Tae-Il Seo

Establishing ANFIS and the use for predicting sliding control of active railway suspension systems subjected to uncertainties and disturbances

The effectiveness of control of the active railway suspension system (ARSS) using a magnetorheological damper (MRD) with unknown track profile and load depends deeply on (1) the control strategy and the ability to adapt to noise, (2) system’s response delay compared with the real status of track profile impacting on it, and (3) uncertainty of the model used to describe the ARSS and external disturbance. Deriving from these, in order to improve the control efficiency, in this paper, we focus on three following factors. The first is to improve the accuracy of the MRD model. The second is to establish the ability to predict the track-profile’s status to update adaptively the optimal parameters of the control system. Finally, it is to build an uncertainty and disturbance observer (DUO) to compensate for noise. A novel algorithm for fuzzy C-means clustering (FCM) in an overlapping data space deriving from the Kernel space and the data potential field named PKFCM is proposed. Based on the PKFCM, the inverse MRD model is established as well as the design of a fuzzy-based predicting sliding controller (FPSC) for the ARSS is performed which is always updated by the optimal parameters adapting to the status of track profile. The stability of the FPSC is proved theoretically while its performance is estimated by numerical surveys.

ANFIS deriving from jointed input-output data space and applying in smart-damper identification

Display Omitted Reflecting the relation between the convergent capability of ANFIS and especial features of the created cluster data space.Providing solutions for improving the convergent ability of ANFIS.Proposing an improved-configuration for ANFIS.Proposing a novel algorithm for building ANFIS.Establishing smart damper models based on ANFIS. For approximation of unknown mapping f: XY expressing a given database via an adaptive Neuro-Fuzzy inference system (ANFIS), ANFISs convergent capability is quite sensitive to the data features. In order to deal with this, this paper focus on ameliorating quality of cluster data space (CDS) used to establish the ANFIS. Firstly, we formulate and prove CDS-related necessary conditions for an approximation expressing an initial data space (IDS) convergent. Based on this theory basis, we propose a fuzzy system typed ANFIS associated with two solutions for establishing the CDS from the IDS, which focus on preventing, seeking and exterminating critical data samples in the CDS. In order to deploy these, we also present an improved structure of ANFIS. These aspects are described via a novel offline identification algorithm named ANFIS-JS for building ANFIS in a jointed input-output data space (JDS) deriving from the IDS. The results obtained via several surveys, including identifying smart dampers, magnetorheological damper (MRD) and electrorheological damper (ERD), show that the convergent stability and response accuracy are the main advantages of the ANFIS-JS.

Recurrent Mechanism and Impulse Noise Filter for Establishing ANFIS

In many real applications, building and updating adaptive neuro-fuzzy inference system (ANFIS) based on noisy measuring data sources need to be performed such that the filtering impulse noise (IN) from the initial datasets (IDSs) and establishing the ANFIS via the filtered IDS are carried out simultaneously. Focused on this purpose, in this paper, a novel recurrent mechanism as well as a solution for filtering IN based on Lyapunov stability theory is proposed to establish an adaptive online IN filter (AOINF). Using the AOINF, kernel fuzzy-C-means clustering method, and the least mean squares method, a cluster data space deriving from the filtered IDS is created to which the ANFIS is then formed. The recurrent mechanism executes filtering IN to build ANFIS and using the ANFIS as an updated-filter to filter IN synchronously until either the ANFIS converges to the desired accuracy or a stop condition is satisfied. Surveys, including identifying dynamic response of a magnetorheological damper via measuring datasets, are performed to evaluate the proposed method.

Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator

It is difficult to efficiently control nonlinear systems in the presence of uncertainty and disturbance (UAD). One of the main reasons derives from the negative impact of the unknown features of UAD as well as the response delay of the control system on the accuracy rate in the real time of the control signal. In order to deal with this, we propose a new controller named CO-FSMC for a class of nonlinear control systems subjected to UAD, which is constituted of a fuzzy sliding mode controller (FSMC) and a fuzzy-based compensator (CO). Firstly, the FSMC and CO are designed independently, and then an adaptive fuzzy structure is discovered to combine them. Solutions for avoiding the singular cases of the fuzzy-based function approximation and reducing the calculating cost are proposed. Based on the solutions, fuzzy sliding mode technique, lumped disturbance observer and Lyapunov stability analysis, a closed-loop adaptive control law is formulated. Simulations along with a real application based on a semi-active train-car suspension are performed to fully evaluate the method. The obtained results reflected that vibration of the chassis mass is insensitive to UAD. Compared with the other fuzzy sliding mode control strategies, the CO-FSMC can provide the best control ability to reduce unwanted vibrations.

Prediction of Cutting Force and Tool Deflection in Micro Flat End Milling

because this model is relatively simple. Finite element method was used to predict tool deflection based on predicted cutting forces. Predicted tool deflection amounts and actual machined profiles were compared each other in order to check out the differences between them.

Reverse engineering for rapid prototyping of 3D compound surfaces using edge detection and delaunay triangulation method

The objective of this research is to develop an efficient reverse engineering method of 3-dimensional compound surfaces for rapid prototyping processes. As a first step, the image-processing techniques were applied to scanned data obtained using a laser scanner for edge detection. Based on the detected edges, the boundary information of the compound surface was extracted in order to divide the surface into several separate regions. As a next step, the Delaunay triangulation method was applied in order to independently reconstruct the surface on the basis of the scanned data and the boundary information. Finally, STL files were created for the rapid prototyping process. Required simulations and experiments were performed and the results were analyzed to show the effectiveness of the proposed methods.

Novel fuzzy sliding controller for MRD suspensions subjected to uncertainty and disturbance

In this paper, the design of an adaptive optimal fuzzy sliding controller (AOFSC) for semi-active magnetorheological damper (MRD) vehicle suspension system subjected to uncertainty and disturbance (UAD) whose time-varying rate may be high but bounded is presented. This is a combination of an adaptive optimal fuzzy sliding mode controller (FSMCop), a nonlinear disturbance observer (NDO) and an inverse MRD model to create the desired control force, including the compensation part for UAD. An adaptive control law is proposed to establish a fuzzy-gain update law for the AOFSC and a parameter tie for the NDO such that the convergence of systems dynamic response is a Lyapunov asymptotically stable process. Surveys via simulations along with via an experimental apparatus showed that the high capability to exterminate vibration, robust stability, and the economic efficiency are the main advantages of the proposed AOFSC. Structure and operating principle of the controller AOFSC, in which (t1) and (t) respectively denote the previous and present loop.Display Omitted Designing the NDO for compensating for external disturbance.Designing the FSMCop.Establishing the parameter ties between the update laws of the FSMCop and NDO.An application of the proposed method to a real MRD suspension system.

Durability Characteristics Analysis of Plastic Worm Wheel with Glass Fiber Reinforced Polyamide

Plastic worm wheel is widely used in the vehicle manufacturing field because it is favorable for weight lightening, vibration and noise reduction, as well as corrosion resistance. However, it is very difficult for general plastics to secure the mechanical properties that are required for vehicle gears. If the plastic resin is reinforced by glass fiber in the fabrication process of plastic worm wheel, it is possible to achieve the mechanical properties of metallic material levels. In this study, the mechanical characteristic analysis of the glass-reinforced plastic worm wheel, according to the contents of glass fiber, is performed by analytic and experimental methods. In the case of the glass fiber-reinforced resin, the orientation and contents of glass fibers can influence the mechanical properties. For the characteristic prediction of plastic worm wheel, computer-aided engineering (CAE) analysis processes such as structural and injection molding analysis were executed with the polyamide resin reinforcement glass fiber (25 wt %, 50 wt %). The injection mold for fabricating the prototype plastic worm wheel was designed and made to reflect the CAE analysis results. Finally, the durability of prototype plastic worm wheel fabricated by the injection molding process was evaluated by the experimental method and the characteristics according to the glass fiber contents.

Design and fabrication of multi-cavity injection mold using hot runners and direct edge gates

A hot runner system can provide many advantages to plastic injection mold engineers for improving product quality. In edge gate systems in particular, the gate traces can appear on the side of products rather than the top. However, it is difficult to establish hot runner systems using edge gates because of their structural differences from conventional gate systems. This article presents the entire process of preparing a 48-cavity plastic injection molding system with edge gates. This process consists of 48-cavity injection mold design, structural analysis, verification of design plans, filling analysis of multi-cavity, cooling channel design on the basis of cooling analysis, fabrication of the mold system, and test injection. All presented computer-aided engineering analyses were conducted using ANSYS and MoldFlow.

A Development and Estimation about Flexible Rod for Flexibility of Pedicle Screw System

In this paper, it is analyzed about the mechanical characteristics of pedicle screw system which is a artificial implant for surgery to treatment serious lumbar vertebra diseases. The disk of lumbar vertebra to be fixed by pedicle screw system shows regressive phenomena. But if flexible rod, to give a flexibility(under 6 degree) to fixable disk is applied, it can protect against the degeneration of disk. This research is carried out a mechanical characteristic of pedicle screw system used flexible rod through finite elements analysis, and then flexible rod system was verified about safe movement through compression, tension and torsion test which is the pedicle screw system official recognition test(ASTM F 1717).