• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.130-135
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• 2007

This paper deals with a controller design for a 2 dimensional aeroelatic model which has unknown parameters including polynomial type nonlinearity. Actually in case of state and acuator signal having magnitude, rate and bandwidth limitations, the controller can't be implemented and so in each case, a filter is used for implementation. First, error signals are defined upon the backstepping theory, and tracking error signals are also defined due to command signal and filter signals and then compensated tracking error signals are defined. Lastly, a Lyapunov function is defined for the stabilization and from this method, an adaptive law is derived. Simulations are done for the demonstrtion of the effectiveness of the algorithms.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1646_1647
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• 2009

In this paper, Takagi-Sugeno(T-S) fuzzy controller and search method are developed for efficiency optimization of induction motors(IMs). The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of T-S fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is used to control of speed of IMs. Simulation results are presented to validate the proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.332-338
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• 2000

In this paper, a robust nonlinear excitation controller is proposed to achieve both voltage regulation and system stability enhancement for single machine-infinite power systems. The proposed method employs backstepping technique and combines this with an adaptation algorithm for estimating the effective reactance of transmission line, thereby leading to adaptive nonlinear control. Simulation results show that power that angle stabilization as well as voltage regulation is achieved in a satisfactory manner, regardless of the system operating conditions and system structure.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.32-43
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• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.371-372
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• 2008

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.308-314
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• 2005

Transient stabilization with voltage regulation is investigated for a synchronous generator when the mechanical power is perturbed to any unknown value within its physical bounds so that the operating point of the system shifts to an unknown point. An adaptive excitation controller is designed based on the backstepping method with tuning functions. It will be shown that the adaptive control law proposed can achieve the convergence of the system states to the new equilibrium point in correspondence with the real value of the unknown mechanical power and the regulation of the terminal voltage to the required value. Simulation results are given to demonstrate the effectiveness of the proposed controller for the transient stabilization and voltage regulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.12
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• pp.518-525
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• 2006

This paper presents the adaptive robust control method for the flight control systems with model uncertainties. The proposed control system can be composed simply by a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the 'explosion of complexity' problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems, and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.253-258
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• 2001

This paper introduces a simple nonlinear adaptive control method for pipeline inspection gauge (PIG) flow in natural gas pipeline. The dynamic behavior of the PIG depends on the different pressure across its body and the bypass flow through it. The system dynamics includes: dynamics of driving gas flow behind the PIG, dynamics of expelled gas in front of the PIG, and dynamics of the PIG. The method of characteristics (MOC) and Runger-Kuta method are used to solve the dynamics of flow. The PIG velocity is controlled through the amount of bypass flow across its body. A simple nonlinear adaptive controller based on the backstepping method is introduced. To derive the controller, three system parameters should be measured: the PIG position, its velocity and the velocity of bypass flow across the PIG body. The simulation has been done with a pipeline segment in the KOGAS low pressure system, Ueijungboo-Sangye line to verify the effectiveness of the proposed controller. Three cases of interest are considered: the PIG starts to move at its launcher, the PIG arrives at its receiver and the PIG restarts after stopping in the pipeline by obstruction. The simulation results show that the proposed nonlinear adaptive controller attained good performance and can be used for controlling the PIG velocity.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1848-1849
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• 2006

The new robust controller design method is proposed for the flight control systems with model uncertainties. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the "explosion of complexity" problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

• 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.