Bahan 5

Materi Kuliah Pertemuan: 3

Contoh Aplikasi PID Control.
Judul Makalah: Adaptive Decoupling Predictive Temperature Control for an Extrusion Barrel in a Plastic Injection Molding Process




Anda diharapkan:
Dapat menganalisa bagaimana suatu sistem kontrol bekerja.

CISAR 2009

Conference on Intelligent Systems and Robotics (CISAR)

International Advanced of Technology Congress (ATCi)

PWTC, Malaysia
November 3-5, 2009

A Novel Soft Computing Technique for Resolving Locational Ambiguities in Wireless Positioning and Tracking Systems

A New Fuzzy Logic Approach to Building Automation from Safety And Health Perspective

P300 Applications and Detection Via Continues Wavelet Transform Preliminary Results

Palm-Dorsa Vein Detection Using Webcam

A Survey on Performance and Requirements of Virtual Cellular Manufacturing versus Classical Cellular Manufacturing and Future Research Issues

A Review on Fuzzy Linguistic Approach in Artificial Intelligent Applications

Colour Model for Outdoor Machine Vision for Tropical Regions and Its Comparison with the Cie Model

Productivity Rate of Automatic Machine Tools Change of Processing Modes

Bio-Inspired Adaptive Linear Classifier for Colour Discrimination in Outdoor Conditions

Biologically Inspired Scene Recognition Using Scale Invariant Feature Transform

Committee Neural Networks for Prediction of Machine Failure Times

Design of Intelligent Control for 3dof Nonlinear Robot Arm Using Afis

Economic Production Quantity Model Considering Imperfect Products

Dynamic Bayesian Networks with Ranking-Based Feature Selection for Dialogue Act Recognition

Simulation-Based Scheduling For E-Maintenance Systems Considering Remaining Useful Life of Equipments

In-Process Surface Roughness Prediction Using Heat Generation Rate of Work Piece Surface in Turning Operation

Brain Computer Interface Design and Applications: A Literature Review

Non-Destructive Inspection of Multi-Layered Composites Using Ultrasonic Signal Processing

Human Behaviour Recognition: Challenges and Future

Design and Control of a Small Mobile Robot: Robotic Vacuum Machine

Contour Extraction of Echocardiographic Images Based On Pre-Processing

Automated Attendance System and Face Recognition: Motives and Challenges

The Application of Real Numbers Code For Genetic Algorithms Into Design Membership Function In Fuzzy Logic Control System

Intelligent Robotic Parts Feeder Using Radio Frequency Identification (Rfid) Technology

Protection Decision Algorithm Discovery from Numerical Relay Recorded Event Report

A Smart Gas Sensor Insensitive To Humidity and Temperature Variations

Utilizing the Response Patterns of a Temperature Modulated Chemoresistive Gas Sensor For Gas Diagnosis

An Integrated Model of It Adoption in Small and Medium-Sized Enterprises; Influencing Factors

Embedded System Implementation on Fpga System with Clinux Os

A Heuristic Model to Create Initial Assignment of Mixed Model Production Through The Parallel Assembly Lines

Wireless Sensor Networks in Medical Application

A Framework of Software Maintenance Tool for Classifying Maintenance Requests

Design and Development of Pneumatic Gripper for Comau Robot

Small Autonomous Robotic Kits and Competition as A Tool To Enhance Science And Technology Interest In Malaysia

Knowledge Management in Medical Informatics for Early Warning System

Employing Spatial Objects with Natural Languages for Autonomous Machine

Anti-Terrorism Knowledge System for Crimes Prevention in A Collaborative Environments

Artificial Control of 6 Dof Robot Arm Based On Afgs

Palm Print Verification System

Pneumatic Tourniquet System For Limb Surgery (Review Paper)

Biomechanical Analyses And Design Optimization Of Hip Prosthesis For Total Hip Joint Arthroplasty

Analyzing The Effect Of Cutting Parameters On Surface Roughness And Tool Wear When Machining Nickel Based Hastelloy – 276.

Developing Mixed-Integer Programming Model For Minimizing The Overall Make-Span Time In Mixed Model Assembly Line

Intelligent Manufacturing System: Step-Nc

A Proactive Architecture For Heterogeneous Systems Interoperability In Smart Home Environment

A New Bidirectional Heuristic Algorithm In A Multi Objective Albp

Fuzzy Logic Modeling For Peripheral End Milling Process

Trends Of Virtual Reality In Malaysian Automotive Industries

Rough Shared Weight Neural Networks For Improving Generalization Of Neural Networks

Virtual Environment And Virtual Reality Application In Automotive Industry: A Review


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Fuzzy-GA

In our daily life from the production lines in manufacturing plants, medical equipment, and agriculture to the consumer products such as washing machine and air-conditioner, FLC can be applied. The important part in FLC is during the process in selecting the membership function. The membership function of a fuzzy set is a generalization of the indicator function in classical sets. In fuzzy logic, it represents the degree of truth as an extension of valuation.

As for an example, the controller temperature sets for plastic extruders by FLC. When extruding certain materials, the temperatures along the extruder must be accurately controlled in accordance with properties of the particular polymer and of the extruder. If the temperatures are not accurately controlled, the molten polymer will not be uniform and may decompose as a result of excessive temperatures.

One of the problems associated with the prior art extruder control systems occurs in the design of the barrel zone temperature controllers (Tsai & Lu, 1998; Lu & Tsai, 2001). Preferably, these controllers are designed with a high sensitivity to disturbance signals. However, when a change in a temperature set point occurs, there is a danger in saturating the zone temperature controllers as the magnitude of the temperature set point changes are generally greater than the magnitude of disturbances. Hence, the sensitivity of the controller to disturbance signals must be reduced to prevent saturation of the controllers to set point changes (Tsai & Lu, 1998; Lu & Tsai, 2001; Altinten, et al., 2006).

Thus it is important to select the accurate membership functions for temperature setting an extruder control systems. However, conventional FLC uses membership function generated by human operator, where the membership function selection process is done with trial and error and it is runs step by step, which is too long in solving the problem (Torres, 2000; Altinten et al, 2006). For a new approach for optimum coding of fuzzy controllers via Genetic Algorithms (GA), GA are used to determine membership function specially designed in situations as above.

The controller must operate in two modes (Bela, 2006; Hung & Sheng, 2006).

1. In automatic mode, it increases from a fixed initial point to a fixed set point at a fixed rate. Designing a conventional controller for these operational specifications is routine.

2. In autonomous mode, however, the control system must cope with abnormal situations that can shut down plant operation. Recovery from such conditions involves reheating from arbitrary initial points at different rates and possibly to different set points. A conventional controller cannot handle all these situations efficiently.

According to the situations, this is why we need to use control system based on FLC, but manually designing the membership function of FLC to satisfy such requirements is to possess one common weakness where conventional FLC use membership function generated by human operator (Torres, 2000; Altinten et al, 2006). Thus, GA used to design FLC. GA are a rule of the resolution that is carried out at the same time to several solutions and they are done randomly to increase the efficiency as well as taking the fastest processes in solving the problems (Torres, 2000; Galantucci et al, 2004; Altinten et al, 2006; and Gen et al, 2008).

Reference

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IBSI/VI/2009 - 22

Merepresentasikan Pengetahuan pada
Sistem Pakar

1.  Pendahuluan

2.  Jenis-jenis representasi pengetahuan untuk sistem pakar

     2.1.  Frame

     2.2.  Semantic Network

     2.3.  Script

     2.4.  Logic

     2.5.  Rule base

3. Rule base

     3.1.  Prinsip Rule Base

     3.2.  Kelebihan Representasi Menggunakan Rule Base

     3.3.  Contoh Penerapan Rule Base

4. Kesimpulan

Daftar Pustaka

Format Penulisan Daftar Pustaka

Referensi buku:

Negnevitsky, M. (2008). Artificial intelligence : a guide to intelligent systems. 2nd ed. Harlow: Addison-Wesley.

Referensi web/link:

Netadelica. (2010). Comparing Different Parameters for Evolving a Bit Counter. [Online].
Available: http://www.netadelica.com/ga/.

Referensi Journal:

Nicol N. Schraudolphl and Richard K. Belew1 (2004). Dynamic Parameter Encoding for Genetic Algorithms. Springer Netherlands. Volume 9, Number 1: pp 9 - 21.

 

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