In this paper, we fabricated the EM wave absorber for 94 GHz radar sensors using Permalloy of magnetic material with chlorinated polyethylene (CPE), and S-parameter was measured. The complex relative permittivity and permeability are calculated by the measured data. Absorption abilities are simulated according to different thickness of the EM wave absorbers, and the EM wave absorber was manufactured based on the simulated design. Simulated and measured results agree very well. As a result, we developed the EM wave absorber with the thickness of 1.15 mm which has an absorption ability of 18 dB at 94 GHz.

Development of the Electromagnetic Wave Absorber for 94 GHz Radar Sensors Using Permalloy

An anti-windup controller for multi-input nonlinear system is proposed in this paper. The proposed method does not need to calculate every time for every fuzzy rules comparing with traditional linear pole placement of T-S(Takagi-Sugeno) fuzzy. This means fewer LMIs(linear matrix inequality) will be needed and its solution will be guaranteed as much as possible. For different saturation limit, different D-stable disk center and radius of pole placement can be selected to eliminate input saturation effect directly. Nonlinear system will be transferred to T-S fuzzy model first. Then, by employing a series of transition matrix, nonlinear system will be transferred into a nearly linear format accompanied by a nonlinear part. Finally, by designing a proper controller, linear pole placement method can be used and the controller gains can be calculated out with LMIs.

Linear pole-placement anti-windup control for input saturation nonlinear system based on Takagi Sugeno fuzzy model

The limited number of roads and the increasing number of vehicles demand the automatic regulation of overspeed vehicles, illegal vehicles, and overloaded vehicles and the automatic charge calculation depending on the type of the vehicle. To meet such requirements, it is important to remove the shadow of the vehicle as processing and recognizing an image captured by a camera. The shadow of the vehicle is likely to cause misclassification of the vehicle type due to diverse errors and mistakes occurring when detecting geometrical properties of the vehicle. In case that shadows of two different vehicles are overlapped, not only the type of the vehicles may be misclassified but also it is difficult to accurately identify the type of the vehicles. In this paper, we propose a robust algorithm to remove the shadow of a vehicle by calculating the luminance, the chrominance, the gradient density of the cast shadow from information acquired using the image subtraction of the background, and to recognize the substantial vehicle figure. Even when it is hard to detect and split a target vehicle from its shadow as shadows of vehicles are attached to each other, our robust algorithm can detect the vehicle figure only. We implemented our system with a general camera and conducted experiments on various vehicles on general roads to find out our vehicle shade removal algorithm is efficient when detecting and recognizing vehicles.

Vehicle Shadow Removal For Intelligent Traffic System

Considering input saturation problem of nonlinear system, a linearized model of multi-inputs nonlinear system is proposed in this paper. The final linear model has prescribed poles and has the same convergence nearby the designed equilibrium points. After this, the linear control theorem can be applied. During the calculation of linearization, T-S (Takagi Sugeno) fuzzy model and pole placement method were utilized. Pole placement just was applied only once for the final model comparing the traditional case where it was designed for every fuzzy rule. This means fewer LMIs (linear matrix inequality) will be needed and its solution will be guaranteed as much as possible. In this paper, nonlinear system will be transferred to T-S fuzzy model first. Note that the T-S fuzzy model is still nonlinear. Then, by employing a series of transfer matrix, nonlinear T-S fuzzy model will be transferred into a nearly linear form accompanied with only one nonlinear part. Finally, by designing a proper controller, linear pole placement method is used and the designed linearization controller gains can be calculated out with LMIs.

Feedback Linearization for Input-saturation Nonlinear System Based on T-S Fuzzy Model

We have investigated the spectral characteristics of the semiconductor lasers locked to the sidebands of the master laser in this paper, which were expressed by a series of the Bessel function. The numerical model for the semiconductor lasers based on the typical Lang's equation has been extended in order to take into account the simultaneous injection of the multiple sidebands of the directly modulated ML. We analyses characteristics of direct intensity modulation.

Analyses of Characteristics for Direct Intensity Modulation Scheme

In this paper, the adaptive fuzzy logic controller(AFLC) is proposed, which uses real-coding genetic algorithm showing a good performance on convergence velocity and diversity of population among evolutionary computations. The effectiveness of the proposed AFLC was demonstrated by computer simulation for speed control system of AC servo motor. As a result of simulation for the AC servo motor, it is shown the proposed AFLC has the better performance on overshoot, settling time and rising time than the PI controller which is used when tuning AFLC.

Design of Adaptive Fuzzy Logic Controller for Speed Control of AC Servo Motor

In this paper, a sliding mode control method with uncertainty adaptation is proposed by introducing the virtual state. Because upper bound of the uncertainty is very difficult to know, we estimate this by using the simple adaptation law and design the sliding surface which has dynamic of nominal system. An optimal controller is used by nominal controller. And if initial values of the virtual state are chosen properly, the reaching phase is removed.

Design of Sliding Mode Controller with Uncertainty Adaptation

Linearization of T-S fuzzy model is difficult to be achieved by using existing linearization methods because fuzzy rules and membership functions are included in T-S fuzzy models. In this paper, a new linearization method is proposed for discrete time T-S fuzzy system based on the properties of T-S fuzzy theorem. The local linear models of a T-S fuzzy model are transformed to a controllable canonical form respectively, and their T-S fuzzy combination results in a feedback linearizable T-S fuzzy model. Based on this model, a nonlinear state feedback linearizing input is determined. Nonlinear states transformation is inferred from the linear state transformations for the controllable canonical form. The proposed method is more intuitive and easier to understand mathematically compared to the well-known feedback linearization technique which requires a profound mathematical background. The feedback linearizable condition of this paper is also weakened compared to the conventional feedback linearization.

Linearization of discrete-time T-S fuzzy model with multiple input

The present invention relates to an automatic inspection device for a solenoid core. The automatic inspection device for a solenoid core comprises: an input module (11) where a plurality of solenoid cores (SC) are stacked, and which leads the stacked solenoid cores to pass through a corner part through an inducement path (111) to move in a line; a loader module (12) which is placed at the end part of the inducement path (111) in order to detect and move each of the SC; an inspection guide module (15) including an inspection path (151) which induces the movement of the plurality of SC, transferred by the loader module (12), along a predetermined path; an inspection module including a plurality of inspection units (131-142) which inspect each of the SC placed in the inspection path (151); and a transfer module (16) which moves the plurality of SC to a preset position at the same time along the inducement path (111). Therefore, the automatic inspection device for a solenoid core can automatically and continuously inspect various specifications required for cores of a large quantity of solenoid valves.

An Apparatus for Inspecting a Solenoid Core Automatically

This paper derives a novel nominal state relationship (NSR) by using support vector machines (SVM). By using the NSR, a novel sliding surface which has the dynamics of a nominal system controlled by pole placement is proposed. The sliding mode control (SMC) with this novel sliding surface gives its robustness to pole placement control systems with uncertainties.

Gun Pyong Kwak

Papers

Design of Adaptive Fuzzy Logic Controller for Speed Control of AC Servo Motor

Design of Sliding Mode Controller with Uncertainty Adaptation

Linearization of discrete-time T-S fuzzy model with multiple input

An Apparatus for Inspecting a Solenoid Core Automatically

Nominal State Relationship with Support Vector Machines and Its Sliding Mode Control Application