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The accuracy of contour tracking is an important issue to be addressed for the X‐Y stage in a machining tool. Applying a better control scheme can help to increase the tracking accuracy with the effects of systems' uncertainties, nonlinearities and disturbances. In this paper, to prevent these negative effects and achieve high accuracy tracking control of the two‐axis motion stage, the adaptive fuzzy wavelet neural network (AFWNN) PI sliding mode controller is proposed. The adaptive algorithm is combined with the basis function of the wavelet neural network and fuzzy system to approximate the plant model functions. Then, the controller with PI sliding mode structure could be built based on the estimated system function. In this method, the time domain positioning property of wavelet and the reasoning of the fuzzy system could provide the well‐estimated plant model. Moreover, the adaptive algorithm and sliding mode control scheme help to reduce the effects of parameter variation and uncertainties. The stability is analyzed via Lyapunov stability theorem to prove the asymptotic stability of the system. In the simulation and experimental results, the contours are planned through the nonuniform rational B‐spline (NURBS), which is considered a high accuracy interpolator. The tested curves consist of circle, bow, heart, star and trident. The average and standard deviations of the tracking errors are compared to other methods to illustrate the performance of the proposed method. The results demonstrate that the method can reduce errors more effectively and have better localization for trajectory tracking. [ABSTRACT FROM AUTHOR]

The accuracy of contour tracking is an important issue to be addressed for the X‐Y stage in a machining tool. Applying a better control scheme can help to increase the tracking accuracy with the effects of systems' uncertainties, nonlinearities and disturbances. In this paper, to prevent these negative effects and achieve high accuracy tracking control of the two‐axis motion stage, the adaptive fuzzy wavelet neural network (AFWNN) PI sliding mode controller is proposed. The adaptive algorithm is combined with the basis function of the wavelet neural network and fuzzy system to approximate the plant model functions. Then, the controller with PI sliding mode structure could be built based on the estimated system function. In this method, the time domain positioning property of wavelet and the reasoning of the fuzzy system could provide the well‐estimated plant model. Moreover, the adaptive algorithm and sliding mode control scheme help to reduce the effects of parameter variation and uncertainties. The stability is analyzed via Lyapunov stability theorem to prove the asymptotic stability of the system. In the simulation and experimental results, the contours are planned through the nonuniform rational B‐spline (NURBS), which is considered a high accuracy interpolator. The tested curves consist of circle, bow, heart, star and trident. The average and standard deviations of the tracking errors are compared to other methods to illustrate the performance of the proposed method. The results demonstrate that the method can reduce errors more effectively and have better localization for trajectory tracking. [ABSTRACT FROM AUTHOR]

In this study, the authors present a control method for the permanent magnet synchronous motor (PMSM) driven X–Y motion system for application in industrial and manufacturing apparatus. Backlash and friction effects in ball‐screw actuated systems are common obstacles to achieve high‐accuracy control. The authors investigate the indirect fuzzy controller to demonstrate the feasibility of reference trajectory tracking and derive an adaptive law in the error state space to deal with parameter uncertainties and external disturbances. The authors adjust the fuzzy parameters online, based on the Lyapunov stability theorem, such that the asymptotic stability of the whole system and error convergence can be guaranteed. In the authors' experiments, this indirect fuzzy control approach compensated for the non‐linear friction and disturbance variation of the biaxial linear stage following the application of four contour shapes, i.e. square, triangular, star, and circular reference contours. Both the authors' simulation and experimental results demonstrate substantial improvement in contour tracking performance in terms of average tracking error and tracking error standard deviation, as well as robustness against platform uncertainties. [ABSTRACT FROM AUTHOR]

The microwave dielectric constants of ceramic dispersions in the polyethylene matrix are studied by five well-known mixture equations in this article. Three ceramic powders of fillers with various dielectric constants at 10 GHz are investigated. The experimental dielectric constant values of the mixtures are compared to the theoretical curves of the five mixing rules. The dielectric constants of pure ceramics are then estimated by these mixing laws from the dielectric constants of composites of various filler concentrations. The theoretical errors of estimations of rules are derived and analyzed. The most adequate mixture law(s) for measuring the dielectric constants of ceramic fillers will be recommended. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2481-2485, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26357 [ABSTRACT FROM AUTHOR]