• 제어로봇시스템학회논문지
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• 제18권10호
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• International Journal of Aeronautical and Space Sciences
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• 제12권2호
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• pp.179-189
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• 2011

In this paper, robust adaptive control design problem is addressed for a class of parametrically uncertain aeroelastic systems. A full-state robust adaptive controller was designed to suppress aeroelastic vibrations of a nonlinear wing section. The design used leading and trailing edge control actuations. The full state feedback (FSFB) control yielded a global uniformly ultimately bounded result for two-axis vibration suppression. The pitching and plunging displacements were measurable; however, the pitching and plunging rates were not measurable. Thus, a high gain observer was used to modify the FSFB control design to become an output feedback (OFB) design while the stability analysis for the OFB control law was presented. Simulation results demonstrate the efficacy of the multi-input multi-output control toward suppressing aeroelastic vibrations and limit cycle oscillations occurring in pre- and post-flutter velocity regimes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.384-384
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• 2000

In adaptive neuro-control, neural networks are used to approximate the unknown plant nonlinearities. Until now, most of the papers in the field of controller design fur nonlinear system using neural networks considers the affine system with fixed number of neurons. This paper considers nonaffne nonlinear systems and dynamic variation of the number of neurons. Control laws and adaptive laws for weights are established so that the whole system is stable in the sense of Lyapunov.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.636-639
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• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1924-1929
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• 1991

The conventional sliding mode control and variable structure control (VSC) of nonlinear uncertain system are well known for their robust property and simplity of control law. However, the use of them is only pardonable on the assumption that the upper-bound of parameter variation or nonlinearity is known and that the complete information about state is available. Though the former has been solved with adaptive robust control theory recently, the latter seems not to be solved. In this paper, we try to solve this problem using the technique of VSS adaptive robust control theory. That is, we propose a VSS adaptive observer and a sliding mode control incorporated with this observer. We can prove the robust stability of the closed system applying the Lyapunov's second method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.37.2-37
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• 2001

This paper addresses the robust adaptive output feedback tracking for nonlinear systems under disturbances whose bounds are unknown. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The State estimation is solved using K-filters, together with the construction of a bound of an error in the state estimation due to the perturbation of the disturbance. Tuning functions are used to estimate unknown system parameters without overparametrization. The proposed control algorithm ensures that the out put tracking error converges to a residual set which can be arbitrarily small, while maintaining the boundedness of all other variables. A simulation shows the effectiveness of the proposed approach

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.64.2-64
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• 2002

Contents 1. Introduction $\textbullet$ Contents 2. System description $\textbullet$ Contents 3. Desired feedback control and function approximation $\textbullet$ Contents 4. Robust adaptive controller design $\textbullet$ Contents 5. Simulation study $\textbullet$ Contents 6. Conclusion

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1955-1959
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• 2005

This paper presents a systematic analysis and a simple design of a robust adaptive control law for a class of non linear systems with modeling errors and a time-delay input. The theory for designing a robust adaptive control law based on input- output feedback linearization of non linear systems with uncertainties and a time-delay in the manipulated input by the approach of parameterized state feedback control is presented. The main advantage of this method is that the parameterized state feedback control law can effectively suppress the effect of the most parts of nonlinearities, including system uncertainties and time-delay input in the pp-coupling perturbation form and the relative order of non linear systems is not limited.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.313-316
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• 1990

This paper proposes the design of the decentralized adaptive controllers which are an arbitrary interconnection of sub-systems with unknown parameters, nonlinear ities and bounded disturbances. In order to exponentially converge the state and parameter errors, robust decentralized adaptive controllers are developed for stabilization and tracking the parameters. In the simulation studies of the decentralized adaptive control of a two-area interconnected power system, the effectiveness of the proposed adaptive schemes is demonstrated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.187-190
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• 2003

In this paper, we address the robust adaptive backstepping controller using fuzzy neural network (FHIN) for a class of uncertain output feedback nonlinear systems with disturbance. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The state estimation is solved using K-fillers. All unknown nonlinear functions are approximated by FNN. The FNN weight adaptation rule is derived from Lyapunov stability analysis and guarantees that the adapted weight error and tracking error are bounded. The compensated controller is designed to compensate the FNN approximation error and external disturbance. Finally, simulation results show that the proposed controller can achieve favorable tracking performance and robustness with regard to unknown function and external disturbance.