm of the present invention comprises the following steps:
(1) original PID controller is replaced with the fuzzy controller of parameter self-tuning, it is mainly made up of indistinct logic computer and PID controller two parts, using the rate of change ec of controlled variable error e and error as the input of fuzzy controller, with the variation delta K of pid control parameterP、ΔKI、ΔKDAs output, utilize expert and practice summary fuzzy control rule out that three Parameters variation amounts of PID controller are carried out real-time online adjustment, meet not the requirement of pid parameter Self-tuning System in the same time.
(2) in the fuzzy controller of parameter self-tuning, feedforward link is added, when interference occurs, before it is had an effect, direct feedforward control action is in control system, eliminate major part deviation controlled quentity controlled variable, residual deviation then controls to eliminate by PID/feedback, solve the feedforward to the required precision of model and the simple problem non-timely using PID controller, improve the stability of system and capacity of resisting disturbance.
Fig. 2 is the fuzzy feedforward feedback controller when interfering channel adds step interference and feedforward and feedback controller response curve comparison diagram.
Fig. 3 is fuzzy feedforward feedback controller and feedforward and feedback controller response curve comparison diagram when input adds interference signal.
Claims (2)
1. fuzzy feedforward feedback, comprises the following steps:
(1) fuzzy controller of design parameter Self-tuning System replaces original PID controller, it is mainly made up of fuzzy reasoning module and pid control module two parts, using the rate of change ec of controlled variable error e and error as the input of fuzzy reasoning controller, utilize fuzzy rule that tri-Parameters variation amounts of PID are carried out on-line tuning, with the variation delta K of pid control parameterP、ΔKI、ΔKDAs output, add the initial set value of PID controller, and then act on controlled device by PID controller, to meet the requirement of not pid parameter Self-tuning System in the same time.
(2) in the fuzzy controller of parameter self-tuning, feedforward link is added, when interference occurs, before it is had an effect, direct feedforward control action is in control system, eliminate major part deviation controlled quentity controlled variable, residual deviation then controls to eliminate by PID/feedback, solves the feedforward to the required precision of model and the simple problem non-timely using PID controller.
(3) closed loop transfer function of controlled volume is by the interference described in algorithm:Apply indeformable condition, P (s) ≠ 0, Y (s) ≡ 0, show that the transmission function of feedforward controller is: GPD(s)+Gff(s)GPC(s)=0, namelyCan be seen that model also to change therewith when model or operating mode change from transmission function, being compensated for so needing to add feedback element.
2. fuzzy feedforward feedback according to claim 1, traditional PID controller is replaced with the self-adaptive PID controller with fuzzy control, and introduce feedforward and feedback controlling unit, and then ensure that the stability of system mode, make it that interference to have good following feature and inhibitory action, enhance the controller adaptive ability to interference, there is good stability and robustness, it is adaptable to the control of Large-lag System.
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CN107490958A (en) * | 2017-07-31 | 2017-12-19 | 天津大学 | A kind of Fuzzy Adaptive Control Scheme of series parallel robot in five degrees of freedom |
CN108983703A (en) * | 2018-07-06 | 2018-12-11 | 清华大学 | Ultraprecise kinematic system feedforward controller parameter tuning method |
CN110161841A (en) * | 2019-06-05 | 2019-08-23 | 中国空气动力研究与发展中心高速空气动力研究所 | A kind of feedforward-fuzzy PID control method suitable for temporarily rushing formula transonic wind tunnel |
CN111367168A (en) * | 2018-12-26 | 2020-07-03 | 博众精工科技股份有限公司 | Feedforward parameter design method based on fuzzy logic |
CN112305912A (en) * | 2020-10-16 | 2021-02-02 | 贵州航天乌江机电设备有限责任公司 | Feedforward pressure control method based on reaction kettle parameter self-adjusting fuzzy PID algorithm |
CN112947088A (en) * | 2021-03-17 | 2021-06-11 | 中国人民解放***箭军工程大学 | Modeling and control method of temperature and humidity system based on closed space |
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CN107490958A (en) * | 2017-07-31 | 2017-12-19 | 天津大学 | A kind of Fuzzy Adaptive Control Scheme of series parallel robot in five degrees of freedom |
CN107490958B (en) * | 2017-07-31 | 2020-06-19 | 天津大学 | Fuzzy self-adaptive control method of five-freedom-degree series-parallel robot |
CN108983703A (en) * | 2018-07-06 | 2018-12-11 | 清华大学 | Ultraprecise kinematic system feedforward controller parameter tuning method |
CN111367168A (en) * | 2018-12-26 | 2020-07-03 | 博众精工科技股份有限公司 | Feedforward parameter design method based on fuzzy logic |
CN110161841A (en) * | 2019-06-05 | 2019-08-23 | 中国空气动力研究与发展中心高速空气动力研究所 | A kind of feedforward-fuzzy PID control method suitable for temporarily rushing formula transonic wind tunnel |
CN112305912A (en) * | 2020-10-16 | 2021-02-02 | 贵州航天乌江机电设备有限责任公司 | Feedforward pressure control method based on reaction kettle parameter self-adjusting fuzzy PID algorithm |
CN112947088A (en) * | 2021-03-17 | 2021-06-11 | 中国人民解放***箭军工程大学 | Modeling and control method of temperature and humidity system based on closed space |
CN112947088B (en) * | 2021-03-17 | 2022-08-16 | 中国人民解放***箭军工程大学 | Modeling and control method of temperature and humidity system based on closed space |
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