Advanced Fuzzy Logic Technologies in Industrial Applications

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. In the mid-1960s and contemporary with Kalman’s pioneering papers on sta- space models and optimal control, L.A. Zadeh began publishing papers on “fuzzy sets”. It took another decade before the fuzzy-logic controller due to Mamdani and Assilion was reported in the literature (ca. 1974), and now the fuzzy-logic control paradigm is entering its fifth decade of development and application. Thus, this new Advances in Industrial Control monograph edited by Ying Bai, Hanqi Zhuang and Dali Wang on fuzzy-logic control and its practical application comes as a timely reminder of the wide range of problems that can be solved by this continually evolving methodology.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. In the mid-1960s and contemporary with Kalman's pioneering papers on sta- space models and optimal control, L.A. Zadeh began publishing papers on "e;fuzzy sets"e;. It took another decade before the fuzzy-logic controller due to Mamdani and Assilion was reported in the literature (ca. 1974), and now the fuzzy-logic control paradigm is entering its fifth decade of development and application. Thus, this new Advances in Industrial Control monograph edited by Ying Bai, Hanqi Zhuang and Dali Wang on fuzzy-logic control and its practical application comes as a timely reminder of the wide range of problems that can be solved by this continually evolving methodology.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. In the mid-1960s and contemporary with Kalman’s pioneering papers on sta- space models and optimal control, L.A. Zadeh began publishing papers on “fuzzy sets”. It took another decade before the fuzzy-logic controller due to Mamdani and Assilion was reported in the literature (ca. 1974), and now the fuzzy-logic control paradigm is entering its fifth decade of development and application. Thus, this new Advances in Industrial Control monograph edited by Ying Bai, Hanqi Zhuang and Dali Wang on fuzzy-logic control and its practical application comes as a timely reminder of the wide range of problems that can be solved by this continually evolving methodology.

From Classical Control to Fuzzy Logic Control.- Fundamentals of Fuzzy Logic Control — Fuzzy Sets, Fuzzy Rules and Defuzzifications.- Implementation of Fuzzy Logic Control Systems.- Knowledge-based Tuning I: Design and Tuning of Fuzzy Control Surfaces with Bezier Function.- Knowledge-based Tuning II: ?-Law Tuning of a Fuzzy Lookup Table.- Apply a Fuzzy Logic Controller to Suppress Noises and Coupling Effects for a Laser Tracking System.- Fuzzy Logic for Image Processing: Definition and Applications of a Fuzzy Image Processing Scheme.- Fuzzy Logic for Medical Engineering: An Application to Vessel Segmentation.- Fuzzy Logic for Transportation Guidance: Developing Fuzzy Controllers for Maintaining an Inter-Vehicle Safety Headway.- Fuzzy Logic Control for Automobiles I: Knowledge-based Gear-position Decision.- Fuzzy Logic Control for Automobiles II: Navigation and Collision Avoidance System.- Fuzzy Logic Based Control Mechanisms for Handling the Uncertainties Facing Mobile Robots in Changing Unstructured Environments.- Combine Sliding Mode Control and Fuzzy Logic Control for Autonomous Underwater Vehicles.- Fuzzy Logic for Flight Control I: Nonlinear Optimal Control of Helicopter Using Fuzzy Gain Scheduling.- Fuzzy Logic for Flight Control II: Fuzzy Logic Approach to Path Tracking and Obstacles Avoidance of UAVs.- Close Formation Flight Control of Multi-UAVs via Fuzzy Logic Technique.- Applications of Fuzzy Logic in Data Mining Process.- Fuzzy Logic Control for Power Networks: A Multilayer Fuzzy Controller.- Fuzzy Predictive Control for Power Plants.- Fuzzy Logic for Robots Calibration — Using Fuzzy Interpolation Technique in Modeless Robot Calibration.- Fuzzy Control on Manufacturing Welding Systems: To Apply Fuzzy Theory in the Control of Weld Line of PlasticInjection-Molding.