This paper presents an obstacle detection algorithm based on the consecutive and the cooperative range sensor scanning schemes. For a known environment, a mobile robot scans the surroundings using a range sensor that can rotate 3600°. The environment is rebuilt using nodes of two adjacent walls. The robot configuration is then estimated and an obstacle is detected by comparing characteristic points of the sensor readings. In order to extract edges from noisy and inaccurate sensor readings, a filtering algorithm is developed. For multiple robot localization, a cooperative scanning method with sensor range limit is developed. Both are verified with simulation and experiments.

Nowadays, the road safety is an important research field. One of the principal research topics in this field is the vehicle localization in the road network. This article presents an approach of multi sensor fusion able to locate a vehicle with a decimeter precision. The different informations used in this method come from the following sensors: a low cost GPS, a numeric camera, an odometer and a steer angle sensor. Taking into account a complete model of errors on GPS data (bias on position and nonwhite errors) as well as the data provided by an original approach coupling a vision algorithm with a precise numerical map allow us to get this precision.

In this paper, to improve the efficiency of welding and user convenience in the shipbuilding industry, a PC-based off-line programming (OLP) technique and the development of a robot transfer unit are presented. The developed OLP system is capable of not only robot motion simulations but also automatic generations of a series of robot programs. The strength of the developed OLP system lies in its flexibility in handling the changes of the welding robot's target objects. Moreover, for a precise transfer of the robot to a desired location, an auxiliary mobile platform named a robot-origin-transfer-unit (ROTU) was developed. To enhance the cornering capability of the platform in a narrow area, the developed ROTU is equipped with 2 steering wheels and 1 driving wheel. Both the OLP and the ROTU were field­tested and their performances were proven successful.

In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the dynamic property of chaotic systems. The gradient descent method with the adaptive learning rates is applied to train the parameters of the SRWNN based predictor and controller. The adaptive learning rates are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the predictive controller. Finally, the chaotic systems are provided to demonstrate the effectiveness of the proposed control strategy.

In this paper, it is clearly shown that the two well-known necessary and sufficient conditions mp n as generic static output feedback pole-assignment and mp + d(m+p) n+d as generic minimum d-th order dynamic output feedback pole-assignment on complex field, unbelievably, do not match up each other in strictly proper linear systems. For the analysis, a diagram analysis is newly created (which is defined by the analysis of 'convoluted rectangular/dot diagrams' constructed via node-branch conversion of the signal flow graphs of output feedback gain loops). Under this diagram analysis, it is proved that the minimum d-th order dynamic output feedback compensator for pole-assignment in m-input, p-output, n-th order systems is quantitatively decomposed into static output feedback compensator and its associated d number of arbitrary 1st order dynamic elements in augmented (m+d)-input, (p+d)-output, (n+d)-th order systems. Total configuration of the mismatched data is presented in a Table.

This paper presents hybrid control of displacement and force in a Medical Tele-Analyzer by disturbance observer-based controller which is robust to internal and external disturbances; model uncertainty, load, and friction for instances. The developed Medical Tele-Analyzer consists of 2 subsystems; doctor-side subsystem and patient-side subsystem. In the doctor side subsystem, an array of displacement sensor is equipped to detect movement of doctor's hand and fingers. The detected information is transmitted to the patient side to be used in medical analysis. On the other hand, the patient-side subsystem consists of an array of displacement actuators, which is used to follow displacement of doctor's hand and fingers. An array of force sensors is used to detect forces between patient and the equipment. Since displacement control in patient side is coupled with force control in doctor side and vice-versa, design of the controller has to take into account this coupling. Not only using in medical tele-analysis, the proposed system can also be used in any tele-displacement-force controls of industrial processes.

In this paper, an estimator scheme for the rotor speed and flux of an induction motor is proposed on the basis of a fourth-order electrical model. It is assumed that only the stator currents and voltages are measurable, and that the stator currents are bounded. There are a number of common terms in the motor dynamics, and this is utilized to find a simple error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming that the rotor speed is constant. Some stability properties are given on the basis of Lyapunov analysis. In addition, the rotor resistance, which varies with the motor temperature, can also be estimated within the same framework. The effectiveness of the proposed scheme is demonstrated through computer simulations and experiments.

We present in this paper the stabilization (tracking) with motion planning of the six independent configurations of a mini unmanned areal vehicle equipped with four streamlined rotors. Naturally, the yaw-dynamic can be stabilized without difficulties and independently of other motions. The remaining dynamics are linearly approximated around a small roll and pitch angles. It will be shown that the system presents a flat output that is likely to be useful in the motion generation problem. The tracking feedback controller is based on receding horizon point to point steering. The resulting controller involves the lift (collective) time derivative for what flatness and feedback linearization are used. Simulation tests are performed to progress in a region with approximatively ten-meter-buildings.

This work presents a novel control index to regulate the pump speed of an axial flow blood pump for the left ventricular assist device (LVAD). The control index is based on the characterization of pump operating conditions such as normal or suction status. The pump operating characteristics reveal that a certain pulsatility relationship between the pump pressure difference and the pump flow is a unique index to identify the pump operating status under the diverse pump operating environments.

The design of reconfiguring a class of second-order dynamic systems via proportional plus derivative (P-D) feedback is considered. The aim is to resynthesize a P-D feedback controller such that the eigenvalues of the reconfigured closed-loop system can completely recover those of the original close-loop system, and make the corresponding eigenvectors of the former as close to those of the latter as possible. Based on a parametric result of P-D feedback eigenstructure assignment in second-order dynamic systems, parametric expressions for all the P-D feedback gains and all the closed-loop eigenvector matrices are established and a parametric algorithm for this reconfiguration design is proposed. The parametric algorithm offers all the degrees of design freedom, which can be further utilized to satisfy some additional performances in control system designs. This algorithm involves manipulations only on the original second-order system matrices, thus it is simple and convenient to use. An illustrative example and the simulation results show the simplicity and effect of the proposed parametric method.

This paper deals with the state estimation of linear time-invariant discrete systems with unknown inputs. The forward sequences of the output are treated as additional outputs. In this case, the rank condition for designing the unknown input estimator is relaxed. The gain for minimal estimation error variance is presented, and a numerical example is given to verify the proposed unknown input estimator.

We describe the MiniWeb[7] TCP/IP stack (mIP), which is an extremely small implementation of the TCP/IP protocol suite running 8 or 32-bit micro controllers intended for embedded control systems, and satisfying the subset of RFC1122 requirements needed for host­to-host interoperability over different platforms. Our TCP/IP implementation does sacrifice some of TCP's mechanisms such as fragmentation, urgent data, retransmission, or congestion control. Our implementation is applicable to web based controllers. The network protocols are tested in operational networks using CommView and Dummynet where the various operational parameters such as bandwidth, delay, and queue sizes can be set and controlled.

A new optical digitizing system for determining the position of a cursor in three dimensions(3D) and an experimental device for its measurement are presented. A semi-passive system using light intensity modulation, a technology that is well known in radar ranging, is employed in order to overcome precision limitations imposed by background light. This system consists of a charge-coupled device camera placed before a rotating mirror and a light-emitting diode whose intensity is modulated. Using a Fresnel pattern for light modulation, it is verified that a substantial improvement of the signal to noise ratio is realized for the background noise and that a resolution of less than a single pixel can be achieved. This opens the doorway to the realization of high precision 3D digitized measurement. We further propose that a 3D position measurement with a monocular optical system can be realized by a numerical experiment if a linear-period modulated waveform is adopted as the light-modulating one.

Biomedical signals such as ECG, EMG, and EEG are extremely important in the diagnosis of patients. It is difficult to filter noise from these signals, and errors resulting from filtering can distort a biomedical signal. Existing systems have shown poor performance when complicated noise appears. Adaptive filtering is selected to contend with these defects. Existing adaptive filters can adjust the filter coefficient with the given filter order, but they can produce an unsuitable order in different environments. In order to solve this problem, an optimal adaptive filter with a dynamic structure was designed. Positive experimental results were obtained.