• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.351-354
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• 2006

In underwater environment, the control of AUV is difficult, because of the existence of parameter uncertainties and disturbances as well as highly nonlinear and coupled system dynamics. The requirement for the simple and robust controller which works satisfactorily in those dynamical uncertainties, call for a design using the PD or sliding mode controller. The PD controller is very popular controller in the industrial field and the sliding mode controller has been used successfully for the AUV controller design. In this paper, the two controllers arc designed for ISiMI(Integrated Submergible Intelligent Mission Implementation) AUV and the performances are compared by numerical simulation under the modeling uncertainty and disturbances. The design process of PD and sliding mode controller for ISiMI AUV and simulation results are included to compare the performances of the two controllers.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.264-269
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• 2002

In this paper, Η$_{\infty}$ depth and course controller of an AUV(Autonomous Underwater Vehicle) using Η$_{\infty}$ servo control is proposed. The Η$_{\infty}$ servo problem is formulated to design the controllers satisfying a robust tracking property with modeling errors and disturbances. The solution of the Η$_{\infty}$ servo problem is as fellows: first, this problem is modified as an Η$_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The Η$_{\infty}$ depth and course controller are designed to satisfy with the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under disturbances(wave force, wave moment, tide). The performances of the designed controllers are evaluated with computer simulations, and finally these simulation results show the usefulness and application of the proposed Η$_{\infty}$ depth and course control system.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.95-98
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• 2002

This paper presents a study on DSP(TMS320F240) controller design for multi-axes transportation system using BLDC servo motor. This BLDC servo motor controller was realized with DSP(Digital Signal Processor) and IPM (Intelligent Power Module). The multi-axes transportation system needs torque, speed, position control of servo motor for variable action. This paper implements those servo control with vector control and space vector modulation technique. As CPU of controller DSP(TMS320F240) is adopted because, it has PWM(Pulse Width Modulation) waveform generator, A/D(Analog to Digital) converter, SPI(Serial Peripheral Interface) port and input/output port etc. The controller of multi-axes transportation system consists of 3-level hierarchy structure that main host PC manages three sub DSP system which transfer downword command and are monitoring the states of end servo controllers. Each sub DSP system operates eight BLDC servo controllers which control BLDC servo motor using DSP and IPM Between host system and middle digital signal processor communicate with RS-422, between main processor and controller communicate with SPI port.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.4
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• pp.113-118
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• 2017

As the demand for industrial robots and Automated Guided Vehicles (AGVs) increases, higher performance is also required from them. Fuzzy controllers, as part of an intelligent control system, are a direct control method that leverages human knowledge and experience to easily control highly nonlinear, uncertain, and complex systems. This paper uses a $LabVIEW^{(R)}-based$ fuzzy controller with gain scheduling to demonstrate better performance than one could obtain with a fuzzy controller alone. First, the work area was set based on forward kinematics and inverse kinematics programs. Next, $LabVIEW^{(R)}$ was used to configure the fuzzy controller and perform the gain scheduling. Finally, the proposed fuzzy gain scheduling controller was compared with to controllers without gain scheduling.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.1
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• pp.23-31
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• 2011

In this paper, the intelligent smart monitor system is implemented for the next generation vehicle. to mitigate the numerous effects of distractions within the vehicle, it is vital to put critical information where the driver can use it without affection focus on the road ahead. Audible alarms are useful supplements when used in conjunction with visual displays. But driving is an overwhelmingly visual task. To optimize a vehicle's active safety systems, more than just audible alarms are necessary. The driver needs a visual interface that focuses his or her attention on the road ahead. The most commonly viewed information in a vehicle is from the instrument cluster, where speed, tachometer, fuel, engine temperature, fuel gauge, turn indicators and warning lights provide the driver with an array of fundamental information. TFT LCD, LCD Back light led, plane mirror, lens and controllers parts were designed to intelligent integrated smart monitor system. Finally, in this paper, we analyze intelligent integrated smart monitor system for driver safety vehicles.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.52-62
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• 2006

In a fuzzy control system to process fuzzy data in high-speed for intelligent systems, one of the important problems is the improvement of the execution speed in the fuzzy inference and defuzzification stages. Especially, it is more important to have high-speed operations in the consequent part and defuzzification stage. Therefore, in this paper, to improve the speedup of the fuzzy controllers for intelligent systems, we propose an integer line mapping algorithm using only integer addition to convert [0,1] real values in the fuzzy membership functions in the consequent part to integer grid pixels $(400{\times}30)$. This paper also shows a novel defuzzification algorithm without multiplications. Also we apply the proposed system to the truck backer-upper control system. As a result, this system shows a real-time very high speed fuzzy control as compared as the conventional methods. This system will be applied to the real-time high-speed intelligent systems such as robot arm control.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.593-597
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• 2004

This paper presents the new design method of fuzzy control system for nonlinear system. Many conventional design methods for fuzzy controller find the control gain for stabilizing fuzzy controller with some mathematical approaches. However, there exist some controllers which are hard to design with mathematical approach. In order to solve these problems, we propose the intelligent design method for fuzzy controller by using genetic algorithm with evolution strategy. The genetic algorithm with evolution strategy finds the control gain by changing the evolution region of chromosome. Finally, an application example of stabilizing a cart-pole typed inverted pendulum system will be given to show the stabilizability of the fuzzy controller.