• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.915-921
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• 2004

In this paper, a variable structure controller(VSC) is used to control the position of the hydraulic servo system subjected to unknown disturbances. The system consists of two cylinders, which connected in series. One cylinder executes position control, the other executes force control to generate disturbances. In order to control each cylinder, interaction must be considered between two cylinders because two cylinders are connected in series. Therefore, the controller is designed regarding interaction between two cylinders as disturbances. Performance of the proposed controller was verified through experiments and compared to PID controller. The experiments showed that the proposed controller had a good performance and robustness.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.650-658
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• 2012

This paper proposes a high performance position controller for a driving system using a time optimal controller which has been widely used to control driving systems to achieve desired reference position or velocity in a minimum response time. The main purpose of this research lies in an improvement of transient response performance rather than that of steady-state response in comparison with other control strategies. In order to refine the scheme of time optimal control, Lyapunov stability proofs are incorporated in a controller of standard second order system model. This scheme is applied to the control of a driving system. In view of the simulation and experiment results, the standard second order system model exhibits better minimum-time control performance and robustness than double integral system model does.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.729-737
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• 1998

In this paper, using $\mu$ synthesis algorithm with structured uncertainty, we design controller and apply it for the Two-Inertia resonance(TMS: Two Mass Spring) system. The TMS system is one of the simplest models which generate a torsional vibration. In this system, it is required to design a controller achieving the control performance while suppressing the torsional vibration. Furthermore, when vibration frequency for the system is varying by reason of parameter variations, we should consider parameter variations in controller design. Then, we design two other controller schemes of the PI controller and the standard $H_{\infty}$ controller and compare these controllers with the controller designed by the $\mu$ synthesis robust control method by using simulations and experiments.

• Journal of Power System Engineering
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• v.14 no.1
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• pp.65-70
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• 2010

Magnetic levitation system is nonlinear and inherently unstable, so it is difficult to control. Analog control circuit was widly used as the controller of magnetic levitation system, but digital controller is now substituted for analog controller according to development of digital electronics. In this study, Atmel AVR series, ATmega 128 which is a kind of $\mu$-processor for digital controller is used because the chip is cheap and popular. We designed and made ATmega 128 one-board controller and aimed to verify validity through the experiance of levitation response.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.25-30
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• 2017

Arago's disk system consists of a speed controller of the DC motor (inner loop controller) and a position controller of the magnetic bar angle (main controller), which are implemented by the design of the PI and PID controller, respectively. First, we analyzed the nonlinear characteristics of the Arago disk system and found the operating point range of three locations as a result. In this paper, a gain scheduler method was applied to guarantee a constant control performance in the range of $0{\sim}130^{\circ}C$, and a structure to change the controller according to the control reference value based on the previously obtained operating points was experimentally implemented. The Distributed Control Systems (DCS) configuration using the Controller Area Network (CAN) was used to verify the proposed method by improving the operational efficiency of the entire experimental system. So, simplicity of the circuit and easy diagnosis were achieved through a single CAN bus communication.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.21-27
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• 2018

This paper proposed the real-time monitoring methodology of a traffic signal controller. The proposed methodology is based on the simulation technology, and it is necessary to construct a simulation model imitating the behavior of a traffic signal controller. By executing the simulation model, we can obtain the 'nominal system trajectory' of the traffic signal controller. On the other hand, an IoT(Internet of Things)-based monitoring device is implemented in a traffic signal controller. Through the monitoring device, it is possible to obtain the 'actual system trajectory'. By comparing the nominal system trajectory and the actual system trajectory, we can estimate the degree of deterioration of a traffic signal controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.83-89
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• 2000

This paper presents a dynamic modeling and a sliding mode controller for the high-speed / high-accuracy position control system. Selected target system is the wire bonder head assembly which is used in semiconductor assembly process. This system is a reciprocating one around the pivot point that consists of VCM(voice coil motor) as a actuator and transducer horn as a bonding tool. For the modeling elements, the system is divided into electrical circuit, magnetic circuit and mechanical system. Each system is modeled by using the bond graph method and united into the full system. Two major aims are considered in the design of the controller. The first one is that the horn must track the given reference trajectory. The second one is that the controller must be realizable by using the DSP board. Computer simulation and experimental results show that the designed sliding mode controller provides better performance than the PID controller.

• Journal of the Korean Institute of Navigation
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• v.23 no.3
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.169-177
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• 2024

Interacting Spherical tank has maximum storage capacity is broadly utilized in industries because of its high storage capacity. This two tank level system has the nonlinear characteristics due to its varying surface area of cross section of tank. The challenging tasks in industries is to manage the flow rate of liquid. This proposed work plays a major role in controlling the liquid level in avoidance of time delay and error. Several researchers studied and investigated about reducing the nonlinearity problem and their approaches do not provide better result. Different types of controllers with various techniques are implemented by the proposed system. Intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) based Sliding Mode Controller (SMC) with Fractional order PID controller is a novel technique which is developed for a liquid level control in a interacting spherical tank system to avoid the external disturbances perform better result in terms of rise time, settling time and overshoot reduction. The performance of the proposed system is obtained by analyzing the simulation result obtained from the controller. The simulation results are obtained with the help of FOMCON toolbox with MATLAB 2018. Finally, the performance of the conventional controller (FOPID, PID-SMC) and proposed ANFIS based SMC-FOPID controllers are compared and analyzed the performance indices.