Control Allocation Design for Torpedo-Like Underwater Vehicles with Multiple Actuators

Abstract

For solving the transformation problem between the desired nonlinear control laws and installed actuators’ input commands of torpedo-like underwater vehicles, one closed-form control allocation method is proposed in this article. The goal of this study is to optimally distribute the desired nonlinear control law to each single actuator installed on the torpedo-like underwater vehicle. The first step of this proposed control allocation method is to arrange the required types, numbers, and positions of the installed actuators and then build up the thrust configuration matrix for the developed torpedo-like underwater vehicle. In this step, the desired nonlinear control law can be optimally distributed to output commands of installed actuators based on the optimization method. Next, through collecting the input and output data of each installed actuator by practical experiments, the mathematical transformation of input and output commands of each installed actuator can be found. For verifying performance of this proposed control allocation method, simulations with the robust trajectory tracking design of a torpedo-like underwater vehicle with four fins, four rudders, and one thruster are executed in this investigation.

Addressing Actuator Saturation during Fault Compensation in Model-Based Underwater Vehicle Control

“…In [6], the formula u = B † τ c is used, where B † is the control allocation matrix calculated from pseudo-inverse of the AUV's actuator configuration matrix B. The use of the actuator configuration matrix pseudoinverse (Moore-Penrose inverse) for control allocation is also explored for underactuated and fully actuated underwater vehicle configurations [35][36][37]48]. For our controller, we replace the control allocation matrix B † with a dynamic term B that is updated based on actuator faultiness, so that the pseudo-inverse operation is no longer used.…”

“…The literature on control allocation for AUVs is not as plentiful as the works on control law design and is mainly focused on minimizing the individual actuator outputs to produce the desired control authority. This optimization has been achieved using linear and quadratic optimization [33,34], and the pseudo-inverse of the matrix corresponding to actuator configurations consisting purely of control surfaces [35,36] or thrusters [37,38]. Fault tolerance through control allocation is explored in the works regarding thruster configurations, where control is allocated to four thrusters using the pseudo-inverse of the actuator configuration matrix multiplied by weights based on thruster faultiness.…”

Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle

“…4,5 Thrusters as universal power components are often used in AUVs. 6,7 However, thrusters are prone to different faults due to terrible working conditions. 8 Thruster faults maybe not only make AUVs unable to complete the task, but also make them unable to recover themselves.…”