• Journal of Power Electronics
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• v.16 no.5
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• pp.1781-1790
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• 2016

This study focuses on the coordination control problem of multiple electrical excited synchronous motor systems. A robust coordination controller is designed on the basis of cross coupling and an interval matrix. The proposed control strategy can deal with load uncertainty. In addition, the proposed control strategy is applied to a high-power metal-rolling system. Simulation and experiment results demonstrate that the proposed control strategy achieves good dynamic and static performance. It also shows better coordination performance than traditional proportional-integral controllers.

• Journal of Power Electronics
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• v.8 no.4
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• pp.317-324
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• 2008

This paper proposes a Multiband Shunt Hybrid Active Filter (SHAF) with sensorless control. A plant is modeled in the discrete- time domain and a controller is designed using the Pole shifting law in the polynomial domain. This control approach is very useful for filtering the load harmonics with reduced sensor counts where a low cost solution like SHAF is required. Multiple Synchronous Reference Frames (MSRF) and low pass filters are used to measure the $5^{th}$ and $7^{th}$ harmonic components separately from the load and filter currents. Individual current controllers are designed for the $5^{th}$ and $7^{th}$ harmonic currents. Control is realized in the stationary, three-phase (abc) reference frame. Performance of the controller is validated through simulation, using realistic plant and controller models, as well as experimentally on a full-scale distribution system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.803-812
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• 2000

In this paper we introduce a model based centralized hierarchical controller for cooperative team of soccerplaying multiple mobile robots. The hierarchical controller is composed of high-level and low-level controllers. Using the coordinates information of objects from the vision are simple models of multiple mobile tobots on the playground. Subsequently, the high level controller selects and action model corresponding to the perceived state transition model and generates subgoal and goal-velocity, from which the low level controller generates trajectory of each wheel velocity of the robot. This two layered simplicity. The feasubility of the control strategy has been demonstrated in an implementation for real soccer games at a MiroSot league.

• Journal of KSNVE
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• v.11 no.1
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.262-271
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• 2009

The purpose of this study was to propose the method to recognize gestures based on inertia sensor which recognizes the movements of the user using inertia sensor and lets the user enjoy the game by comparing the recognized movements with the pre-defined movements for the game contents production. Additionally, it was tried to provide users with various data entry methods by letting them wear small controllers using three-axis accelerator sensor. Users can proceed the game by moving according to the action list printed on the screen. They can proceed the experiential games according to the accuracy and timing of their movements. If they use multiple small wireless controllers together wearing them on the major parts of hands and feet and utilize the proposed methods, they will be more interested in the game and be absorbed in it.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.3
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• pp.13-18
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• 2005

This paper presents a design of a multi-objective $H_2/H_{\infty}$ controller of an inverted pendulum with polytopic model by the stabilizing regulator and tracking performances. Multi-objective controllers are designed for polytopic models by the LMI design technique with convex algorithms. It is observed that the inverted pendulum controlled by any controller designed for each polytopic model is stably restored to the vertical angle position for initial values of larger tilt angles.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.192-199
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• 2022

In DC distribution systems, a TAB converter employing multiple transformers is one of the most widely used topologies due to its high power density, modularizability, and cost-effectiveness. However, the conventional control technique for a grid-connected mode in the TAB converter cannot maintain its reliability for an islanding mode under a blackout situation. In this paper, the islanding mode control technique is proposed to solve this issue. To verify the relative stability and dynamic characteristics of the control technique, small-signal models of both the grid connected and the islanding mode are derived. Based on the small-signal models, PI controllers are designed to provide suitable power control. The proposed control technique, the accuracy of small-signal models, and the performance of the controllers are verified by simulations and experiments with a 1-kW prototype TAB converter.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.99-105
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• 2011

This paper presents a method to design a centralized repetitive controller that is robust to variations in the multiple system parameters. The uncertain parameters are specified probabilistically by their probability distribution functions. Instead of working with the distribution functions directly, the centralized repetitive controller is designed from a set of models that are generated from the specified probability functions. With this multiple-model design approach, any number of uncertain parameters that follow any type of distribution functions can be treated. Furthermore, the controller is derived by minimizing a frequency-domain based cost function that produces monotonic convergence of the tracking error as a function of repetition number. Numerical illustrations show how the proposed multiple-model design method produces a repetitive controller that is significantly more robust than an optimal repetitive controller designed from a single nominal model of the multiple system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1470-1473
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• 2003

In this paper the networked control systems (NCS) problem is discussed where plants and controllers are distributed and interconnected by a common network. NCS is designed with LQ regulator and applied to an inverted pendulum accounting for the multiple time delays. We are to deals with a networked control system with a single controller, multiple sensors and multiple actuators. Since these parts are distributed, they are interconnected by communication networks. An NCS with LQ regulator is designed and applied to an inverted pendulum as a benchmark plant to check its performance under time delays induced by the network. Network induced delays are composed of two parts. One is the delay from controller to plant, and another is from plant to controller. They are assumed to be constant in this paper, and the plant and controller are discretized. To apply the LQ regulator the NCS model is transformed to a standard model with delayed states as state variable. And real network induced delay is measuring in TCP/IP network assuming that two delays are constant.