This article describes a robust state estimation method which enables to produce reliable estimates in spite of heavy perturbation including plant uncertainty and external disturbances. The main idea is to combine the standard state estimator with the perturbation observer in the estimator frame. The perturbation observer reflects equivalent quantity of plant uncertainty and external disturbances during the estimation process so that the state estimator dynamics gets as close as possible to the real plant dynamics. The robust state estimator proposed in this paper is given in a recursive discrete-time form which is very useful fur implementation purpose. In terms of the error dynamics derived for the robust state estimator, we discuss the stability issue and noise sensitivity. The effectiveness and practicality of the robust state estimator are verified through numerical examples and experimental results.

Using a disturbance observer is effective in enhancing the performance of dynamic system in presence of disturbances. Although various types of disturbance observers have been proposed to improve sensitivity of systems, there exist poor transient responses due to cross-couplings among disturbance observer loops. In this paper, dual disturbance observer (DOB) is proposed to reduce the effects of the cross-couplings. A different type of loop transfer function is proposed for external disturbance observer. While improving the sensitivity function by adding external DOB, it also provides improved complementary sensitivity function. The proposed dual DOB is applied to a commercial optical disk drive tracking system. It is shown that the dual DOB is an effective method in rejecting the effect of disturbance as well as improving the tracking performance.

This paper deals with the problem of estimating the asymptotic stability region(ASR) of uncertain variable structure systems with bounded control. Using linear matrix inequalities(LMIs) we estimate the ASR and we show the exponential stability of the closed-loop control system in the estimated ASR. We show that our estimate is always better than the estimate of [3].

This paper presents experimental results of the frequency offset locking of He-Ne lasers and the stability analysis. The master laser is free running, and the slave laser is a single-mode operating laser. The frequency difference of two lasers is stabilized to 200 MHz which can be synchronized using PLL servo. The measured beat frequency between two lasers was 200.004 MHz ${\pm}$ 0.15 MHz. The square root of Allan variance as a measure of stability in time domain is also measured. The long-term stability of the beat was worse than sort-term stability. With a gate time $\tau=1000\;s$, the square root of Allan variance was about 1 GHz. The results of the square root of Allan variance of the stabilized beat signal was a gate time of $\tau=1000\;s$, the square root of Allan variance was about 1.5 kHz. The long-term stability was improved by more than several hundred times compared with that without the stabilization.

In this paper, a 4-wheel vehicle model including the effects of tire slip was considered, along with variable parameter sliding control, in order to improve the performance of the vehicle longitudinal response. The variable sliding parameter is made to be proportional to the square root of the pressure derivative at the wheel, in order to compensate for large pressure changes in the brake cylinder. A typical tire force-relative slip curve for dry road conditions was used to generate an analytical tire force-relative slip function, and an antilock sliding control process based on the analytical tire force-relative slip function was used. A retrofitted brake system, with the pushrod force as the end control parameter, was employed, and an average decay function was used to suppress the simulation oscillations. The simulation results indicate that the velocity and spacing errors were slightly larger than those obtained when the wheel slip effect was not considered, that the spacing errors of the lead and follower were insensitive to the adhesion coefficient up to the critical wheel slip value, and that the limit for the antilock control under non-constant adhesion road conditions was determined by the minimum value of the equivalent adhesion coefficient.

In this paper, an open architecture control system for automated container cranes is investigated. The hardware architecture for automating cranes is first discussed. A standard reference model for cranes based upon the OSACA platform is proposed, in which three modules are suggested: hardware module, operating system module, and application software module. Finally, a hybrid control system combining deliberative and reactive controls for autonomous operations of the cranes is implemented.

Strip off-center is one of the major problems in hot strip mill line. The key to good centering is having good equipment, modern control systems, excellent maintenance and an understanding of milling process. Therefore, this study aims to develop a system that is useful for quantitative analysis of strip off-center. In this study, the measuring method of strip off-center was thoroughly studied and the exclusive control board to line scan camera were designed. Also, the manipulated type housing for line scan camera was developed to adjust initial parameters for strip width and center line. In order to check the accuracy and usefulness of the developed system, FM stand in $\#2$ Hot Strip Factory in Pohang Steel Works was targeted.

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

We proposed a robust localization algorithm for mobile robots using LRF. A novel cost function for localization is suggested, which was used for calculating correct rotation angle and translation vector. We examined validity of our algorithm with various simulations and experiments, and also revealed robustness and accuracy compared to previous localization algorithms.

This paper deals with modeling and analysis fer the landing motion of a human-body model. First, the dynamic model of a floating human body is derived. The external impulse exerted on the ground as well as the internal impulse experienced at the joints of the human body model is analyzed. Second, a motion planning algorithm exploiting the kinematic redundancy is suggested to ensure stability in terms of ZMP stability condition during a series of landing phases. Four phases of landing motion are investigated. In simulation, the external and internal impulses experienced at the human joints and the ZMP history resulting from the motion planning are analyzed for two different configurations. h desired landing posture is suggested by comparison of the simulation results.

The multivariate statistical analysis methods, using both multiple linear regression(MLR) and partial least square(PLS), have been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PET) synthesis. On the basis of the set of data including the flow rate of water vapor, the flow rate of EG vapor, the concentration of acid end groups of a product and other operating conditions such as temperature, pressure, reaction times and feed monomer mole ratio, two multi-variable analysis methods have been applied. Their regression and prediction abilities also have been compared. The prediction results are critically compared with the actual plant data and the other mathematical model based results in reliability. This paper shows that PLS method approach can be used for the reasonably accurate prediction of a product quality of a direct esterification reactor in PET synthesis process.

In this paper, we implemented a web-based virtual laboratory system(VLab system) with creative and interactive multimedia contents, which can be used to enhance the quality of education in the area of digital logic circuits. Since the proposed VLab system is implemented to describe the on-campus laboratory, the learners can obtain similar experimental data through it. Also, the VLab system is designed to increase the learning and teaching efficiencies of both the learners and the educators, respectively. The learners will be able to achieve high teaming standard and the educators save their time and labor. The virtual experiments on our VLab system are performed according to the following procedure: (1) Circuit composition on the virtual bread board (2). Applying input voltage (3) Output measurements (4) Checkout of experiment results. Furthermore, the circuit composition on the virtual bread board and its corresponding online schematic diagram are displayed together on the VLab system for the learner's convenience. Finally, we have obtained several affirmative effects such as reducing the total experimental hours and the damage rate for experimental equipments and increasing learning efficiencies as well as faculty productivity.