Artificial Intelligence And Fuzzy Logic Controller In A Plc System Computer Science Essay

Artificial watch treatment And Fuzzy logic Controller In A Plc System Computer Science EssayIn this research paper, I am trying to analyse more roughly advanced Programmable logical remains commands.Today it is profound to imagine a industry without PLC and different automatic ascendencys. As the production becomes more and more efficient, the controller work speedy and the outline become more multiform. Artificial intelligence (AI) techniques reduce the intricateity and they ar wasting diseased through PLC-based attend to control dodging. The working of artificial intelligence consist of -diagnostic, association, technical and the expression of an AI agreement. Function such as AI find fault diagnostics in surgical procedure assist in controlling and successfully predicting the outcomes based on resident experience.Here i result be researching more close the applications of PLCs such as lend oneself of PLC s with blear-eyed logic. Basic fuzzy logic and withal its fundamental concepts will be analysed. Use of the fuzzy logic controller in concrete applications include providing actual age logical control dodges. In the end i will be concluding on how advanced PLC argon more efficient than the conventional PLCs.In industry use of automatic controllers is increased, the use of PLCs. The programmable logic controllers are based upon the on/off logic, in PLCs we use ordinarily closed or norm in ally open switch, and these switch piece of ass tress on or turn off the devices. PLCs contain a tenuous mathematical bear uponing unit, memory, input and siding interfaces. But the PLCs are non able to re hold the all entropy of the process and they are not able to take put to death to remove the faults. But with the armed service of the Artificial Intelligence we can make the brass to make the conclusion on faults. Artificial Intelligence is the branch of estimator science. In AI we use the info from the process to solve th e many faults in the industry. All the tuition use by the AI is gathered from the person working in the workings/machine and log book excessively give information about fault. The information about the fault-what kind of fault that was and how that was solved. Once all the information we gather from the process, all information is stored in the memory of the PLC or elsewhere will be used by the PLC to solve the thickening problems of the process..II. ARTIFICIAL INTELLIGENCE IN A PLCA. Three type of AI dodgingThe classification of AI system is very difficult because they are used in the many applications but however we can classify in three types 1.diagnostic 2. fellowship 3. skilful.All three type of AI system have similar characteristics. The system become more and more sophisticated as the size of the info base increases and the extent how the process entropy is used.Diagnostic AI system.This type of system is the fault detecting systems. They detect the fault in the appl ication and they do not solve the problem. For example if the temperature of a tank is decreased the diagnostic system can diagnose the fault by reading the thermocouple values. These system use the companionship to kick in on a fault conclusion, these type of system are used in the applications that use a small data base and knowledge.Knowledge AI systemAn knowledge AI system is the intensify diagnostic system. These type of systems are able to detect the fault and process behaviours based on the knowledge and they are in add togetherition able to take the closes concerning the process and/or the possible cause of a fault. serious AI systemThis type of system comes on the initial blank space in AI applications. talented systems are more capabilities than the knowledge system. The expert system provides a further capability for examining process data with the financial aid of statistical analysis and the system predict outcomes of the process that are based on present proc ess assessments. The outcome calculation may be a decision and with the help of that decision process maintain the output in spite of a fault detection. The knowledge used in the expert AI systems are more interlocking than in theother AI systems these type of system commit more feedback information. The expert systems also require more refined software programme to make decision, since their decision trees involve more options and attributes.The implementation of the expert systems is only done by with the help of extra programming and they also extremity more hardware. The system use the transducers to make the decision in the process and the wide number of transducer used in this system is more than the other system. Programmable logic controller use the AI system, it will need two or more than two processer to make the all programming for the system. PLC system require more speed to operate in real time, the system should be fast. The system has mountainous data to operate in the real time due to gravid data system also need large memory to store that data .B. Artificial Intelligence System architectureThe leave diagram (Figure 1 ) shows the basic architecture of an AI system. It has three primary elements 1 Global database, 2 Knowledge database, 3 Inference locomotive. The block diagram show that expert block first, that block provide the knowledge to the AI system and the knowledge is received from a person who know about the plant/process, how the machine accomplish their operation. The expert sends the all information (about system maintenance, faults) to the knowledge engineer. The process of transmitting the knowledge and gathering data is kn knowledge as knowledge acquisition.CUsersPARVEENDesktopimg3.jpgFigure.1 Artificial Intelligence system architectureGlobal DatabaseGlobal database contain the information about the process and the system, how to control them. The information contained by the orbiculate database is about the input and output data flow from the process. The spheric database is the storage domain, the information about the process stored. The data stored in global database can be used any time to make the AI decision to control the process. PLC have memories to store the data and the Global database resides in the memory of the system that makes the system to take the AI decisions. We can also use the AI system with computer and the Global database will be in the hard disk of the computer.Knowledge DatabaseThe knowledge database store the information as the global database store about the process and the all information is supplied from the expert. It also contains information about the faults, process, causes of the problems and their solutions as well. Moreover, all the rules that help to make the decision are also stored in the knowledge database. The diagnostic system has knowledge database and that is less complex than the knowledge system. The knowledge system is less complicated than the expert system. It stored in the system memory.Inference EngineAll the AI system has inference engine. All the decisions are made in the inference engine. Inference engine use the knowledge database to make the decision about the process and later that inference engine execute the rules in the process. It also uses the historical data of the process to make the real time decision. PLC system contain the central processing unit, CPU perform all the operation for the system and the inference engine may be inside the CPU or it may not be inside data that depends upon the diagnostic, knowledge, expert.C. Knowledge patternIn the knowledge representation all the AI strategies are organised and the knowledge engineer represent the input of the expert. The knowledge database is used for the storage of the representation. The knowledge from the expert is changed in the form of rules (IF and THEN/ELSE) and we call it rule-based knowledge representation. It make the system sure-footed to tak e challenge and decision.A PLC system is used with AI, all the control strategies are executed by software programs. Whenever a fault is detected by the system and at that time system makes a decision, inference engine also use the knowledge representation. The decision will be in the form of software.D. Rule-based knowledge representationIt uses the knowledge from the expert and make the decision with the help of that knowledge. The rules contain two parts, first part herald (IF something happens) and the second part consequent (THEN take this act). All the rules are made for the process and they can be complex.A simple rule-based System may make a simple diagnostic rule, such as IF the temperature of a tank is less than the set point, THEN turn on the heater. A more complex diagnostic formula may contain rules that further depend on a more complex diagnostic formula and they involve the rules that are depend on Parent rulesIF case 1, THEN ELSE noughtIF case 2, THEN ELSE someth ingIF case 3 THEN nothingThe decision tree makes the system capable to take the decisions. The figure 2 shows how the decision tree work to get a decision on the given process data.CUsersPARVEENDesktopimg4.jpgFigure 2 Decision TreeE. Knowledge inferenceThis is the rule used to draw conclusion by gathering the data. When the system execute the main control strategy at that time the inference of knowledge takes place in the inference engine. The knowledge inference is also takes place in knowledge database when computation of rule is going on. In the small control system the knowledge inference takes place on local basis. But in case of large systems knowledge inference takes place in the hierarchical system. To purpose a AI based PLC we need hardware, the need of hardware depends on the involvement of the AI. In all AI systems some common methods of rules are used for the implementation of knowledge inference. Methods are 1. Forward Chaining, 2.Backward Chaining. Forward chaining-T his method is used to find out the outcomes of a given data and receives the information from the global database. Forward Chaining is done by two methods depth first, extensiveness first search. Backward chaining-This is also similar to the forward chaining. Basically it is used to find the antecedents.F. Basic Architecture of an AI based PLCLarge and complex distributed control systems are made by the combination of small systems. They can communicate with each other either directly or with the help of local area network. The AI is added in the large systems, global database, knowledge database and knowledge inference from these is distributed all over the system. These large systems are made by the combination of small system and all the local system has their own local data base and knowledge database. The PLCs in the diagram shows they perform inference engine computations. In the large systems the supervisory PLC use the all subsystem and their local database to make a comple x decision. The main computer we call it blackboard hold the all information from the small units. The main computer applies all the complex AI solution.CUsersPARVEENDesktopimg5.jpgFigure 3 Architecture of an AI based PLCIII. FUZZY LOGIC IN A PLCIn industrial automation Programmable Logic Controller combine the simplicity, and reliability. Fuzzy logic is a part of AI which deals with reasoning used to imitate human decision making and thinking in machines. The reasoning is transformed in algorithms. These algorithms are used when the data cannot be converted in the double star form. The output of the process is the input for the fuzzy controller. Fuzzy logic performs three main actions. First is fuzzification, in this action the data received at the input is converted in the fuzzy form. Second is fuzzy processing, which involves the transformation of the input data according to IFTHEN rules formed by the user at the time of design and programming of the fuzzy control systems. After finishing the fuzzy processing (rule-processing stage) the fuzzy controller reach an outcome. Third is defuzzification process, this is final step of the fuzzy controller. In this step the final output data is converted into the real output data and after that the data is sent to the process with the help of output interface. The fuzzy logic controller is placed in the PLC rack in this case the controller does not have a direct contact with the process, the fuzzy logic controller will send the defuzzification data in the PLC memory location and PLC send that data to the process by the interface module. In the more or less of the fuzzy logic controller have their independent interface ports and they are also connected to the PLC with the help of the plug. The fuzzy controller can communicate with the process through the PLCs input/out ports. PLC can be interfaced with the intelligent fuzzy controllers.Interface of Fuzzy logic with PLCA Fuzzy logic controllers input interface can rea d the data from the 8 devices and it can transmit the data to 4 output devices with the help of the output interface. This interface is able to perform 128 rules, each rule can have maximum IF conditions and the action will be in the form of two THEN. The fuzzy logic controller has capability to perform all its computations in only in 6 msec if fuzzy logic unit works separately of the processer, as a result it providing fast functioning of fuzzy logic control.Fuzzy Logic and I/O CommunicationIn below given Table 1, the Fuzzy Logic whole (FLU) uses the programmable controllers memory to store the control parameters and fuzzy logic controller uses 10 words or learns. The position of the FLU module in the rack tells about the registers addresses. Assuming that the position of the FLU module takes the addresses one hundred ten through 119, the use of the addresses by the FLC module as followsThe first four bits (0-3) the first word is (word 110) and its first four bits(0-3) enclose, in BCD, the FLU module uses as the number of inputs. 15 number bit turns on the fuzzy processing of this word.The second word (word 111) specifies that the location of the input data stored in the PLCs memory. It tells the starting register address.TABLE Iinputs bits 0-3 of word 110 specify the number of inputs to be read(8 max) (e.g., I = 8) expression 111 starting address where input data is located (length of I)(e.g., address = 120)Outputs bits 0-3 of word 112 specify the number of outputs to bewritten (4 max) (e.g., O = 4) countersignature 113 starting address where output data is located (length of O)(e.g., address = 130)Word 114 used for flags and settingsWords 115-119 available as working word addresses3) As the first word, the third word is (word112) and the first four bits enclose the outputs in BCD.4) The fourth word (word 113) store the address where the output data is stored, the output data is obtained by the fuzzy logic computations.Because fuzzy logic controller work wi th the other I/O interfaces, their input/output data must be send to the I/O modules working with them. Figure 4 shows how the memory addresses (words) used by the Fuzzy Logic Controller and it also shows the location of the input and output data according to the input/output devices.CUsersPARVEENDesktopimg2.jpgFigure 4 The working of the Fuzzy Logic Unit works with I/O interfacesWe can also use the block transfer instruction to transfer the data between FLU and input/output interfaces (Figure 5).CUsersPARVEENDesktopimg1.gifFigure 5.Block Transfer of instructionsIV CONCLUSIONWhen we apply artificial techniques to a system, we need to add hardware as well as software to in the system. The program that system needed is depending upon the fault in the system, the fault detection is complex then the program will be more complex. We design a system that also has intelligence this is possible by adding the data from the process. The data should be about the process regarding the last time fault and what type of fault that was, how that was solved and when was the last maintenance performed. 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