• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.7
• /
• pp.1010-1024
• /
• 1995

An intelligent trajectory control method that controls a direction and a average velocity for a prosthetic arm by force and direction estimations using EMG signals is proposed. 3 stage linear filters are used as a real time joint trajectory planner to minimize the impact to human body induced by arm motions and to reduce muscle fatigues. We use combination of MLP and fuzzy filter for a limb direction estimation and a time model of force for determining a cartesian trajectory control parameter. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. Simulation results of the proposed method show that the arm is effectively followed the desired trajectory by estimated foreces and directions. This method reduces the number of electrodes and attatched sites compared with the method using Hogan's impedance control.

• Asian-Australasian Journal of Animal Sciences
• /
• v.17 no.8
• /
• pp.1047-1052
• /
• 2004

The genomes of Chinese native chicken populations were screened using microsatellites as molecular markers. A total of, 528 individuals comprisede12 Chinese native chicken populations were typed for 7 microsatellite markers covering 5 linkage groups and genetic variations and genetic distances were also determined. In the 7 microsatellite loci, the number of alleles ranged from 2 to 7 per locus and the mean number of alleles was 4.6 per locus. By using fuzzy cluster, 12 Chinese native chicken populations were divided into three clusters. The first cluster comprised Taihe Silkies, Henan Game Chicken, Langshan Chicken, Dagu Chicken, Xiaoshan Chicken, Beijing Fatty Chicken and Luyuan Chicken. The second cluster included Chahua Chicken, Tibetan Chicken, Xianju Chicken and Baier Chicken. Gushi Chicken formed a separate cluster and demonstrated a long distance when comparing with other chicken populations.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.1
• /
• pp.10-15
• /
• 2009

With the development of techniques, robots are getting smaller, and the number of robots needed for application is greater and greater. How to coordinate large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot Systems (SRS) is a system that independent autonomous robots in the restricted environments infer their status from pre-assigned conditions and operate their jobs through the cooperation with each other. In the SRS, a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Especially, in order to cooperate with other robots, communicating with other robots is one of the essential elements. Because Bluetooth has many advantages such as low power consumption, small size module package, and various standard protocols, it is rated as one of the efficient communicating technologies which can apply to small-sized robot system. In this paper, we will develop Bluetooth communicating system for autonomous robots. And we will discuss how to construct and what kind of procedure to develop the communicating system for group behavior of the SRS under intelligent space.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.3
• /
• pp.250-255
• /
• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

• Proceedings of the IEEK Conference
• /
• 2002.06e
• /
• pp.261-264
• /
• 2002

In this study, we used a 16-bit microprocessor, 80C196KC for a control part in order to develop a multi-functional wheel-chair system, and implemented a joy-stick to control this system. For the complete system, we used a commercial electromotive wheelchair as a basic plant, and applied an encoder to get the rotating number of the motor to transfer data to the MCU to control the motor. We used PWM (Pulse Width Modulation) method to control the wheel-chair motor where a H-bridge circuit was configured. We used the fuzzy control algorithm for the operation of DC motor, which was attached to the electromotive wheelchair and manipulated following the change of the joystick position while a user was controlling the joystick. He also could control the speed and direction of DC motor as well as control position information.

• Journal of Navigation and Port Research
• /
• v.47 no.2
• /
• pp.75-84
• /
• 2023

Ships need to ensure safety during their navigation, which makes route determination highly important. It must be accompanied by a route following controller that can accurately follow the route. This study proposes a method for automatically generating the ship route based on deep reinforcement learning algorithm and following it using a route following controller. To generate a ship route, under keel clearance was applied to secure the ship's safety and navigation chart information was used to apply ship navigation related regulations. For the experiment, a target ship with a draft of 8.23 m was designated. The target route in this study was to depart from Busan port and arrive at the pilot boarding place of the Ulsan port. As a route following controller, a velocity type fuzzy P ID controller that could compensate for the limitation of a linear controller was applied. As a result of using the deep Q network, a route with a total distance of 62.22 km and 81 waypoints was generated. To simplify the route, the Douglas-Peucker algorithm was introduced to reduce the total distance to 55.67 m and the number of way points to 3. After that, an experiment was conducted to follow the path generated by the target ship. Experiment results revealed that the velocity type fuzzy P ID controller had less overshoot and fast settling time. In addition, it had the advantage of reducing the energy loss of the ship because the change in rudder angle was smooth. This study can be used as a basic study of route automatic generation. It suggests a method of combining ship route generation with the route following control.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.4
• /
• pp.281-286
• /
• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.3
• /
• pp.246-254
• /
• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.35-43
• /
• 2001

In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.2
• /
• pp.95-100
• /
• 2010

This paper proposes a new spatial regularization of Fisher linear discriminant analysis (LDA) to reduce the overfitting due to small size sample (SSS) problem in face recognition. Many regularized LDAs have been proposed to alleviate the overfitting by regularizing an estimate of the within-class scatter matrix. Spatial regularization methods have been suggested that make the discriminant vectors spatially smooth, leading to mitigation of the overfitting. As a generalized version of the spatially regularized LDA, the proposed regularized LDA utilizes the non-uniformity of spatial correlation structures in face images in adding a spatial smoothness constraint into an LDA framework. The region-dependent spatial regularization is advantageous for capturing the non-flat spatial correlation structure within face image as well as obtaining a spatially smooth projection of LDA. Experimental results on public face databases such as ORL and CMU PIE show that the proposed regularized LDA performs well especially when the number of training images per individual is quite small, compared with other regularized LDAs.