• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.2
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• pp.107-114
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• 2014

This paper proposes a common rail pressure control algorithm for passenger car diesel engines. For handling the parameter-varying characteristics of common rail systems, the quantitative feedback theory (QFT) is applied to the design of a robust rail pressure control algorithm. The driving current of the pressure control valve and the common rail pressure are used as the input/output variables for the common rail system model. The model parameter uncertainty ranges are identified through experiments. Rail pressure controller requirements in terms of tracking performance, robust stability, and disturbance rejection are defined on a Nichols chart, and these requirements are fulfilled by designing a compensator and a prefilter in the QFT framework. The proposed common rail pressure control algorithm is validated through engine experiments. The experimental results show that the proposed rail pressure controller has a good degree of consistency under various operating conditions, and it successfully satisfies the requirements for reference tracking and disturbance rejection.

• Journal of Power Electronics
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• v.7 no.3
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• pp.213-221
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• 2007

A digital state feedback control method for the current mode control of DC-DC converters is proposed in this paper. This approach can precisely achieve interleaved current sharing among the converter modules. As the controller design and system analysis are performed in the time domain, the proposed method can easily satisfy the required converter specification by using the pole placement technique. The digital state feedback controller in the continuous and discrete time domain is derived for the robust tracking control. For the verification of the proposed control scheme, a parallel module bi-directional converter in a prototype 42V/14V hybrid automotive power system, which is a design example in the continuous time domain, and a parallel module buck converter, which is a design example in the discrete time domain, are implemented using a TMS320F2812 digital signal processor (DSP).

• Proceedings of the KIPE Conference
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• 2007.11a
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• pp.31-33
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• 2007

In this paper, a simple digital control scheme for the single/parallel module buck converters is proposed using a digital state feedback control method. The discrete state feedback controller structure for the robust tracking control is derived by using the error state. The proposed control system can precisely achieve the interleaved current sharing and the output regulation, and can achieve the systematical controller design for a given converter specification using the pole placement technique. For a design example, the single module buck converter is simulated using the MATLAB Simulink software and two 100W parallel module buck converters with a TMS320F2812 DSP is implemented.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.670-673
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• 1999

In this paper, we present a robust motion controller based on Adaptive-Fuzzy technique is proposed that multifunctional vehicle(MVR) for two DOF mobile robot can perform detailed inspection of physical conditions of sewage pipes as well as can effectively repair the damaged portions of the inner walls. The main difficulties in controlling this multifunctional robot vehicles lie in the fact that vehicles usually have three degrees of freedom in position and orientation in spite of having only two degrees of freedom for motion control in tracking mode. Decomposition of error between the reference posture and the current posture makes control of speed and steering possible. The Gyro compass part and Inclonometer of the robot is configured in order to realize position of robot. The proposed Adaptive-Fuzzy motion controller has two main characteristics: The one guarantees that the MVR follows the reference trajectory; the other one compensates the dynamics of the MVR. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

• Journal of Power Electronics
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• v.19 no.4
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• pp.881-893
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• 2019

This paper proposes a practical sliding-mode controller design for shaping the impedances of cascaded boost-converter power decoupling circuits for reducing the second order harmonic ripple in photovoltaic (PV) current. The cascaded double-boost converter, when used as power decoupling circuit, has some advantages in terms of a high step-up voltage-ratio, a small number of switches and a better efficiency when compared to conventional topologies. From these features, it can be seen that this topology is suitable for residential (PV) rooftop systems. However, a robust controller design capable of rejecting double frequency inverter ripple from passing to the (PV) source is a challenge. The design constraints are related to the principle of the impedance-shaping technique to maximize the output impedance of the input-side boost converter, to block the double frequency PV current ripple component, and to prevent it from passing to the source without degrading the system dynamic responses. The design has a small recovery time in the presence of transients with a low overshoot or undershoot. Moreover, the proposed controller ensures that the ripple component swings freely within a voltage-gap between the (PV) and the DC-link voltages by the small capacitance of the auxiliary DC-link for electrolytic-capacitor elimination. The second boost controls the main DC-link voltage tightly within a satisfactory ripple range. The inverter controller performs maximum power point tracking (MPPT) for the input voltage source using ripple correlation control (RCC). The robustness of the proposed control was verified by varying system parameters under different load conditions. Finally, the proposed controller was verified by simulation and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.89-92
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• 2005

Using natural speech commands for controlling a human-robot is an interesting topic in the field of robotics. In this paper, our main focus is on the verification of a speaker who gives a command to decide whether he/she is an authorized person for commanding. Among possible dynamic features of natural speech, pitch period is one of the most important ones for characterizing speech signals and it differs usually from person to person. However, current techniques of pitch detection are still not to a desired level of accuracy and robustness. When the signal is noisy or there are multiple pitch streams, the performance of most techniques degrades. In this paper, we propose a two-level approach for pitch detection which in compare with standard pitch detection algorithms, not only increases accuracy, but also makes the performance more robust to noise. In the first level of the proposed approach we discriminate voiced from unvoiced signals based on a neural classifier that utilizes cepstrum sequences of speech as an input feature set. Voiced signals are then further processed in the second level using a modified standard AMDF-based pitch detection algorithm to determine their pitch periods precisely. The experimental results show that the accuracy of the proposed system is better than those of conventional pitch detection algorithms for speech signals in clean and noisy environments.