Pi-Cheng Tung

A self-tuning fuzzy PID-type controller design for unbalance compensation in an active magnetic bearing

This paper presents a design for a fuzzy gain tuning mechanism dealing with the problem of unbalanced vibration problem in an active magnetic bearing (AMB) system. For the purpose of enhancing the performance of the AMB system, we replace the conventional proportional-integral-derivative (PID) controller with a self-tuning fuzzy PID-type controller (FPIDC). The shaft displacement and the unbalanced forces of the rotor are evaluated by model-based observation. If there are model uncertainties in the rotor system or nonlinearities in the magnetic bearing system, this observer may not work well at any operating speed. A fuzzy gain tuner is added to adjust the actuating signal of the self-tuning FPIDC in order to overcome the disturbances and suppress the unbalancing vibration. The experimental results show that the proposed scheme allows for a remarkable improvement in reducing vibration in an unbalanced AMB system as well as demonstrate an efficient reduction in the shaft displacement of the rotor.

A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition

Recently, in a task of face recognition, some researchers presented that independent component analysis (ICA) Architecture I involves a vertically centered principal component analysis (PCA) process (PCA I) and ICA Architecture II involves a whitened horizontally centered PCA process (PCA II). They also concluded that the performance of ICA strongly depends on its involved PCA process. This means that the computationally expensive ICA projection is unnecessary for further process and involved PCA process of ICA, whether PCA I or II, can be used directly for face recognition. But these approaches only consider the global information of face images. Some local information may be ignored. Therefore, in this paper, the sub-pattern technique was combined with PCA I and PCA II, respectively, for face recognition. In other words, two new different sub-pattern based whitened PCA approaches (which are called Sp-PCA I and Sp-PCA II, respectively) were performed and compared with PCA I, PCA II, PCA, and sub-pattern based PCA (SpPCA). Then, we find that sub-pattern technique is useful to PCA I but not to PCA II and PCA. Simultaneously, we also discussed what causes this result in this paper. At last, by simultaneously considering global and local information of face images, we developed a novel hybrid approach which combines PCA II and Sp-PCA I for face recognition. The experimental results reveal that the proposed novel hybrid approach has better recognition performance than that obtained using other traditional methods.

EXPERIMENTAL AND ANALYTICAL STUDY OF DITHER SIGNALS IN A CLASS OF CHAOTIC SYSTEMS

Abstract A method for controlling a class of chaotic systems by injecting another external input, called a dither signal, into the systems, just ahead of the nonlinearities is given. The method is robust to measurement noise due to no state being fed back and applicable to experimental situations in which the system parameters are unknown and unalterable. Two numerical examples and one experimental test are performed to demonstrate the feasibility of the method.

Robust control for a class of nonlinear oscillators with chaotic attractors

Abstract An approach using the sliding mode control theory to control a class of nonlinear oscillators with a chaotic attractor is presented. It can control chaotic motion not only to a steady state but also to a desired periodic orbit. Especially, the method is easy to implement and does not require the exact dynamics model in advance.

Application of a rule self-regulating fuzzy controller for robotic deburring on unknown contours

Most metal parts made by machining operations contain burrs, which can be removed by robotic manipulators. Modeling a deburring robot on unknown contours is a relatively difficult task. In this study, we present a novel compliant motion controller that uses a modified on-line rule self-regulating fuzzy control (RSFC) and depends on no mathematical models. In the proposed controller, a Cartesian robot on which a grinding tool is mounted rigidly performs edge following (precision deburring) and chamfering on unknown contours. The manipulator is controlled along the tangential direction of a constrained surface and its cutting force is maintained at a desired level. Experimental results demonstrate the effectiveness of this control strategy in terms of automatically deburring the edges of parts with an unknown geometrical configuration.

CONTROLLING CHAOS VIA STATE FEEDBACK CANCELLATION UNDER A NOISY ENVIRONMENT

Abstract Combining a linear Kalman estimator (filter) and a feedback cancellation of the nonlinear system terms, the approach of engineer control can effectively govern a noisy chaotic system. The methodology is easy to comprehend and to implement, but previous knowledge of the system dynamics is needed.

Design of model-based unbalance compensator with fuzzy gain tuning mechanism for an active magnetic bearing system

This paper deals with the unbalanced vibration problem of a stabilized active magnetic bearing (AMB) system. First, a model-based integral-type observer is proposed to evaluate the shaft displacement and the unbalancing forces of the rotor of an AMB system controlled by a proportional-integral-derivative (PID) controller. A fuzzy gain tuning mechanism is added to adjust the output of the PID controller in order to overcome the disturbances and suppress the unbalancing vibration. We have shown via simulation that the addition of the integral-type force observer improves the rotating accuracy in the device operating range. The experimental results demonstrate an efficient reduction of the shaft displacement of the rotor. Thus, the proposed scheme allows for a remarkable improvement in the unbalanced vibration of an AMB system over conventional PID controls without fuzzy gain tuning mechanism.

Application of the differential geometric method to control a noisy chaotic system via dither smoothing

Abstract The differential geometric method essentially requires a smooth field in a system model. It cannot be applied to a chaotic system that has a continuous but undifferentiable nonlinearity, e.g., Chuas circuit. This drawback is removed via dither smoothing techniques; then, the controlled system may work for previously unworkable nonlinearities.

Application of fuzzy on-line self-adaptive controller for a contour tracking robot on unknown contours

Abstract Modelling a contour tracking robot on unknown contours is a relatively difficult task. Therefore, a new compliant motion controller is developed in this study by applying the on-line rule-adaptive fuzzy control to have a Cartesian manipulator perform contour tracking on unknown contours. Also, the contact force is controlled here within a certain constant value and the manipulator is controlled along the tangent direction in which the manipulator is unconstrained. Experimental results verify the feasibility of our designed control strategy.

Modified Smith predictor with a robust disturbance reduction scheme for linear systems with small time delays

This paper presents a robust disturbance reduction scheme using an artificial neural network (ANN) for linear systems with small time delays. It is assumed that the nominal linear systems are stable, minimum phase and relative degree one systems. The proposed structure is an integration of a modified Smith predictor and an ANN-based disturbance reduction scheme. Unlike other disturbance rejection methods, the proposed approach does not require information about unknown load disturbance frequencies. An ANN is used to approximate the unknown load disturbances and to enhance the robustness of the proposed disturbance reduction scheme against modelling errors in the estimated time delay and the process model. Connective weights of the ANN are trained on-line using a back-propagation algorithm until uncertainties resulting from unknown load disturbances and modelling errors are minimized. The simulation results show the effectiveness of the presented disturbance reduction scheme for controlling linear delay systems subjected to step or periodic unknown load disturbances.