Robust generalized dynamic inversion based control of autonomous underwater vehicles

Abstract

A novel two-loop structured robust generalized dynamic inversion-based control system is proposed for autonomous underwater vehicles. The outer (position) loop of the generalized dynamic inversion control system utilizes proportional-derivative control of the autonomous underwater vehicle's inertial position errors from the desired inertial position trajectories, and it provides the reference yaw and pitch attitude angle commands to the inner loop. The inner (attitude) loop utilizes generalized dynamic inversion control of a prescribed asymptotically stable dynamics of the attitude angle errors from their reference values, and it provides the required control surface deflections such that the desired inertial position trajectories of the vehicle are tracked. The dynamic inversion singularity is avoided by augmenting a dynamic scaling factor within the Moore-Penrose generalized inverse in the particular part of the generalized dynamic inversion control law. The involved null control vector in the auxiliary part of the generalized dynamic inversion control law is constructed to be linear in the pitch and yaw angular velocities, and the proportionality gain matrix is designed to guarantee global closed-loop asymptotic stability of the vehicle's angular velocity dynamics. An additional sliding mode control element is included in the particular part of the generalized dynamic inversion control system, and it works to robustify the closed-loop system against tracking performance deterioration due to generalized inversion scaling, such that semi-global practically stable attitude tracking is guaranteed. A detailed six degrees-of-freedom mathematical model of the Monterey Bay Aquarium Research Institute autonomous underwater vehicle is used to evaluate the control system design, and numerical simulations are conducted to demonstrate closed-loop system performance under various types of autonomous underwater vehicle maneuvers, under both nominal and perturbed autonomous underwater vehicle system's mathematical model parameters.

Genetic Algorithm-Based Tuning of Backstepping Controller for a Quadrotor-Type Unmanned Aerial Vehicle

“…Quadrotors have very simple mechanics since the control of their position is determined by the changes in speed in their motors and they are used when high maneuverability is required, since they are capable of moving in any direction or flying at low speeds. Due to the complexity of the system, different algorithms have been developed to achieve autonomous control in Unmanned Aerial Vehicles, using techniques from linear control methodologies with PID [10,11], to nonlinear control techniques 2 of 24 such as Feedback Linearization control, model predictive control, adaptive control approaches [12], fail-safe methodologies based on sliding mode control theory and backstepping control [13,14], combinations such as Adaptive Sliding Backstepping Control [15][16][17], diffuse control in the proposal of Geometric Control [18,19], Nonlinear Dynamic In-version (NDI) Control [20], the Robust Generalized Dynamic Inversion (RGDI) Quadcopter Control System [21] and the Neural Network Control System of UAV Altitude Dynamics [22][23][24][25]; most of these state-of-the-art nonlinear and adaptive control techniques for quadrotors were discussed by Hongwei and Ghulam.…”

Quadrotor Control Via Robust Generalized Dynamic Inversion and Adaptive Non‐Singular Terminal Sliding Mode

“…However, GDI control avoids the main limitations and shortcomings of NDI in its implementations to control complex and highly-nonlinear aerospace systems, namely the difficulties in controlling under-actuated dynamics and nonholonomicity, the simplifying approximations that are usually needed to invert nonlinear plants, the square dimensionality restriction, singular configurations of square inversion, elimination of useful nonlinearities, and high controls magnitudes. By avoiding these disadvantages, GDI control has been capable to solve challenging aerospace control problems [22][23][24][25][26][27][28].…”

Positional control of rotary servo cart system using generalized dynamic inversion

“…Hence GDI methodology overcome the limitations associated with classical Nonlinear dynamic inversion control, which includes cancellation of useful nonlinearities, simplifying assumptions required to invert the nonlinear plant dynamics, large control effort and square dimensionality restrictions. GDI control technique had been applied for several aerospace and robotics applications [20][21][22][23][24][25][26].…”