This paper proposed an adaptive robust sliding mode control (SMC) with a nonlinear sliding perturbation observer (SPO) for robot manipulators. SPO estimates the perturbation (nonlinearities, uncertainties, and disturbances) with minimal system information and enhances the controller performance. The estimation is mainly dependent on the selection of SMCSPO gain, and if not tuned well, it might result in increased error dynamics of the system. Therefore, minimizing the error dynamics by improving the estimation is the primary goal of this research. In this regard, the current study accomplishes adaptation of controller gain in real-time by using an optimization technique called extremum seeking (ES). The quality adaptation is controlled with the help of a cost function. Based on the Lyapunov-based stability analysis of SMCSPO, the cost function consisting of the estimation error of the observer and error dynamics is proposed. The unique cost function now guarantees the tracking performance within the defined error tolerance. The effectiveness of the proposed algorithm is illustrated and validated in simulation and experiments. It is shown that the adaptation based on ES with the proposed cost function converges to the optimal control gain enabling the reduced estimation error and error dynamics with enhanced tracking performance.

In this paper, proposed a reaction force estimation and bilateral control of master slave manipulation in hydraulic servo system based on Sliding mode control with sliding perturbation observer (SMCSPO). The reaction force is estimated by sliding perturbation observer (SPO) without using any force sensor. The estimated reaction force without force sensor is transmitted to the master device using the impedance model controller. Sliding mode control (SMC) is used to a bilateral controller for the position and force tracking control of a slave. This study proves in experiment that the slaver of a hydraulic servo system can follow the trajectory of the master device (Human Command) using the bilateral control scheme.

We fabricated poly-Si thin-film transistors at 150/spl deg/C using inductively coupled plasma (ICP) chemical vapor deposition (CVD) and excimer laser annealing (ELA). An Si film deposited by ICP-CVD was recrystallized using ELA, and a poly-Si film with large grains exceeding 5000 /spl Aring/ in diameter was fabricated. An SiO/sub 2/ film with a high breakdown field was deposited by ICP-CVD. A high mobility exceeding 100 cm/sup 2//Vs and a low subthreshold swing of 0.76 V/dec were successfully achieved.

Proposes a self tuning fuzzy inference method based on genetic algorithms for the fuzzy-sliding mode control of a robot. Using this method the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method, and it is guaranteed that the selected solution becomes the global optimal solution by optimizing Akaike's information criterion. A trajectory tracking experiment with the automatic polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

A vehicle driving simulator is a virtual reality device in which a human being is able to feel as if they are actually driving a vehicle. The driving simulator consists of a motion platform, a driving operating system, a motion controller, a visual and audio system, a vehicle dynamic analysis system, etc. In this paper, the main procedures in the development of a driving simulator are classified as follows: 1) a motion platform and a motion controller, which can track a reference trajectory, were developed; 2) a new washout algorithm to realize the motion of an actual vehicle in the driving simulator was developed, and this algorithm enables one to change the real motion space of a vehicle into the workspace of the driving simulator; and 3) a visual and audio system for a more realistic feeling were developed. Finally, an integration system to communicate and monitor among the subsystems was developed. The performance evaluation of the developed Pusan National University vehicle driving simulator (PUNVDS) was carried out.

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a polishing robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method, and it is guaranteed that the selected solution become the global optimal solution by optimizing Akaike's information criterion expressing the quality of the inference rules. Also, trajectory tracking simulation shows that the optimal fuzzy inference rules by the genetic algorithm are automatically selected and the trajectory control result is almost similar to the result which uses the inference rules to be selected through the trial and error method by an expert. Therefore, although a designer is a non-expert of robot systems, the fuzzy-sliding mode controller can be designed by the proposed self tuning fuzzy inference method based on the genetic algorithm.

Polishing work of a freely-curved surface die demands simple and repetitive operations but requires a considerable amount of time for high precision. Some workers tend to gradually avoid the polishing work because of the poor environment caused by dust and noise. In order to reduce the polishing time and solve the problem of the shortage of skilled workers, an automatic polishing system should be developed. In this study, a user-friendly automatic polishing system was developed. It is composed of two different systems: a three-axis machining center and a two-axis polishing robot. The developed polishing system with five degrees of freedom is able to keep the polishing tool normal to the die surface. In order to operate the polishing system, the host computer should transmit the polishing data to the FANUC controller of the machining center and DSP controller of the polishing robot, respectively. A driving program (P-PROS: Pusan National University-polishing robot operating system) in the Windows environment was developed to easily operate the polishing robot system. A communication program was developed for transmitting the polishing data to each controller. To evaluate the performance of the P-PROS and the developed DSP (digital signal processing) controller, a polishing experiment on the shadow-mask die was done.