Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

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A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

Survey paper: A survey on industrial applications of fuzzy control

Precision positioning of an object relative to a reference point is a common task in many activities of production engineering. Sensor technologies for single axis measurement, either linear or rotary, which form the fundamentals of measurement technologies for precision positioning, are reviewed. Multi-axis coordinate measurement methods such as triangulation and multilateration, as well as Cartesian and polar systems for specifying the position in a plane or three-dimensional (3D) space are then presented, followed by a discussion on traceability and standards. Some advanced applications of measurement technologies for precision positioning in manufacturing industries are also demonstrated.

Measurement technologies for precision positioning

Review of mobile mapping and surveying technologies

This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers tuning processes and enhance the performance of their control systems. It further contains application examples.

/pdf/advanced-fuzzy-logic-technologies-in-industrial-applications-3oawnya8qp.pdf

Advanced Fuzzy Logic Technologies in Industrial Applications

Laser tracking systems (LTS) are among the most accurate robot metrology systems. These laser interferometer systems combine the advantages of high resolution, large work space and contactless measurements. A target mounter on the end-effector of the robot, is automatically tracked by a laser beam targeted by the moving mirror. A prerequisite for utilizing a LTS to calibrate robots is that the LTS itself should be self-calibrated successfully. In this paper, we describe the experimental calibration of a PUMA 560 robot by using a LTS developed at the Robotics Center, Florida Atlantic University. The calibration is based on a prior successful self-calibration of the LTS. Calibration results are analyzed and confirmed using a verification method. This is the first actual calibration of robots using a LTS in the United States during the 20th centenary.

Experiment study of PUMA robot calibration using a laser tracking system

Laser tracking systems (LTSs) employ tracking laser interferometers for coordinate measuring of precision machine tools and robots. Such coordinate measuring machines, if properly calibrated, are potentially fast, very accurate and can cover a large workspace. LTS devices must be self-calibrated, using redundancy or constraint surfaces. A methodology for self-calibration of a multi-beam LTS utilizing planar constraints is formulated and demonstrated. A kinematic model of a multi-beam LTS is derived. Model error analysis demonstrates that the use of angular measurement of the gimbal joint positions, relatively inaccurate as these are, does improve the overall system calibration accuracy. Self-calibration model parameters observability of the multi-beam LTS is studied. The results reveal the applicability of planar constraints to system self-calibration. Simulation and experimentation results obtained on a prototype system are reported demonstrating the applicability of the calibration strategies.

Calibration of multi-beam laser tracking systems

In a laser tracking system (LTS) the control objective is for a laser beam to track a retro-reflecting moving target through adjustment of joint angles and velocities of a two-degrees-of-freedom (DOF) tracking gimbal on which tracking mirrors are mounted. This is done based on two types of feedback signals: distance reading, obtained by a laser interferometer and off-center distance error of the returning laser beam, as measured by a four-quadrant photodetector. The LTS control system should effectively overcome noise disturbances originating from the system itself as well as the environment, and coupling effects existing in the tracking system. A complete LTS consists of laser interferometer transducer subsystem, opto-electronic beam steering subsystem, gimbals driving subsystem and the digital control subsystem. As high-tracking accuracy and high-tracking speed are both vital for LTS operation, a design of a high-performance controller is critical. This brief shows that fuzzy logic controllers (FLC) can outperform classic proportional-integral-derivative (PID) controllers in such applications. Disturbances and nonlinearities existing in the LTS developed at the Florida Atlantic University (FAU) Robotics Center are discussed and analyzed, and an experimental-based design and implementation of a mixed-mode FLC to suppress such coupling effects and nonlinearities, which cannot be handled by PID controllers, are studied. The advantages of utilizing a phase-shifted FLC to improve the control performance for a system with a relatively long time delays is confirmed by simulation and experimental results. A comparison between the performances of PID and FLC is presented.

Fuzzy logic control to suppress noises and coupling effects in a laser tracking system

Traditional robot calibrations implement either model-based or modeless methods. A model-based calibration method normally involves four steps: kinematic model definition of the robot, measurement process of the robot’s positions, identification of the kinematic model of the robot and compensation of the position errors. This type of method can be both time consuming and complicated because of the identification and compensation processes. Most traditional modeless methods are relatively simple and practical, but their calibration accuracy is relatively low and most of them are only suitable for the robot’s calibration in the 2D domain and in relative small workspaces. This paper provides a novel modeless fuzzy interpolation method to improve the compensation accuracy for robot calibration in the 3D workspace. A comparison between the model-based and modeless fuzzy interpolation calibration method is made. The simulated results show that the modeless fuzzy interpolation method is compatible with the model-based calibration method, and even outperforms a model-based counterpart in terms of accuracy and complexity in a relatively compact workspace.

Ying Bai

Papers

Advanced Fuzzy Logic Technologies in Industrial Applications

Experiment study of PUMA robot calibration using a laser tracking system

Calibration of multi-beam laser tracking systems

Fuzzy logic control to suppress noises and coupling effects in a laser tracking system

On the comparison of model-based and modeless robotic calibration based on a fuzzy interpolation method