• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.402-408
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• 2017

This paper deals with a robust ${\mathfrak{H}}_{\infty}$ controller design problem for waypoints tracking of large displacement unmanned underwater vehicles (LDUUVs) in Takagi-Sugeno fuzzy form. The LDUUV model uses a rudder to control its horizontal motion. We determine the order of waypoints based on their priorities and consider only surge force. A fuzzy controller in state-feedback form is taken and its design condition of is represented in terms of linear matrix inequalities. A numerical simulation is included to show the effectiveness of the theoretical development.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.579-584
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• 2004

In this paper, we present the mechanical, electrical system design and system integration of controllers including sensory devices of the humanoid, KHR-2 (KAIST Humanoid Robot - 2). We have developed KHR-2 since 2003. Total number of DOF of KHR-2 is 41. Each arm including a hand has 11 DOF and each leg has 6 DOF. Head and trunk also has 6 DOF and 1 DOF respectively. In head, two CCD cameras are used for eye. To control all axes efficiently, distributed control architecture is used to reduce computation burden of main controller and to expand devices easily. So we developed the sub-controller as a servo motor controller and a sensor interfacing devices using microprocessor. The main controller attached its back communicates with sub-controllers in real-time by CAN (Controller Area Network) protocol. We used Windows XP as its OS (Operation System) for fast development of main control program and easy extension of peripheral devices. And RTX HAL extension commercial software is used to realize the real-time control in Windows XP environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.341-346
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• 2004

Nowadays, versatile robots are developed around the world. Novel algorithms are needed for controlling such robots. A 2-Layer fuzzy controller can deal with many inputs as well as many outputs, and its overall structure is much simpler than that of a general fuzzy controller. The main problem encountered in fuzzy control is the design of the fuzzy controller. In this paper, the fuzzy controller is designed by the schema co-evolutionary algorithm. This algorithm can quickly and easily find a global solution. Therefore, the schema co-evolutionary algorithm is used to design a 2-layer fuzzy controller in this study. We apply it to a mobile robot and verify the efficacy of the 2-layer fuzzy controller and the schema co-evolutionary algorithm through the experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1399-1408
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• 2013

This paper proposes a new $H_{\infty}$ T-S fuzzy controller with a novel integral control for induction motors which have nonlinear dynamics. The $H_{\infty}$ T-S fuzzy controller is used for the nonlinearity and robustness and weighted integral is used for tracking problem and control performance. A T-S Fuzzy controller is the fuzzy combination of local linear controllers considering the overall stability, and LMI(Linear Matrix Inequlity) is used for determining the gains of linear controllers. The tracking problem of an induction motor is changed into regulator problem by introducing the integral control technique with weighting factor, diminishing the conservatism of $H_{\infty}$ T-S fuzzy controller.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.1-11
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• 2017

With a given spring-mass-damper system, $H_{\infty}$ and ${\mu}$-synthesis control methods are used to build system controllers which minimize vibrations at two major natural frequencies in two cases; without uncertainty; with 20% uncertainty. In order to check the stability and performance of two controllers, those are examined using GM and PM values. The signal strength of output responses is compared using the concept of central numerical differentiation and then results are quantified using the RMS method. Lastly, 40 random samples of $H_{\infty}$ and ${\mu}$-synthesis controllers are obtained for three different $W_{per\;f1}$ weighting functions and drawn in the time domain in order to compare the stability. Overall, ${\mu}$-synthesis controller manages the vibrations much better than $H_{\infty}$ controller according to the robust stability and performance values obtained by simulating random samples of 40 plant models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.211-214
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\sub$x/, B$\sub$y/, B$\sub$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, learning itself, and the adequacy of the design controller. Also, the performance of the controller can be verified through simulation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.1
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• pp.44-54
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• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.874-882
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• 2011

The decoupling design for the one-degree-of-freedom controller system is treated within the $H_{\infty}$ framework. In the present study, we demonstrate that the $H_{\infty}$ performance problem in the decoupling design is reduced into interpolation problems on scalar functions. To guarantee the properness of decoupling controllers and the overall transfer matrix, the relative degree conditions on the interpolating scalar functions are derived. To find the interpolating functions with relative degree constraints, Nevanlinna-Pick algorithm with starting function constraint is utilized in the present study. An illustrative example is given to provide details regarding the solution.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.226-232
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• 2011

The $H_{\infty}$ approach, adopted in this paper, is based on loop shaping using a normalized coprime factor combined with a field-oriented control to control induction motor. We develop two loops. The first one, the inner loop, controls the stator current by $H{\infty}$ controller in order to obtain good performance. The second loop, the outer one, guarantees stability and tracking performance of speed and rotor flux using a proportional integral controller. When the rotor flux cannot be measured, we introduce a flux observer to estimate the rotor flux. Simulation and experimental results are presented to validate the effectiveness and the good performance of this control technique.