This paper investigates the attitude tracking problem for rigid spacecraft. An adaptive backstepping sliding mode control law is proposed to solve this problem in the presence of inertia uncertainties and external disturbances. The control scheme is developed by combining sliding mode control with adaptive backstepping technique to achieve fast and accurate tracking responses. The proposed cont...

This paper is concerned with the control of a class of chaotic systems using adaptive backstepping, which is a systematic design approach for constructing both feedback control laws and associated Lyapunov functions. Firstly, we show that many chaotic systems as paradigms in the research of chaos can be transformed into a class of nonlinear systems in the so-called nonautonomous “strict-feedbac...

Design of adaptive backstepping control for stabilization and synchronization a class uncertain fractional-order chaotic systems with uncertainties disturbances

For the actuators fault of reconfigurable modular robots, a backstepping decentralized fault tolerant control (DFTC) algorithm is proposed. The reconfigurable robot system is divied into a set of interconnected subsystems. The fault tolerant controller is designed based on backstepping method. It is hard to obtain the model parameters uncertainty term and interconnected term, so the adaptive fu...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NONLINEAR CONTROL FOR SYSTEMS CONTAINING INPUT UNCERTAINTY VIA A LYAPUNOV-BASED APPROACH By William MacKunis May 2009 Chair: Dr. Warren E. Dixon Major: Aerospace Engineering Controllers are often designed based on the assumption that a c...

This paper proposes an improved learning algorithm of analog compound orthogonal networks and a novel tracking control approach for nonholonomic mobile robots by integrating the neural network into the backstepping technique. The adaptive control is derived from continuously tuning parameters using the analog neural network in the backstepping control law. The proposed control approach for the ...

With increasing marine transportation and logistics, the ship autopilot has become much more important not only to lower the seaman's operating intensions, but also to reduce the seaman's deployment. It is still a challenge to design ship coursekeeping controller because of ship's uncertain dynamics and time-varying environmental disturbance. This study focuses on backstepping adaptive course-k...

In order to achieve the accurate trajectory tracking of 2 degree-of –freedom robot, a backstepping adaptive fuzzy control scheme based on Lyapunov method, is presented for the SCARA (Selective Compliance Assembly Robot Arm) robot system. The control strategy consists of the traditional backstepping control and adaptive fuzzy control to cope with the model unknown and parameter disturbances. The...

This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion e...

Abstract This paper presents a novel method for designing an adaptive control system using radial basis function neural network. The is capable of dealing with nonlinear stochastic systems in strict-feedback form any unknown dynamics. proposed network allows the not only to approximate dynamic systems, but also compensate actuator nonlinearity. By employing surface method, common problem that i...