Robust Trajectory Tracking Control for Uncertain 3-DOF Helicopters With Prescribed Performance

Abstract

This article presents a robust control scheme for the trajectory tracking problem of a three-degree-offreedom helicopter with prescribed transient and steadystate performance. The control design does not employ any information regarding the dynamics of the system. In addition, the transient and steady-state response of the system with respect to a given time-varying trajectory is a priori and explicitly imposed by certain designer-specified performance functions and is fully decoupled from the control gain selection and the dynamic model parameters. Finally, both simulation and experimental results verify the theoretical findings.

Robust Trajectory Tracking for Underactuated Quadrotors with Prescribed Performance

“…2, thus achieving desired performance specifications, such as maximum overshoot, convergence speed, and maximum steady-state error. However, as mentioned before, the USV model ( 1) is underactuated, and hence the original PPC methodology cannot be directly applied [24], [25]. Consequently, we modify the PPC methodology to achieve trajectory tracking with prescribed performance for the position.…”

Real-time measurement-driven reinforcement learning control approach for uncertain nonlinear systems

“…Many adaptive approaches have been designed offline and lack the ability to capture high-order modelfollowing dynamics [3][4][5][6]. Hence, many adaptive learning approaches employ either complex or computationally expensive algorithms [5][6][7][8]. This gets more challenging when adaptive mechanisms are adopted for coupled regulation and optimization missions, where the dimensions of the state and action spaces grow significantly [9][10][11].…”

“…Measurement-driven solutions based on adaptive learning concepts are challenged by many factors, such as the need to incorporate the dynamics of the process explicitly into the underlying strategies [1,2]. Many adaptive approaches have been designed offline and lack the ability to capture high-order modelfollowing dynamics [3][4][5][6]. Hence, many adaptive learning approaches employ either complex or computationally expensive algorithms [5][6][7][8].…”

Fault‐tolerant attitude tracking control of tandem rotor helicopter considering internal actuator saturation and external wind gust

“…Zheng et al 30 proposed a robust linear control to improve the transient and steady‐state tracking performance of the system. Verginis et al 31 proposed a robust control scheme independent of system dynamics information to solve the attitude tracking problem of 3‐dof helicopter. Yang et al 32 proposed an adaptive neural network backstepping control design method for a 3‐dof helicopter based on the radial basis function neural network with online gradient descent training.…”