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 ...

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...

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...

Compared with traditional aircraft, the near space hypersonic unmanned aerial vehicle control system design must deal with the extra prominent dynamics characters, which are differ from the traditional aircrafts control system design. A new robust adaptive control design method is proposed for one hypersonic unmanned aerial vehicle (HSUAV) uncertain MIMO nonaffine block control system by using ...

This paper presents a new strategy to improve the performances of speed control of a Double-Fed Induction Machine (DFIM), whose stator and rotor windings are connected to a voltage inverter PWM (Pulse Width Modulation) independently. This work shows the robustness of the adaptive Backstepping control strategy applied to the DFIM. The main objective of this work is to stabilize the speed of the ...

This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based...

The dynamics model considering payload eccentricity and friction effects of an omni-directional mobile robot is first derived using Lagrange’s equation. Based on the dynamics model with uncertainty, a stable adaptive fuzzy control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term and a fuzzy fun...

This study contrives a discrete-time adaptive decentralized control algorithm with input quantization for interconnected multi-machine power systems SVC. First, dynamic surface scheme is applied to the excitation controller design, in which first-order digital low-pass filters are used predict next virtual law, overcomes model conversion problem backstepping. Therefore, design and structure sim...

This paper proposes an adaptive backstepping control strategy for a class of uncertain non affine systems using self recurrent neural networks. To assure the stable tracking of nonlinear non affine system, it is first converted to an affine like form and subsequently a wavelet based adaptive backstepping controller is developed. Self recurrent wavelet neural network (SRWNN) is used to approxima...

Backstepping method is a successful approach to deal with the systems in strict-feedback form. However, for networked control systems, discontinuous virtual law caused by state quantization introduces huge challenges its applicability. In this article, quantized adaptive robust backsetpping framework developed article nonlinear both and input quantization. order prove efficiency of designed sch...