A Simulation Research of Artificial Intelligence Control

1、A Simulation Research of Artificial Intelligence Control Abstract: The traditional control system can not meet the more complex control tasks of the problem, using artificial intelligence control method of imitation, artificial intelligence control system on the overall structure of the design, and

2、given the specific control algorithms. System relies on accurately identify the various features of the error and make the appropriate decisions to multiplexing, open, closed loop control mode of combining control and solve the complex control of the process of identification, decision-making and co

3、ntrol problems and achieve A unified identification control. U29er29A1136ini29AraAorDe29kAop作文/A Simulation Research of Artificial Intelligence Control_Key words: intelligent control, artificial intelligence, PID controlIntroduction60s of last century, automatic control theory and technology is a po

4、werful, artificial intelligence research have begun to rise, first proposed in 1966, JM Mendel of artificial intelligence for spacecraft control system design 1; 1971, the famous scholar KS Fu from the perspective of the development of learning control was first proposed intelligent control this eme

5、rging discipline 2; 1977, Saridis from the control theory point of view, put forward a hierarchical intelligent control structure 3; KJ Astrom proposed expert control system 4. In the ensuing decades, neural networks, fuzzy control, intelligent control of optimization theory has been widespread conc

6、ern.Intelligent control is artificial intelligence, operations research and automatic control of the intersection of three disciplines. It is the traditional control of the advanced stage of development, primarily those who use traditional methods to solve difficult to resolve complex system control

7、. These include intelligent robotic systems, complex industrial process control systems.For some of the production process or control objects, difficult to use the general laws of physics or chemistry to create a mathematical model. The object of many factors, some of the factors and the cross coupl

8、ing between, making the model is very complex and not easy to build, and sometimes not even find the real meaning. For the sort of production process or the controlled object, such as the use of classical control theory and modern control theory methods to design control systems, it is obvious very

9、difficult to have good control effect. But in fact difficult for this type of automatic control of the production process or the controlled object, an experienced operator can manually control but often to achieve a satisfactory control effect. Therefore, the proposed imitation artificial intelligen

10、ce control, control structure and control behavior from both mimic some of the features and functions, including the identification of peoples online properties, characteristics such as memory and logic inference intuition. The intelligent control algorithm can not predict the information needs of o

11、nline identification controlled object is not an accurate model, we can achieve fast and high precision control, and has strong robustness. I. Control the overall design of artificial intelligence imitation1.1 Control Model Comparison and SelectionPID control to a certain extent, imitating the proce

12、ss of manual control, but can not completely imitate the manual control of the whole process 5. Manual control of the process can also be viewed as a special kind of PID control process, but manual control, compared with the ordinary PID control has obvious difference. Specific performance:1) Observ

13、ation of the human eye has the intelligence and nonlinear characteristics, and the measurement instrument is linear, and no intelligence;2) to the error by looking at the size and direction of the control object also proportional control, but the analysis and control of human decision-making and rea

14、l-time nonlinear time-varying, and has ability to learn, and the role of an ordinary PID controller, only the performance of the ratio of for the simple linear proportional relationship;3) The persons memory effect through the brain accumulation of errors arising from the role of integral control. P

15、eople are strong and selective memory, people in the adjustment process in the memory of those who have chosen to useful information while ignoring unwanted parts. Ordinary PID controller integral action is not indiscriminately memory all the information, which will contain useless or even harmful i

16、nformation, thereby controlling the level of people can not be achieved the role;4) the error by looking at changes to the size and direction of the control object also differential control, and error variation of observation and control decision-making with predictable and selective to distinguish

17、between changes in the causes of errors take the appropriate control strategy, not only obvious effect of large changes, the error for the slow changes can also be effectively controlled.5) The role of ordinary differential PID controller is the error produced by a variety of reasons are treated the

18、 same, the trend of large sensitive and difficult to change in response to a slow trend.For example of the temperature and humidity control: The sensor detects the temperature, humidity, through the corresponding transmitter is converted to DC signals, placed in front of the machine (from the machin

19、e) into the controller (host). According to the testing parameters of the host data processing, and control signals are sent to the corresponding actuator solenoid valve to regulate the gas flow, to achieve temperature, humidity and other environmental parameters of the intelligent control. Temperat

20、ure, humidity, electromagnetic valve by adjusting the appropriate enforcement agency to change the temperature and humidity values, for this process, the object of the mathematical model can be simplified to first order approximation of the inertia plus dead time model, with the transfer function ca

21、n be expressed as:G(S) = e-tsWhere T is the time constant, t is the time delayMeanwhile, the temperature of the transfer function G(S) can be simplified to the second inertia model: G(S) = Although this is a very simple mathematical model, but difficult to establish precise temperature, humidity mat

22、hematical model, using the classical control theory and modern control theory to design the temperature and humidity control system, it has been difficult to obtain satisfactory control effects, so in a more complex environment parameter control process, using traditional control methods can not ada

23、pt to complex environmental parameters. As can be seen by comparing the above, we use simulation intelligent control method, the error will be very help identify the various features, which make the corresponding control mode to control. Can effectively control the speed of protection, stability and

24、 accuracy.1.2 System StructureImitation artificial intelligence control system will be divided into the following four components, the system structure shown in Figure 1:1) Imitation of artificial intelligence controller: control by computer simulation of artificial intelligence algorithms digital c

25、ontroller.2) The input and output interface devices: imitation artificial intelligence control device through the input interface to get the signal from the controlled object, the output interface device through the artificial intelligence controller to imitate the output control signals to the impl

26、ementing agency, the purpose to control the controlled object.3) Generalized objects: including the implementing agencies and charged objects. Controlled object which can be linear or nonlinear, steady or time-varying, single-variable or variables, there is a strong pure time delay and the interfere

27、nce of the object.4) Sensor: its role is to be charged object or the production process of electricity or electricity signal is converted to a standard computer can accept voltage or standard current signal. The conversion accuracy of the level of the control system performance greatly.II. Imitation

28、 artificial intelligence control algorithmSelect the appropriate control mode control is the core of algorithm design, simulation of artificial intelligence control algorithm is mainly based on the size of the controller input signal, the direction of its trend to make the appropriate decision-makin

29、g, relying on accurate identification of the various errors features and make the appropriate decisions and to multiplexer, open, closed loop control mode of combining control. This flexible and clever to rely on the identification, decision-making and control, so for those who control quality of ch

30、ecks and balances (fast, smooth and precision) under the control algorithm is easy to unity. Imitation artificial intelligence control algorithm can be described as follows:If enM1, then output P0 = FFH or P0 = 00H, Using the switch mode control;When en?驻en 0 or ?驻en = 0, en 0, and enM2 , then outpu

31、t P0(n-1)+K1KpeWhen en?驻en 0 or ?驻en = 0, en 0, and enM2 , then output P0(n-1)+Kpe , Using proportional control mode; When en?驻en 0,?驻en?驻en-10 or en =0, then output P0(n)=P0(n-1), Used to maintain control mode 1; When en?驻en 0 or ?驻en?驻en-10, and enM2, then output P0(n-1)+K1K2Kpe, Used to maintain

32、control mode 2; When en?驻en 0 or ?驻en?驻en-10, and enM2, then output P0(n-1)+K2Kpe , Used to maintain control mode 2; After discrimination with the current value of en e said, Expressed by en-1,en-2,e cycles before the value of 1 and 2, ?驻e=en-en-1、?驻en-1=en-1- en-2 represents the current and previou

33、s cycle of time difference e. Where: e is the first n-pole plant of e; Kp is the proportional gain; K1 is the gain amplification factor, and K11; K2 is the inhibition coefficient, and 0K21; M1、M2 is the set error limits, and M1M2; n is a natural number, indicating the serial number of the control cy

34、cle; P0(n) is the output P for the first time the need to maintain the value of n; P0(n-1) is the n one cycle before the output to maintain the value of P; Analysis of the above algorithm as follows:When the error increases the absolute value of e, which is characterized en?驻en 0: When the error dec

35、reases when the absolute value of e, which is characterized en?驻en 0; at the pole t1 and t3, with features ?驻en?驻en-10; on the contrary, if the ?驻en?驻en-10, said the system polarity.When the error is enM1, is used to control switch mode; only when the enM1, the characteristics can be the basis of it

36、s corresponding control mode. When the error of the trend toward increased, the amount can be increased in order to adjust the bias control, this time with the ratio model, Kp will get a large proportional gain. When the enM2, can be multiplied by the gain amplification factor Kp & K1, makes the con

37、trol volume becomes larger. When the error reaches extreme t1 & t3 time, you can maintain the value of the original on the basis of a modest increase in the value of (hold mode 2), e to maintain that output up to date against No. (Hold mode 1).In practical applications, the error curve may be more c

38、omplex, although there t1 & t2 extreme point, but before and after these two points, the error e trends are different, Expressed as: Points in t1: ?驻en?驻en-10，en?驻en0;Points in t2: ?驻en?驻en-10，en?驻en0. t1 Point in the use of protective mode 2, the proportion of the t2 point mode is available; otherw

39、ise it will extend the transition process.Control applications in the system, the conventional proportional control, if a larger proportion of the gain, it will cause system instability. However, in imitation of the proportion of artificial intelligence control algorithm the control period, but will

40、 not cause a large Kp system instability, because as long as the error is more than extreme point, the controller will switch to hold mode, not only reduces the control time volume, is more important is to keep the system open-loop model is equivalent to running, the controller output has nothing to

41、 do with the current conditions, it is the characteristic quantity by the memory control.In imitation of artificial intelligence control, when the error when e=0, indicating that the system is in balance, in this case, so long as to maintain this energy balance can be, without having to modify the controllers output, this time can be based on changes, then make new decisions and decision-making. Can be shown that a class of integral functions hold mode, meaning that it can eliminate the residual and thus rely on precise control. III. Conclusion In traditional control systems, control tas