• 전기학회논문지
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• 제57권5호
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2006년도 전력전자학술대회 논문집
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• pp.526-528
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• 2006

An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

• 전기학회논문지
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• 제58권9호
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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.

• International Journal of Control, Automation, and Systems
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• 제6권3호
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• pp.364-377
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• 2008

Due to the difficulty in solving the Hamilton-Jacobi-Isaacs equation, the nonlinear optimal control approach is not very practical in general. To overcome this problem, Ezal et al. (2000) first solved a linear optimal control problem for the linearized model of a nonlinear system given in the strict-feedback form. Then, using the backstepping procedure, a nonlinear feedback controller was designed where the linear part is same as the linear feedback obtained from the linear optimal control design. However, their construction is based on the cancellation of the high order nonlinearity, which limits the application to the smooth ($C^{\infty}$) vector fields. In this paper, we develop an alternative method for backstepping procedure, so that the vector field can be just $C^1$, which allows this approach to be applicable to much larger class of nonlinear systems.

• 전기학회논문지P
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• 제54권3호
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• pp.119-128
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• 2005

In this paper, an robust adaptive backstepping controller is proposed for the chaos system with disturbances. This controller will be applicable to the chaos system of strict-feedback form and utilize the saturation function for decreasing the effect of disturbances derived from unmodelled dynamics and external noise. It shows that backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.

• 한국통신학회논문지
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• 제33권7A호
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• pp.768-775
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• 2008

본 논문에서는 부분적 채널 피드백 정보를 이용하는 다중사용자 직교 주파수 분할다중화 시스템의 하향링크 전송성능을 고려한다. 특히, 두 종류의 부분적 채널 정보 궤환 방식을 고려하는데 첫째는 부반송파 당 1비트의 정보만을 이용하는 1비트(1bit per sub-carrier) 궤환 방법과 선택적으로 채널정보를 궤환하는 선택적 궤환(selective feedback) 방법을 비교 분석한다. 사용자당 주어진 피드백 비트 수에 대한 절대적인 비교 분석은 매우 어려우므로 대신에 각 방법에서의 설계 파라미터에 따른 성능 곡선을 분석함으로써 실제 시스템에의 적용에 필요한 정보를 제공하고자 한다.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.513-522
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• 2006

This paper considers a robust output feedback $H\infty$ controller design method for singular systems with time-varying delay in state and parameter uncertainty in system matrix by an LMI approach and observer based technique, which can be solved efficiently by convex optimization. The sufficient condition for the existence of controller and the controller design method are presented by strict LMI(linear matrix inequality) approach. Since the obtained condition can be expressed as an LMI form, all variables including feedback gain and observer gain can be calculated simultaneously by Schur complement and changes of variables.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권10호
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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.

• 대한기계학회논문집A
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• 제28권12호
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• pp.1833-1844
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• 2004

A controller is proposed for the robust backstepping control of a class of nonlinear multiple-input multiple-output (MIMO) systems which can be converted to a strict feedback form. The proposed robust backstepping control scheme follows a systematic procedure for the design of control laws and uses time delay estimation (TDE) to estimate the uncertainties such as parameter variations, unknown disturbances, and unmodeled dynamics, etc. The proposed controller can be also applied to nonlinear MIMO systems with unmatched uncertainties. Stability analysis of the closed-loop system which contains the plant and the proposed controller is also studied and hereby a sufficient stability condition for the closed-loop system is proposed. The simulation results show that the control scheme works well with uncertainties and the proposed stability condition is valid. The controller is experimentally verified on a single-link flexible arm to show the effectiveness of the proposed scheme in the complicated systems with uncertainties.

• Steel and Composite Structures
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• 제52권5호
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• pp.571-581
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• 2024

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. This work studies the tracking control problem of a class of strict-feedback nonlinear systems with input saturation nonlinearity. Under the framework of dynamic surface control design, RBF neural networks are introduced to approximate the unknown nonlinear dynamics. In order to address the impact of input saturation nonlinearity in the system, an auxiliary control system is constructed, and by introducing a class of first-order low-pass filters, the problems of large computation and computational explosion caused by repeated differentiation are effectively solved. In response to unknown parameters, corresponding adaptive updating control laws are designed. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.