• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2138-2139
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• 2002

In this paper we presents a speed controller for separately excited DC motor using adaptive backstepping technique. The motor was modeled in two local areas the first model is a linear one when speed is under base speed, the other is nonlinear one when field weakening is used to obtain the speed well above base speed. Then linear robust state feedback controller was designed for the linear model while adaptive backstepping controller was designed for the nonlinear model. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed controller is proved to be asymptotically stable by the Lyapunov stability theory and some simulations have been carried out to test.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.292-300
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• 2009

This paper considers a robust adaptive stabilization problem for a class of uncertain nonlinear systems which include an unknown virtual control coefficient, an unknown constant parameter, and a time-varying disturbance whose bound is unknown, We propose a new estimator for an un-known virtual control coefficient and present a robust adaptive backstepping design procedure which results in a smooth state feedback control law, a new two-dimensional parameter update law, and a $C^1$ Lyapunov function which is positive definite and proper.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.181-184
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• 1996

This paper deals with the design problem of model reference adaptive controllers for MIMO plants with unknown orders. A design scheme for an adaptive control system based on CGT theorem, which has hierarchical structures derived from backstepping strategies, is proposed for MIMO plants with unknown orders but with known relative MacMillan degrees(relative degrees for SISO plants). It is also shown that all the signals in the resulting control system are bounded, and that the asymptotic tracking is achieved in the case where reference inputs are step.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.78-83
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• 2003

In this paper, it is dealt with a controller design problem for nonlinear systems with higher order relative degree. A robust adaptive control for uncertain nonlinear systems with stable zero dynamics will be proposed based on the high-gain adaptive output feedback and backstepping strategies. The proposed method is useful in the case where only the output signal is available.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.563-571
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• 2000

In this paper, a nonlinear adaptive control method for an EMS(Electro-Magnetic Suspension) system with mass uncertainty is proposed. Using the coordinate transformation and feedback linearizing control, EMS system has been transformed into the form of parametric strict-feedback system with unknown virtual control coefficients. With this transformed system, tuning functions approach, which is an advanced from of adaptive backstepping, has been applied in order to stabilize the system against mass uncertainty. Computer simulation is also carried out in order to compare the performance of the proposed controller with that of feedback linerizing controller.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.128-131
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• 2005

In this paper a robust controller using adaptive backstepping technique is proposed to control the speed of a wind turbine system. To make wind power generation truly cost effective and reliable, advanced and robust control algorithms are derived to on-line adjust the excitation winding voltage of the generator based on both mechanical and electrical dynamics. This method is shown to be able to achieve smooth and asymptotic rotor position tracking, as justified by analysis.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1227-1229
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• 2007

In this paper a robust controller using adaptive backstepping technique is proposed to control the position of wind power generation system. To make wind power generation truly cost effective and reliable, advanced and robust control algorithms are derived to on-line adjust the excitation winding voltage of the generator based on both mechanical and electrical dynamics. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by analysis and computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.405-413
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• 2006

In general mechanical servo systems, friction deteriorates the performance of controllers by its nonlinear characteristics. Especially, friction phenomenon causes steady-state tracking errors and limit cycles in position and velocity control systems, even though gains of controllers are tuned well in linear system model. Even if sensor is used higher accuracy level, it is difficult to improve tracking performance of the position to the same level with a general control method such as PID type. Therefore, many friction models were proposed and compensation methods have been researched actively. In this paper, we consider that the variation of mover's mass is various by loading and unloading. The normal force variation occurs by it an other parameters. Therefore, the proposed control system is composed of main position controller and a friction compensator. A parameter estimator for a nonlinear friction model is designed by adaptive control law and adaptive backstepping control method.