We present a state-space approach to design a passivity-based dynamic output feedback control of a finite collection of non-square linear systems. We first determine a squaring gain matrix and an additional dynamics that is connected to the systems in a feedforward way, then a static passivating (i.e. rendering passive) control law is designed. Consequently, the actual feedback controller will be the static control law combined with the feedforward dynamics. A necessary and sufficient condition for the existence of the parallel feedfornward compensator (PFC) is given by the static output feedback fomulation, which enables to utilize linear matrix inequality (LMI). The effectiveness of the proposed method is illustrated by some examples including the systems which can be stabilized by the proprotional-derivative (PD) control law.

We presents a new method of constructing an equivalent T-S fuzzy model by using the sum of products of linearly independent scalar functions from nonlinear dynamics. This method exactly expresses nonlinear systems and automatically determines the number of rules. We design a stabilizing controller f3r ul inverted pendulum system by using the concep of parallel distributed compensation (PDC) and linear matrix inequalities (LMIs) based on the proposed T-S fuzzy modeling method. We show effectiveness of a systematically designed fuzzy controller based on the proposed T-S fuzzy modeling method through the simulation and experiment of an inverted pendulum system.

A variable structure control (VSC) based model following control system that possesses fault detection and isolation (FDI) capability as well as fault tolerance property is proposed. The nonlinear part of the proposed control law. whose magnitude is determined by sliding variables, plays the role of suppressing fault effect. Thus, approximate fault reconstruction is also possible via the analysis of sliding variables. The proposed algorithm is applied to an active suspension system of pound vehicles to verify its applicability.

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

For robot navigation and visual reconstruction, structure from motion (SFM) is an active issue in computer vision community and its properties arc also becoming well understood. In this paper, when using stereo image sequence and direct method as a tool for SFM, we present a new method for overcoming bas-relief ambiguity. We first show that the direct methods, based on optical flow constraint equation, are also intrinsically exposed to such ambiguity although they introduce robust methods. Therefore, regarding the motion and depth estimation by the robust and direct method as approximated ones. we suggest a method that refines both stereo displacement and motion displacement with sub-pixel accuracy, which is the central process f3r improving its ambiguity. Experiments with real image sequences have been executed and we show that the proposed algorithm has improved the estimation accuracy.

Two methods of constructing T-S fuzzy model which is equivalent to a given nonlinear system are presented. The first method is to obtain an equivalent T-S fuzzy model by using the sum of linearly independent scalar functions with constant real matrix coefficients. The sum of products of linearly independent scalar functions is used in the second method. The former method is to formulate the procedures of T-S fuzzy modeling dealt in many examples of previous publications; the latter is a new method. By comparing the number of linearly independent functions used in the two methods, we can easily find out which method makes fewer rules than the other. The nonlinear dynamics of an inverted Pendulum on a cart is used as an equivalent T-5 fuzzy modeling example.

The electric power load during the peak time in summer is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system are possible solutions to settle this problem. In this study. the method of estimating temperature and humidity to forecast the cooling load of ice-storage system is suggested, then the method of forecasting the cooling load using fuzzy logic is suggested by simulating that the cooling load is calculated using actual temperature and humidity. The forecast of the temperature, humidity and cooling load are simulated, and it is shown that the forecasted data approach to the actual data. Operating the ice-storage system by the forecast of cooling load with night electric power will improve the ice-storage system efficiency and reduce the peak electric power load during the summer season as a result.

In a park or street, we can see many people jogging or walking with their dogs tracking their masters. In this study, an entertainment robot that imitates a dog's behavior is created. The robot's task is tracking a moving target that is recognized as the master. In order to design the robot, the ecological approach. in which the robot's goals and surroundings heavily influence its design, is used. A three-wheel type locomotion system is designed as the robot's physical structure which can follow a human jogging in outdoor space like a park. A sensor system which can detect the position of a master for the robot in the outdoor space, is developed. This sensor system consists of a signal transmitter which is at the hand of a master and some sensors which are mounted on the robot. The transmitter emits RF(radio frequency) and ultrasonic signals and the sensors detect the direction and distance from the robot to the transmitter by using the received signals. For the control architecture of the robot, a purely reactive behavior-based method is used in order to increase speed of response. The developed robot is evaluated through experiments conducted in indoor and outdoor environments.

Design method of a robust impedance control is proposed for the kinematically redundant manipulators. To achieve this objective, we first use the momentum feedback disturbance observer(MFDOB) scheme which can handle the nonlinear dynamics of a manipulator in Joint space. An extended task space formulation to describe the behaviors of task and null spaces of redundant manipulator is employed. Using the extended task space formulation and disturbance observer scheme, a robust impedance control method is designed. The performance of the proposed extended impedance controller is verified through experiments with a planar three links direct-drive manipulator.

We suggests an effective method to construct time-varying C-obstacles in the 3-dimensional configuration space (C-space) using free arc. The concept of free arc was defined mathematically and the procedure to find free arc in the case off-dimensional C-space was derived in [1]. We showed that time-varying C-obstacles can be constructed efficiently using this concept, and presented simulation results for two SCARA robot manipulators to verify the efficacy of the proposed approach. In this paper, extensions of this approach to the 3-dimensional C-space is introduced since nearly all industrial manipulators are reasonably treated ill the too or three dimensional C-space f3r collision avoidance problem The free arc concept is summarized briefly and the method to find lice arc in the 3-dimensional f-space is explained. To show that this approach enables us to solve a practical collision avoidance problem simulation results f3r two PUMA robot manipulators are presented.

We presents a modified variable dimension filter with input estimation for maneuvering target tracking. The conventional variable dimension filter with input estimation(VDIE) consists of the input estimation(IE) technique and the variable dimension(VD) filter. In the VDIE, the IE technique is used for estimation of a maneuver onset time and its magnitude in the least square sense. The detection of the maneuver is declared according to the estimated magnitude of the maneuver. The VD filter structure is applied for the adaptation to the maneuver of the target after compensating the filter parameter with respect to the estimated maneuver when the detection of the maneuver is declared. The VDIE is known as one of the best maneuvering target tracking filter based on a single filter. However, it requires too much computational burden since the IE technique is performed at every sampling instance and thus it is computationally inefficient. We propose another variable dimension filter with input estimation named 'Modified VDIE' which combines VD filter with If technique. Modified VDIE has less computational load than the original one by separating maneuver detection and input estimation. Simulation results show that the proposed VDIE is more efficient and outperforms in terms of computational load.

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. The proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.