Mugdha S. Naik’s research while affiliated with University of Nevada, Las Vegas and other places

This paper treats the question of servoregulation of autonomous underwater vehicles (AUVs) in the yaw plane using pectoral-like mechanical fins. The fins attached to the vehicle have oscillatory swaying and yawing motion. The bias angle of the angular motion of the fin is used for the purpose of control. Of course, the design approach considered here is applicable to AUVs for other choices of oscillation patterns of the fins, which produce periodic forces and moments. It is assumed that the vehicle parameters, hydrodynamic coefficients, as well the fin forces and moments are unknown. For the trajectory control of the yaw angle, a sampled-data indirect adaptive control system using output (yaw angle) feedback is derived. The control system has a modular structure, which includes a parameter identifier and a stabilizer. For the control law derivation, an internal model of the exosignals (reference signal (constant or ramp) and constant disturbance) is included. Unlike the direct adaptive control scheme, the derived control law is applicable to minimum as well as nonminimum phase biorobotic AUVs (BAUVs). This is important, because for most of the fin locations on the vehicle, the model is a nonminimum phase. In the closed-loop system, the yaw angle trajectory tracking error converges to zero and the remaining state variables remain bounded. Simulation results are presented which show that the derived modular control system accomplishes precise set point yaw angle control and turning maneuvers in spite of the uncertainties in the system parameters using only yaw angle feedback.

This article considers the control of a biorobotic autonomous underwater vehicle BAUV in the yaw plane using biologically inspired oscillatory pectoral-like fins of marine animals. The fins are assumed to be oscillating harmonically with a combined linear sway and angular yaw motion producing unsteady forces, which are used for fish-like control of BAUVs. Manoeuvring of the BAUV in the yaw plane is accomplished by altering the bias mean angle of the angular motion of the fin. For the derivation of the adaptive control system, it is assumed that the physical parameters, the hydrodynamic coefficients, and the fin force and moment are not known. A direct adaptive sampled-data control system for the trajectory control of the yaw-angle using only yaw-angle measurement is derived. The parameter adaptation law is based on the normalised gradient scheme. Simulation results for the set point control, sinusoidal trajectory tracking and turning manoeuvres are presented, which show that the control system accomplishes precise trajectory control in spite of the parameter uncertainties.

The paper treats the question of suboptimal dive plane control of autonomous underwater vehicles (AUVs) using the state-dependent Riccati equation (SDRE) technique. The SDRE method provides an effective mean of designing nonlinear control systems for minimum as well as nonminimum phase AUV models. It is assumed that the hydrodynamic parameters of the nonlinear vehicle model are imprecisely known, and in order to obtain a practical design, a hard constraint on control fin deflection is imposed. The problem of depth control is treated as a robust nonlinear output (depth) regulation problem with constant disturbance and reference exogenous signals. As such an internal model of first-order fed by the tracking error is constructed. A quadratic performance index is chosen for optimization and the algebraic Riccati equation is solved to obtain a suboptimal control law for the model with unconstrained input. For the design of model with fin angle constraints, a slack variable is introduced to transform the constrained control input problem into an unconstrained problem, and a suboptimal control law is designed for the augmented system using a modified performance index. Using the center manifold theorem, it is shown that in the closed-loop system, the system trajectories are regulated to a manifold (called output zeroing manifold) on which the depth tracking error is zero and the equilibrium state is asymptotically stable. Simulation results are presented which show that effective depth control is accomplished in spite of the uncertainties in the system parameters and control fin deflection constraints.

This paper treats the question of adaptive control of a biorobotic autonomous underwater vehicle (BAUV) in the yaw plane using biologically-inspired pectoral-like fins. The fins are assumed to be oscillating harmonically with a combined linear (sway) and angular (yaw) motion. The bias (mean) angle of the angular motion of the fin is used as a control input. Oscillatory fins produce periodic time-varying control forces and moments. It is assumed that the physical parameters, the hydrodynamic coefficients, and the fin force and moment are not known to the designer. Using a discrete-time state variable representation of the BAUV, an adaptive sampled data control system for the trajectory control of the yaw angle using state feedback is derived. The parameter adaptation law is based on the normalized gradient scheme. In the closed-loop system, time-varying yaw angle reference trajectories are tracked and all the signals in the closed-loop system remain bounded. Simulation results for the set point control and sinusoidal trajectory tracking are presented, which show that the control system accomplishes precise trajectory control in spite of the parameter uncertainties, and the inter sample segments of the yaw angle trajectory remain close to the discrete-time reference trajectory.