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ABSTRACT: A finite-time attitude tracking control scheme is proposed for spacecraft using terminal sliding mode and Chebyshev neural network (NN) (CNN). The four-parameter representations (quaternion) are used to describe the spacecraft attitude for global representation without singularities. The attitude state (i.e., attitude and velocity) error dynamics is transformed to a double integrator dynamics with a constraint on the spacecraft attitude. With consideration of this constraint, a novel terminal sliding manifold is proposed for the spacecraft. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated unknown function, a switch function is applied to generate a switching between the adaptive NN control and the robust controller. Meanwhile, a CNN, whose basis functions are implemented using only desired signals, is introduced to approximate the desired nonlinear function and bounded external disturbances online, and the robust term based on the hyperbolic tangent function is applied to counteract NN approximation errors in the adaptive neural control scheme. Most importantly, the finite-time stability in both the reaching phase and the sliding phase can be guaranteed by a Lyapunov-based approach. Finally, numerical simulations on the attitude tracking control of spacecraft in the presence of an unknown mass moment of inertia matrix, bounded external disturbances, and control input constraints are presented to demonstrate the performance of the proposed controller.
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 09/2011; · 3.08 Impact Factor
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ABSTRACT: This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.
IEEE Transactions on Neural Networks 10/2010; · 2.95 Impact Factor
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ABSTRACT: This paper investigates the robust stability of an asymptotic second-order sliding mode (2nd-SM) control system, where a first-order sliding mode (1st-SM) control law is implemented to realize an asymptotic 2nd-SM control for a linear time-invariant continuous-time system with a relative degree of two. It is found in the paper that a 2nd-SM can be reached locally and asymptotically by a 1st-SM control law if the sum of the system poles is less than the sum of the system zeros. The asymptotic convergence to the 2nd-SM and the robust stability of the asymptotic 2nd-SM control system are for the first time proved with Lyapunov functions, in the presence of matched external disturbances and parameter uncertainties. Finally, the effectiveness of the asymptotic 2nd-SM control algorithm is verified through numerical simulations.
Information and Automation (ICIA), 2010 IEEE International Conference on; 07/2010
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ABSTRACT: A variable structure control (VSC) algorithm is proposed with a nonlinear time-varying (NTV) sliding sector for a class of nonlinear time-variant systems represented in a state-dependent linear time-variant form. The NTV sliding sector, a subset of the state space is designed by the state-dependent differential Riccati equation (SDDRE). A VSC law is designed such that the system enters the sliding sector in finite time and a Lyapunov function candidate decreases inside the NTV sliding sector. An NTV control and a sliding mode control algorithms are proposed based on the solution of the SDDRE as well.
IEEE Transactions on Automatic Control 09/2009; · 2.11 Impact Factor
