• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1119-1128
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• 2013

In this paper, we propose an algorithm to detect and track the human face with a GPU-based high speed. Basically the detection algorithm uses the existing Adaboost algorithm but the search area is dramatically reduced by detecting movement and skin color region. Differently from detection process, tracking algorithm uses only depth information. Basically it uses a template matching method such that it searches a matched block to the template. Also, In order to fast track the face, it was computed in parallel using GPU about the template matching. Experimental results show that the GPU speed when compared with the CPU has been increased to up to 49 times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2846-2866
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• 2022

Caenorhabditis elegans exhibits sophisticated chemotaxis behavior through two parallel strategies, klinokinesis and klinotaxis, executed entirely by a small nervous circuit. It is therefore suitable for inspiring fast and energy-efficient solutions for autonomous navigation. As a random search strategy, the Lévy walk is optimal for diverse animals when foraging without external chemical cues. In this study, by combining these biological strategies for the first time, we propose a spiking neural network model for search and contour tracking of specific concentrations of environmental variables. Specifically, we first design a klinotaxis module using spiking neurons. This module works in conjunction with a klinokinesis module, allowing rapid searches for the concentration setpoint and subsequent contour tracking with small deviations. Second, we build a random exploration module. It generates a Lévy walk in the absence of concentration gradients, increasing the chance of encountering gradients. Third, considering local extrema traps, we develop a termination module combined with an escape module to initiate or terminate the escape in a timely manner. Experimental results demonstrate that the proposed model integrating these modules can switch strategies autonomously according to the information from a single sensor and control steering through output spikes, enabling the model worm to efficiently navigate across various scenarios.

• Smart Structures and Systems
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• v.31 no.5
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• pp.437-454
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• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1249-1255
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• 2004

A new parameter adaptation scheme for RBF Neural Network (NN) has been developed in this paper. Even though the RBF Neural Network (NN) based controllers are robust against both un-modeled dynamics and external disturbances, the performance is not satisfactory for a fast and precise mobile robot. To improve the tracking performance as well as robustness, all the parameters of RBF NN are updated in real time. The stability of this control law is rigorously proved by following the Lyapunov stability theory and shown by the experimental simulations. The fact that all of the weighting factors, width and center of RBF NN have been updated implies that this scheme utilizes all the possibilities in RBF NN to make the controller robust and precise while the mobile robot is following un-known trajectories. The performance of this new algorithm has been compared to the conventional RBF NN controller where some of the parameters are adjusted for robustness.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.702-712
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• 2008

This paper presents a novel approach for controlling electrically driven robot manipulators based on voltage control. The voltage-based control is preferred comparing to torque-based control. This approach is robust in the presence of manipulator uncertainties since it is free of the manipulator model. The control law is very simple, fast response, efficient, robust, and can be used for high-speed tracking purposes. The feedback linearization is applied on the electrical equations of the dc motors to cancel the current terms which transfer all manipulator dynamics to the electrical circuit of motor. The control system is simulated for position control of the PUMA 560 robot driven by permanent magnet dc motors.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.201-208
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• 2002

In this paper, the control strategy of ratio changing system for a metal belt CVT adopting primary pressure regulation is developed, and the shirting performance of pressure regulating type CVT with the suggested control strategy is investigated. The control strategy suggested in this study is composed of 2 feedback loop, one is speed ratio feedback and the other is primary pressure feedback. The pressure feedback is adopted to ensure prohibiting a belt slip during transient period in a fast downshift mode. Simulation results show that the system with suggested control strategy gives appropriate response time and tracking Performance for upshift and also gives a proper primary pressure which can prohibit the belt slip. In addition, it is fecund that the given system has an acceptable servo property in tracking the target speed ratio and robustness for the disturbance of line pressure.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.121-128
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• 2006

This paper deals with the application of enhanced perturbation estimation (SMCEPE) to sliding mode control of a dynamic system in the presence of perturbations including external disturbances, unpredictable parameter variations, and unstructured dynamics. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE), the proposed one can offer robust control performances under serious control conditions, such as fast dynamic perturbations and slow loop-closure speeds, without a priori knowledge on upper bounds of perturbations. The perturbation estimator in SHCEPE also has more adaptability owing to the fractional-order hold technique. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a two-link robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.351-361
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• 1996

A variable structure controller is developed for an AC servo motor used in CNC milling machines. The designed controller is implemented as an outer loop controller to a factory designed motor-servopack system. The robustness parameter is tuned for a fast response when the speed tracking error is large, while it is tuned for small oscillations when the speed tracking error is small. The designed controller is installed on a CNC machine using a PC. Cutting experiments show improved performance over the factory-designed controller.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.135-138
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• 2009

In this paper, a novel maximum power point tracking (MPPT) for a PMSG-based variable speed wind power system is proposed using the fuzzy logic algorithm. The control algorithm is developed based on the normal hill climb searching (HCS) method, commonly used in wind energy conversion systems (WECS). The inputs of fuzzy-based controller are the derivations of DC output power and the step size of DC/DC converter duty cycles. The main advantages of the proposed MPPT method are no need to measure the wind velocity and the generator rotational speed. As such, the control algorithm is independent of turbine characteristics, achieving the fast dynamic responses with non-linear fuzzy systems. The effectiveness of the proposed MPPT strategy has been verified through the simulated results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.346-349
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• 1995

In this paperwe develop a real-time simulator for direct drive cooperative robot by using OpenGL in a Windows NT based system. This simulator is composed of 2 parts, a display part and an interface part. In the display part the robot is modelled and rendered in 3D space. To do this OpenGL, a kind of graphic library, is used for rendering and animating robots and kinematics gives the information of the current robot configuration. The control and the feedback data are sent and received via the interface part. In real time simulation interfacing part needs fast data transfer rate and good nosic immunity. In experiment we have simulated 2-link direct drive cooperative robots using the trajectory tracking algorithm proposed in reference.