This paper presents a control of active suspension for quarter car model with two degree of freedom by using H$\infty$ method. Absolute velocity of car body is measured for feedback. The system parameter variations are treated with multiplicative uncertainty model. Simulation results show that the H$\infty$ control provides good trade-off between ride quality, suspension packaging and road holding constraints. The experiment with a front wheel suspension system was done to verify the simulation results.

A new speech enhancement algorithm for speech corrupted by slowly varying additive colored noise is suggested based on a state-space signal model. Due to the FIR structure and the unimportance of long-term past information, the receding horizon (RH) FIR filter known to be a best linear unbiased estimation (BLUE) filter is utilized in order to obtain noise-suppressed speech signal. As a special case of the colored noise problem, the suggested approach is generalized to perform the single blind signal separation of two speech signals. It is shown that the exact speech signal is obtained when an incoming speech signal is noise-free.

In this paper, an Adaptive Evolutionary Computation(AEC) is proposed. AEC uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner is order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. AEC is used to design the membership functions and the scaling factors of fuzzy logic controller (FLC). To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC series motor system with nonlinear characteristics. Experimental results show that the proposed controller has better performance than that of PD controller.

In this paper, we deal with the problem of designing guaranteed cost state feedback controller for the generalized time-varying delay systems with delayed state and control input. The generalized time delay system problems solved on the basis of LMI(linear matrix inequality) technique considering time-varying delays. The sufficient condition for the existence of controller and guaranteed cost state feedback controller design methods are presented. Also, using some changes of variables and Schur complements, the obtained sufficient condition can be reformulated as LMI forms in terms of transformed variables. Therefore, all solutions of LMIs, guaranteed cost controller gain, and guaranteed cost are obtained at the same time. The proposed controller design method can be extended into the problem of robust guaranteed cost controller design method for parameter uncertain systems with time-varying delays easily.

The aim of this paper is to describe an advanced method of the fault diagnosis using Control Theory with reference to a crack detection, a new way to localize the crack position under influence of the plant disturbance and white measurement noise on a rotating shaft. As the first step, the shaft is physically modelled with a finite element method as usual and the dynamic mathematical model is derived from it using the Hamilton-principle and in this way the system is modelled by various subsystems. The equations of motions with a crack are established by the adaption of the local stiffness change through breathing and gaping[1] from the crack to the equation of motion with an undamaged shaft. This is supposed to be regarded as a reference system for the given system. Based on the fictitious model of the time behaviour induced from vibration phenomena measured at the bearings, a nonlinear state observer is designed in order to detect the crack on the shaft. This is the elementary NL-observer(EOB). Using the elementary observer, an Estimator(Observer Bank) is established and arranged at the certain position on the shaft. In case, a crack is found and its position is known, the procedure, fro the estimation of the depth is going to begin.

We present a robust and reliable H$\infty$ state-feedback controller design for linear uncertain systems, which have norm-bounded time-varying uncertainty in the state matrix, and their prespecified sets of actuators are susceptible to failure. These controllers should guarantee robust stability of the systems and H$\infty$ norm bound against parameter uncertainty and/or actuator failures. Based on the linear matrix inequality (LMI) approach, two state-feedback controller design methods are constructed by formulating to a set of LMIs corresponding to all failure cases or a single LMI that covers all failure cases, with an additional costraint. Effectiveness and geometrical property of these controllers are validated via several numerical examples. Furthermore, the proposed LMI frameworks can be applied to multiobjective problems with additional constraints.

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

Majority of industrial robots are controlled by a simple independent joint control of joint actuators rather than complex controllers based on the nonlinear dynamic model of the robot manipulator. In this independent joint control scheme, the performance of actuator control is influenced significantly by the joint disturbance torques including gravity, Coriolis and centrifugal torques, which result in the trajectory tracking error in the joint control system. The control performance of a redundant manipulator under independent joint control can be improved by minimizing this joint disturbance torque in resolving the kinematic redundancy. A 3 DOF planar robot is studied as an example, and the dynamic programming method is used to find the globally optimal joint trajectory that minimize the joint disturbance torque over the entire motion. The resulting solution is compared with the solution obtained by the conventional joint torque minimization, and it is shown that joint disturbance can be reduced using the kinematic redundancy.

Fixtures are used in almost all phases of machining and assembly to position and hold a part accurately. The class of fixture which consists of 3 locators and 1 clamp(3L/1C) is known as the minimal set that can provide form closure which is a kinematic constraint condition for preventing all planar motions. This type of fixtures has advantages in terms of the number of fixture elements required, the time for clamping, and so on. However it is not widely used in industry because reliable loading scheme has not been reported. In this paper, we propose a method to load the class of 3L/1C fixtures using compliant motions. The planner is developed for synthesizing compliant motions to achieve precise final fixture configuration in the presence of sensing and control uncertainties. A novel approach to eliminate uncertainty in part orientation by adding one extra fixture element called an aligning pin is proposed.

The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about 100m underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the array of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. In the hybrid method, both informations of time-delays and power-ratios are coupled together to produce better performance of position estimation. A new acoustic imaging technique has been developed for improving the hybrid method. This new acoustic imaging method shows the multi-dimensional distribution of the normalized cost function, so as to indicate the trend of the minimizing direction toward the source location. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is 28m for a search area of radius 250m.

A measurement technique of a sea height of burst is introduced for a proximate test using the image recognition of video cameras. In the burst of fuse on the ocean, the burst center of fuse, the sea surface level and the height of calibration poles are measured by the process of image obtained from cameras. Finally, the height of burst of fuse can be computed by Hough transform algorithm. The error compensation algorithms are proposed to eliminate the errors caused by camera level and environmental parameters. As a result of experiment, it has been proved that the proposed measurement system shows the recognition of the center point of the burst image with ${\pm}$0.5m error.