In this paper, a novel biologically inspired neural network approach is proposed for real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a nonstationary environment. The real-time robot trajectory with obstacle avoidance is generated by a topologically organized neural network, where the dynamics of each neuron is characterized by a shunting equation. T...

In this paper we present a new design method for the fight control of an autonomous quadrotor helicopter based on fuzzy sliding mode control using backstepping approach. Due to the underactuated property of the quadrotor helicopter, the controller can move three positions (x,y,z) of the helicopter and the yaw angle to their desired values and stabilize the pitch and roll angles. A first-order n...

A nonlinear adaptive controller for the quadrotor helicopter is proposed using backstepping technique mixed with neural networks. The backstepping strategy is used to achieve good tracking of desired translation positions and yaw angle while maintaining the stability of pitch and roll angles simultaneously. The knowledge of all physical parameters and the exact model of the quadrotor are not re...

This paper presents neural adaptive control methods for a class of nonlinear systems in the presence of actuator saturation. Backstepping technique is widely used for the control of nonlinear systems. By introducing alternative state variables and implementing state transformation, the system can be reformulated as output feedback of a canonical system, which ensures that the controllers can be...

This study deals with the control chaos using generalized backstepping method. This new method to control nonlinear systems was called generalized backstepping method because of its similarity to backstepping but its abilities to control more systems than backstepping. Generalized backstepping approach consists of parameters which accept positive values. The parameters are usually chosen option...

Abstract: This study is aimed at introducing a new robust control strategy in developed backstepping method designed for a special class of nonlinear systems, which does not require any information on the upper bound of parametric uncertainties. A robust generalized backstepping method (RGBM) is introduced by using of both generalized backstepping method and nonlinear damping of Lyapunov redesi...

In this paper, a nonlinear adaptive speed controller for a permanent magnet synchronous motor (PMSM) based on a newly developed adaptive backstepping approach is presented. The exact, input-output feedback linearization control law is first introduced without any uncertainties in the system. However, in real applications, the parameter uncertainties such as the stator resistance and the rotor f...

The backstepping technique was used in order to synthesise a non-linear control law for the non-linear model of the power plant station. The non-linearities in the model are related to steam flow through the super-heater and action of turbine valves. The time constant of the boiler is considered as an unknown parameter. Its value has to be adapted. The backstepping procedure presents a straight...

This paper represents a robust backstepping tracking control based on a Lyapunov redesign for Skid‐Steered Wheeled Mobile Robots (WMRs). We present kinematic and dynamic models that explicitly relate the perturbations to the skidding in order to improve the tracking performance during real running. A robust controller is synthesized in the backstepping approach ...

Backstepping is a nonlinear control design tool for underactuated systems. Backstepping is used for output stabilization or tracking using feedback similarly to feedback linearization. In feedback linearization the stabilizing controller is designed entirely for a virtual input which is then mapped back to the physical input by completely canceling nonlinearities. In backstepping the system is ...