In this paper, we present an image deconvolution algorithm for shift variant blur caused by a relative circular motion between the imaging equipment and the object during the exposure time. The two-dimensional shift variant blurred image caused by the accelerated circular motion is modeled as an output of a series of one-dimensional linear convolutions that expresses the degradation process. To simulate the accelerated circular motion blurred image, the midpoint circle algorithm is employed. In the image decovolution process, for the given center of the circular motion, the algorithm is used to obtain circular paths at which the degradation process happens. The shift invariant deconvolution method is applied to each circular path. After the estimated image is obtained, median filtering is applied to solve the some empty pixels. Simulation experiments confirm the capability of the proposed method.
We develop an automated cell-cutting technique for cell cloning. Animal cells softened by the cytochalasin treatment are injected into a microfluidic chip. The microfluidic chip contains two orthogonal channels: one microchannel is wide, used to transport cells, and generates the cutting flow; the other is thin and used for aspiration, fixing, and stretching of the cell. The injected cell is aspirated and stretched in the thin microchannel. Simultaneously, the volumes of the cell before and after aspiration are calculated; the volumes are used to calculate the fluid flow required to aspirate half the volume of the cell into the thin microchannel. Finally, we apply a high-speed flow in the orthogonal microchannel to bisect the cell. This paper reports the cutting process, the cutting system, and the results of the experiment.
The melting points of Cr3C2-C peritectic (1826°C) and Cr7C3-Cr3C2 eutectic (1742°C) alloys as materials for high-temperature fixed point cells are investigated for the use of thermocouple calibration. Pretests are performed to establish a suitable procedure for constructing contact thermometry cells based on such chromium-carbon mixtures. Two cells are constructed following two different possible procedures. The above two melting points are successfully observed for one of these cells using tungsten-rhenium alloy thermocouples.
This paper presents a current sensor-based home appliance and its state recognition method for intelligent outlets. Our system has three main functions: remote control, monitoring, and power supply schedule management. This research focuses particular on the monitoring function. To recognize the appliance and the state of the appliance, we extract ten features based on a measured current signal. In the experiment, we gather a number of signals with various appliances, and find that three features Irms, Iavg, and Ipeak yield valid recognition results of 84.3%, 86.4%, and 90.3% for classifying the state of the appliance into three categories. Moreover, sufficient recognition rates of 97.4%, 97.7%, and 99.0% are obtained by consideration of three candidates.
This paper presents a free space optics system installed between two single-mode optical fibers (SMFs). The result looks as if the two SMFs were seamlessly connected without the need for any photoelectric devices. Misalignments between the two SMFs caused by disturbances are actively compensated for by introducing a laser beam controller that incorporates an opto-mechatronic mechanism with four degrees of freedom. Experiments using a prototype are conducted to verify the effectiveness of the proposed FSO system for initial beam acquisition and beam tracking when there is a vibration disturbance.
This paper is concerned with robust stabilization of an uncertain system over a rate-limited digital channel from the viewpoint of input-output stability. Because of the quantization in the communication channel, it is impossible to apply the traditional small gain theorem to establish robust stability of the feedback system. To overcome this difficulty, we introduce a new notion of small lp signal lp stability, and derive a sufficient robust stability condition against lp gain-bounded uncertainty based on this notion. Furthermore, for the case of p = ∞, a sufficient data rate for the existence of a robustly stabilizing encoder-controller pair is explicitly given.
The objective of this paper is to show a general framework for online adjustment methods of the state feedback gains for multi-input multi-output optimal regulators via the quadratic stability arguments. We first give a region of state feedback gains containing the nominal optimal gain such that quadratic stability is ensured for all time-invariant state feedback gains in the region. We then show that under some mild conditions, quadratic stability is retained for arbitrary time-varying adjustment of the state feedback gain within this region via the concept of strong uniform complete observability. It is then illustrated how the result can be utilized as a general framework for constructing heuristic online gain adjustment laws, and the usefulness of the result is confirmed with a numerical example.
A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.
We propose a new weight compensation mechanism with a non-circular pulley and a spring. We show the basic principle and a numerical design method to derive the shape of the non-circular pulley. After demonstration of the weight compensation for an inverted pendulum system, we extend the same mechanism to a 2 degrees of freedom (DOF) parallel four-bar linkage system, analyzing the required torques with transposed Jacobian matrices. Finally, we develop a 3-DOF manipulator with relatively small output actuator and verifies that the weight compensation mechanism significantly contributes to decrease static torques to keep the same posture within manipulator's work space, which is also effective in a dynamic movement.
The partial feedback linearization is capable of expressing a complicated nonlinear system as a simple form for control. To get a proper linearized subsystem, it is most important to select a proper coordinate transformation. This paper plays a fundamental role in selecting the proper coordinate by revealing the system structure with respect to a relative degree. The relative degree is a key concept to treat the partial feedback linearization, especially, the input-output linearization of an input affine system. Using special functions of the state characterized in the relative degree, all functions are parameterized and classified according to their relative degrees. Applying the proposed parameterization to a coordinate transformation, the system structure with respect to relative degrees is revealed. Moreover using the input-output linearization with parameterized outputs, it is also shown that the internal dynamics of the partially linearized system is parameterized.