• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.3
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• pp.211-216
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• 2009

Chattering phenomenon is still a large drawback of VSS. To overcome this problem, various approaches have been reported. A new notion of sliding sector has been proposed recently. In this paper, fuzzy control with time-varying boundary layer using the sliding sector theory with continued input function in the sector is proposed. This paper analyzes the stability, using Lyapunov function on the sliding sector. Computer simulation for inverted pendulum results in elimination of the chattering phenomenon.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.62-67
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• 1997

This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.3
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• pp.168-173
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• 2007

Chattering phenomenon is still a large drawback of VSS. To overcome this problem, various approaches have been reported. A new notion of sliding sector has been proposed recently. In this paper, new methods of the nonlinear system control using the sliding sector theory with continued input function in the sector is proposed. This paper analyzes the stability, using Lyapunov function on the sliding sector. computer simulation for inverted pendulum results in elimination of the chattering phenomenon.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.649-651
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• 2015

This paper describes a robust adaptive sliding mode control (RASMC) for torque ripple minimization of switched reluctance motor (SRM) using it in automotive application. The objective is to control effort smoothness while the system is under perturbations by unstructured uncertainties, unknown parameters and external disturbances. The control algorithm employs an adaptive approach to remove the need for prior knowledge within the bound of perturbations. This is suitable for tackling the chattering problem in the sliding motion of sliding mode control method. The algorithm then incorporates modifications in order to build a chattering-free modified robust adaptive sliding mode control using Lyapunov stability theory.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2283-2286
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• 2000

Sliding control is a powerful approach to controlling nonlinear and uncertain systems. Conventional sliding mode control suffer' from high control gain and chattering problem. also it needs mathematic! modeling equations for control systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. In this paper, without mathematical modeling equations, the plant parameters in sliding mode are estimated by the indirect adaptive fuzzy method. the proposed algorithm could analyze the system's stability and convergence behavior using Lyapunov theory. so sliding modes are reconstructed and decreased tracking error. moreover convergence time took a short. An example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

• Ocean Systems Engineering
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• v.12 no.2
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• pp.159-172
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• 2022

To ensure stable performance, adaptive regulators with new theories are designed for steel-covered offshore platforms to withstand anomalous wave loads. This model shows how to control the vibration of the ocean panel as a solution using new results from Lyapunov's stability criteria, an evolutionary bat algorithm that simplifies computational complexity and utilities. Used to reduce the storage space required for the method. The results show that the proposed operator can effectively compensate for random delays. The results show that the proposed controller can effectively compensate for delays and random anomalies. The improved prediction method means that the vibration of the offshore structure can be significantly reduced. While maintaining the required controllability within the ideal narrow range.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.51-57
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• 1999

In this paper, we deal with the problem of controlling an unknown nonlinear dynamical system, using wavelet network. Accurate control of the nonlinear systems depends critically on the accuracy and efficiency of the function approximator used to approximate the function. Thus, we use wavelet network which shows high capability of approximating the functions and includes the free-selection of basis functions for the control of the nonlinear system. We find the dilation and translation that are wavelet network parameters by analyzing the time-frequency characteristics of the controller's input to construct an initial adaptive wavelet network controller. Then, weights is adjusted by the adaptive law based on the Lyapunov stability theory. We apply this direct adaptive wavelet network controller to control the inverted pendulum system which is an nonlinear system.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.94-104
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.139-148
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• 2024

In this paper, we propose a two-degree-of-freedom snake robot head system and an I-PID (Intelligent Proportional-Integral-Derivative)-based controller utilizing RBF (Radial Basis Function) neural network and adaptive robust terms as a control strategy to reduce rotation occurring in the snake robot head. This study proposes a two-degree-of-freedom snake robot head system to avoid complex snake robot dynamics. This system has a control system independent of the snake robot. Subsequently, it utilizes an I-PID controller to implement a control system that can effectively manage rotation at the snake robot head, the robot's nonlinearity, and disturbances. To compensate for the time delay estimation errors occurring in the I-PID control system, an RBF neural network is integrated. Additionally, an adaptive robust term is designed and integrated into the control system to enhance robustness and generate control inputs responsive to signal changes. The proposed controller satisfies stability according to Lyapunov's theory. The proposed control strategy was tested using a 9-degreeof-freedom snake robot. It demonstrates the capability to reduce rotation in Lateral undulation, Rectilinear, and Sidewinding locomotion.