A passive output feedback controller with wave filter for marine vehicles

Two methods for course-keeping of a ship are studied where no measurements of the yaw rate are available. The two methods are a passive output feedback controller and a controller-observer structure. A comparison with special attention to stability and wave filtering properties, is provided. Finally, a case study of a ship autopilot is included.

In a Global Navigation Satellite System (GNSS) receiver the presence of detection and mitigation units, capable of reducing the impact of disturbing signals, can extremely enhance the position accuracy. However the presence of such units is usually limited to professional receivers that dispose of additional computational power that can be used for interference detection and mitigation. In this paper the two-pole notch filter, the natural extension of the one-pole notch filter analyzed in [1], is proposed as computationally effective solution for interference detection and mitigation. The notch filter structure and the adaptive algorithm employed for tracking the disturbing signal are analyzed, and an interference detection unit, based on the adaptive algorithm convergence, is proposed. The two-pole notch filter coupled with the detection unit is used as elementary block for the design of a multi-pole notch filter that can efficiently mitigate more than one CW interference. Theoretical and simulative analyses show the feasibility and the good performance of the proposed method.

The synthesis procedure is applied to different notch filter structures with constrained parameters. Asymptotic results that give analytical insight into notch filter synthesis using parameter constrained filter structures are derived.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Observer-based neural network adaptive control scheme (OBNC) for underwater vehicles is proposed in this paper. Three parts compose the scheme: output feedback control, neural network and sliding mode item. Where, the output feedback control is used to guarantee the stability of the system in initial phase, and the neural network is used to approximate the nonlinear dynamics of underwater vehicles and the sliding mode item is used to compensate and bate the internal and external disturbances. A linear observer is designed to estimate the corresponding rate and the control system is designed with only position measurement. The stability conditions and attraction region of the proposed scheme is provided by using Lyapunov-based approach. The effectiveness of the proposed control scheme is demonstrated by the pool experiment.

This paper analyzes the passivity and feedback passivity of discrete-time-switched nonlinear systems with passive and nonpassive modes that are affine in the control input. When a nonpassive mode is active, the increase in storage function is not necessarily bounded by the energy supplied to the switched system at every time step. Therefore, a switched system with at least one nonpassive mode is defined to be nonpassive in the classical passivity theory. In this paper, we propose a framework to analyze the passivity of such switched systems in a more general sense. We consider switched nonlinear systems which are affine in the control input and may consist of passive, feedback passive modes, and modes which cannot be rendered passive using feedback. In the proposed framework, we prove that a switched nonlinear system is locally feedback passive if and only if its zero dynamics are locally passive. A lower bound on the ratio of total activation time between (feedback) passive and nonfeedback passive modes is obtained to guarantee passive zero dynamics. Finally, we prove that two important properties of classical passivity still hold for the proposed passivity definition, that is: 1) output feedback control can be used to stabilize the switched system, and 2) parallel and negative feedback interconnections of two such passive systems are also passive.

In this paper, the problem of designing numerically stable recursive estimators for adaptive Wave Filtering (WF) of marine vessels is addressed. The WF technique consists of a recursive optimization procedure to identify the dominant wave frequency (the uncertain parameter) by minimizing an appropriate defined performance index and the application of the Kalman filter for dynamic positioning purpose. The computational approach yields to a set of the filter sensitivity equations and a set of matrix Riccati-type sensitivity equations. Recently proposed WF methodology [1] is based on the conventional Kalman filter and its derivatives (with respect to unknown system parameters) that is known to be numerically unstable. To improve the numerical stability we are focusing in the techniques developed in the Kalman filtering community to solve ill conditioned problems. More precisely, here the square-root variant of the adaptive WF scheme is designed to improve accuracy and robustness for a finite-precision computer arithmetics. Then, it is examined on the dynamic positioning model of marine vessels.

Due to the uncertainty in vehicle model parameters, the control performance of active suspensions often deteriorates, especially under extreme conditions such as high velocities and full loads. To address this challenge, this paper proposes a novel robust finite frequency H ∞ output feedback control strategy based on linear parameter varying (LPV) systems. First, we establish a new LPV model for the half-car active suspension control system, taking into account the uncertainties associated with vehicle velocity and sprung mass. Next, a robust finite frequency H ∞ output feedback controller is designed using a gain scheduling approach, formulated through a set of linear matrix inequalities (LMIs). Finally, simulation results demonstrate that the proposed velocity-dependent robust control strategy significantly reduces the root mean square (RMS) values of vertical acceleration by approximately 21% to 31% under various conditions of sprung mass and vehicle speed compared to traditional control methods.

This paper develops an adaptive output feedback controller that forces an autonomous underwater vehicle (AUV), named Omni-Directional Intelligent Navigator (ODIN), to track a desired trajectory with bounded errors in wave disturbance condition. An adaptive controller is introduced based on a nonlinear model whose measurable output is corrupted by wave disturbances. Thus an observer is built to reconstruct the full states including wave velocity, wave motion displacement, vehicles velocity, position and rotation angle information which are used in the output feedback controller. Ultimate boundedness of the error signals is shown through Lyapunovs direct method. Finally, simulation studies for ODIN illustrate the effectiveness of the proposed control scheme.

This paper presents an exact static error dynamics passive output feedback controller to regulate the output voltage of the DC-to-DC power converter Cuk type; this controller is obtained from the error dynamics of the nonlinear average model of the converter. In order to compensate the effects of sudden changes in the load resistance, the desired reference variables for the regulation task are calculated using the estimated load value obtained via an algebraic estimator. The results are validated in an experimental laboratory setup.

Both dynamic state feedback as well as output feedback tracking control designs are presented in this paper for constrained robot systems under parametric uncertainties and external disturbances. The previous studies on tracking control design, not considering the velocity measurements, address only the unconstrained robot design. In contrast, a dynamic output feedback controller based on a linear and reduced-order observer that uses only position measurements is proposed here for the first time to treat the trajectory tracking control problem of constrained robot systems. Both adaptive state feedback control schemes and adaptive output feedback control schemes with a guaranteed H∞ performance are constructed. It is shown that all the variables of the closed-loop system are bounded and a pre-assigned H∞ tracking performance is achieved, in the sense that the influence of external disturbance on the tracking motion error can be attenuated to any specified level. Moreover, it is also shown that the motion and force trajectories asymptotically converge to the desired ones as the dynamic model of robot systems is well-known and the external disturbance is neglected. Finally, simulation examples are presented to illustrate the tracking performance of a two-link robotic manipulator with a circular path constraint by the proposed control algorithms. © 1998 John Wiley & Sons, Ltd.

In this paper a comparative analysis of Mamdani and Sugeno type fuzzy autopilots for ships is given. Both autopilots have two inputs: the heading signal and the yaw rate signal, and only one output: command rudder angle. Input variable fuzzification, fuzzy associative memory (FAM) rules, and output set defuzzification are described. The control system for the course-keeping composed of the nonlinear ship, the steering gear servo system, fuzzy autopilot and wave disturbance is described. Both autopilots are compared in three different sailing conditions: without wave disturbance, with wave disturbance and with wave disturbance and wave filtering. The notch filter was used for filtering of second-order wave disturbances. The influence of wave disturbance on course-keeping performance was analyzed. Even though the obtained performance in simulations are very similar, authors prefer Sugeno type fuzzy autopilot, due to less strain of the steering gear servo system and faster and more accurate heading obtained.

In this paper, it is shown that an input-output (I/O) feedback linearized controller can be designed rationally by utilizing the time-scale properties of heave and pitch for an underwater vehicle. It is assumed that the dynamics of the vehicle is restricted to the vertical plane. An output-feedback control is designed, which stabilizes steady cruising paths. It is shown that the vehicle dynamics with acceleration as output becomes minimum phase. The dynamics can be transformed into a reduced system through a kind of partial linearization and singular perturbation technique. The reduced system is not only minimum phase but also exactly I/O linearizable via feedback. The I/O dynamic characteristics of the heave and pitch modes can be made linear and decoupled. Furthermore it becomes independent of cruising condition such as vehicle velocity. This study may help for designing autopilot systems for underwater vehicles.

Position and attitude measurement of high-speed isolates for hypersonic facilities

Output feedback passification problem is studied when the given system is not minimum-phase or does not have relative degree one. Using a parallel connection with an additional dynamics, the authors provide a dynamic output feedback control law which renders the composite system passive. For linear time-invariant systems, a necessary and sufficient condition for designing an input-dimensional additional system is presented. Motivated by the dynamic passification scheme, a point-to-point control law for an elastic joint robot is presented when only the position measurements are available. This provides an alternative way of replacing the role of the velocity measurements for the proportional-derivative (PD) feedback law. The performance of the proposed control law is illustrated in the simulation studies of a manipulator with three revolute elastic joints.

An Adaptive Output Feedback Controller for Robot Arms: Stability and Experiments