• Journal of Power System Engineering
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• v.2 no.2
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1523-1535
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• 2018

High-performance Phase-Locked Loops (PLLs) are critical for grid synchronization in grid-tied power electronic applications. In this paper, a new single-phase All Digital Phase-Locked Loop (ADPLL) is proposed. It features fast transient response and good robustness under distorted grid conditions. It is designed for Field Programmable Gate Array (FPGA) implementation. As a result, a high sampling frequency of 1MHz can be obtained. In addition, a new OSG is adopted to track the power frequency, improve the harmonic rejection and remove the dc offset. Unlike previous methods, it avoids extra feedback loop, which results in an enlarged system bandwidth, enhanced stability and improved dynamic performance. In this case, a new parameter optimization method with consideration of loop delay is employed to achieve a fast dynamic response and guarantee accuracy. The Phase Detector (PD) and Voltage Controlled Oscillator (VCO) are realized by a Coordinate Rotation Digital Computer (CORDIC) algorithm and a Direct Digital Synthesis (DDS) block, respectively. The whole PLL system is finally produced on a FPGA. A theoretical analysis and experiments under various distorted grid conditions, including voltage sag, phase jump, frequency step, harmonics distortion, dc offset and combined disturbances, are also presented to verify the fast dynamic response and good robustness of the ADPLL.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.688-696
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• 2017

This paper presents an integrated roll-pitch-yaw autopilot using an equivalent based sliding mode control for skid-to-turn nonlinear time-varying missile system with lumped disturbances in its six-equations of motion. The considered missile model are developed to integrate the model uncertainties, external disturbances, and parameters perturbation as lumped disturbances. Moreover, it considers the coupling effect between channels, the variation of missile velocity and parameters, and the aerodynamics nonlinearity. The presented approach is employed to achieve a good tracking performance with robustness in all missile channels simultaneously during the entire flight envelope without demand of accurate modeling or output derivative to avoid the noise existence in the real missile system. The proposed autopilot consisting of a two-loop structure, controls pitch and yaw accelerations, and stabilizes the roll angle simultaneously. The Closed loop stability is studied. Numerical simulation is provided to evaluate performance of the suggested autopilot and to compare it with an existing autopilot in the literature concerning the robustness against the lumped disturbances, and the aforesaid considerations. Finally, the proposed autopilot is integrated in a six degree of freedom flight simulation model to evaluate it with several target scenarios, and the results are shown.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.56-64
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• 2000

The design of filters for pattern recognition that have optimal trade-off for the criteria of noise robustness, peak sharpness and Homer efficiency, when input scene noise is spatially disjoint (nonoverlapping) with the target, are presented Three different criteria, ie, signal-to-noise ratio, peak-to-output energy ratio and light efficiency are used to design the filter. Computer simulation is made for the various types of noise and parameters to illustrate filter performance for optical pattern recognition. When we compare the new trade-off filter with the original optimal trade-off filter, the performance of trade-off filter for nonoverlapping background is better than that of trade-off filter for overlapping background.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.34-43
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• 1990

An improved parameter adaptation and control law for robot manipulator are proposed based on a linearized parametric system equation and augmented error vectors. In view of the modeling error and parasitics with small time constants which inevitably introduced during modelling process, their effects on the robustness of the system performance are reviewed and as an conutermearsure, adaptation mechanism with low pass filter is proposed. Proposed parameter adaptation and control low assure the stability of the robot manipulator in the large without further assumption. Computer simulation shows its effectiveness of the proposed adaptation mechanism to improve the robustness of the system in presence of the parasitics in the system and superior performance for high speed operations make it an attractive option in application of the adaptive control field for robot manipulator.

• ETRI Journal
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• v.31 no.4
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• pp.399-407
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• 2009

In this paper, we present a robust $H_{\infty}$ distributed power control scheme for wireless CDMA communication systems. The proposed scheme is obtained by optimizing an objective function consisting of the user's performance degradation and the network interference, and it enables a user to address various user-centric and network-centric objectives by updating power in either a greedy or energy efficient manner. The control law is fully distributed in the sense that only its own channel variation needs to be estimated for each user. The proposed scheme is robust to channel fading due to the immediate decision of the power allocation of the next time step based on the estimations from the $H_{\infty}$ filter. Simulation results demonstrate the robustness of the scheme to the uncertainties of the channel and the excellent performance and versatility of the scheme with users adapting transmit power either in a user-centric or a network-centric efficient manner.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.315-322
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• 2006

Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.95-107
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• 2001

This paper is devoted to the parameter optimization of unmanned aerial vehicle's (UAV) flight control laws. Optimization procedure is based on the ideas of mixed $H_2/H_{\infty}$ control of multi-model plants. By using this approach, some partial $H_2$-terms defining the performance of nominal and parametrically perturbed Flight Control System (FCS) responses to deterministic command signals in stochastic atmosphere as well as $H_{\infty}$-terms defining robustness of the FCS can be incorporated in the composite cost function. Special penalty function imposed on the location of closed-loop system's poles keeps the speed of response and oscillatory properties for both nominal and perturbed FCS in reasonable limits. That is the reason why this procedure may provide reasonable trade-off between the performance and robustness of FCS that are very important especially for UAV. Its practical importance is illustrated by case studies of lateral and longitudinal control of small UAV.

• Smart Structures and Systems
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• v.5 no.3
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• pp.261-277
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• 2009

A fuzzy-sliding mode controller is presented to control the dynamics of semi-active suspension systems of vehicles using magneto-rheological (MR) fluid dampers. A full car model is used to design and evaluate the performance of the proposed semi-active controlled suspension system. Four mixed mode MR dampers are designed, manufactured, and integrated with four independent sliding mode controllers. The siding mode controller is designed to decrease the energy consumption and maintain robustness. In order to overcome the chattering of the sliding mode controllers, a fuzzy logic control strategy is merged into the sliding mode controller. The proposed fuzzy-sliding mode controller is designed and fabricated. The performance of the semi-active suspensions is evaluated in both the time and frequency domains. The obtained results demonstrate that the proposed fuzzy-sliding mode controller can effectively suppress the vibration of vehicles and improve their ride comfort and handling stability. Furthermore, it is shown that the "chattering" of the sliding mode controller is smoothed when it is integrated with a fuzzy logic control strategy. Although the cost function of the fuzzy-sliding mode control is a slightly higher than that of a classical LQR controller, the control effectiveness and robustness are enhanced considerably.