Steering Autopilot Research Articles

Robust nonlinear PD controller for ship steering autopilot system based on particle swarm optimization technique

This paper proposes a new approach for robust nonlinear proportional derivative (PD) controller. In this approach a nonlinear function (sigmoid) is added to the conventional proportional integral derivative (PID) controller with filtering for the derivative, in order to improve system response and to reduce the effects of the nonlinearity and uncertainty due to variations of hydrodynamic coefficients of ship with the speed. The gains of nonlinear PD controller are tuned by applying particle swarm optimization (PSO) technique. The simulated results by MATLAB program give satisfactory performance with regard to maximum overshoot, settling time and zero steady state error for step, ramp and proposed trajectory as input to the system. The robustness of the autopilot was checked by changing the plant parameters and adding disturbance to the plant input. The used autopilot is nonlinear PD controller because the gain of integral term by PSO is approximately zero which simplifies the controller construction. The results show that the proposed controller has superior transient response and robustness on the conventional PID designed by using symmetrical optimum criterion with pole assignment technique.

Sliding mode control design of a ship steering autopilot with input saturation

In this article, a sliding mode control scheme for the autopilot system of a ship is presented, which also incorporates actuator saturation. Under the designed controller, the actuator doesn’t ente...

GESO based robust output tracking controller for marine vessels

In this paper, a novel design for robust steering autopilot for marine surface vessels is proposed. As the uncertainties and disturbances acting on the ship due to external environmental effects, model inaccuracies, parametric variations, and nonlinearities of rudder movement are matched as well as mismatched, Generalized Extended State Observer (GESO) is used to estimate them. A composite design consisting of an output tracking state feedback controller augmented by GESO derived disturbance compensation term is formulated. Stability of the resulting closed-loop system is established and the efficacy of the controller is demonstrated through simulations by considering various practical circumstances. The results show that the controller offers highly satisfactory tracking performance in the presence of significant matched as well as mismatched uncertainties and disturbances.

Dead‐Zone Model Based Adaptive Backstepping Control for a Class of Uncertain Saturated Systems

AbstractIn this paper, a dead‐zone based model of saturation phenomena is proposed. This method is capable of modelling diverse kinds of saturation, including both hard‐limited and soft‐limited. Due to use of a linear parameter approach, the proposed model is consistent with the available adaptive control techniques in the literature. In addition, based on the proposed model, an adaptive controller is designed for a class of nonlinear saturated systems, where, the shape of the saturation phenomenon is assumed to be unknown. The effectiveness of the proposed method and its robustness against initial condition variation and reference signal is evaluated via simulated examples for both spring–mass–damper and ship steering autopilot systems.

Design of robust fuzzy controller for ship course-tracking based on RBF network and backstepping approach

This study presents an adaptive fuzzy neural network (FNN) control system for the ship steering autopilot. For the Norrbin ship steering mathematical model with the nonlinear and uncertain dynamic characteristics, an adaptive FNN control system is designed to achieve high-precision track control via the backstepping approach. In the adaptive FNN control system, a FNN backstepping controller is a principal controller which includes a FNN estimator used to estimate the uncertainties, and a robust controller is designed to compensate the shortcoming of the FNN backstepping controller. All adaptive learning algorithms in the adaptive FNN control system are derived from the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. The effectiveness of the proposed adaptive FNN control system is verified by simulation results.

Model reference adaptive robust fuzzy control for ship steering autopilot with uncertain nonlinear systems

A novel model reference adaptive robust fuzzy control algorithm is presented for ship steering autopilot, which is an uncertain nonlinear system. In the proposed algorithm, fuzzy logic systems have been used to approximate lumped unknown function in the ship steering systems and the adaptive mechanism with minimal learning parameter, i.e. only one parameter, has been achieved by use of Lyapunov approach. The proposed methodology is verified using the simulation mode of the Dalian Maritime University's ocean-going training ship named Yulong. It is shown that the proposed algorithm guarantees that the ship steering autopilot system is asymptotically stable and its tracking error can approach to zero.

Feedback linearization design of a ship steering autopilot with saturating and slew rate limiting actuator

A full non-linear model including sea-state modelling is used in the design for a ship steering autopilot. This has been done before. However, rather than a conservative design to avoid amplitude and slew rate limit in the rudder, we show how these limits can be accommodated without otherwise compromising the performance. Thus, saturation and slew rate limiting are accepted as inevitable consequence of high performance rather than something to be avoided at all cost. Copyright © 1999 John Wiley & Sons, Ltd.

Adaptive Ship Steering Autopilot Design with Saturating and Slew Rate Limiting Actuator

The proposed adaptive ship steering autopilot is based on the internal model control method, which is characterized by a model-based design approach that provides clear connections between the structure of the controller and that of the ship model. Specifically, the controller parameters depends explicitly on the ship model parameters and on a design parameter that specifies the closed-loop system response speed. Once the ship model parameters are estimated on-line, the controller parameters are adjusted accordingly to adapt to different operating conditions. A key feature of the proposed approach being that the rudder limit and rudder rate limit are directly taken into the adaptation design consideration. Specifically, a reference conditioning technique that modifies the reference input in such a way that the rudder command is always equal to the actual rudder input into the plant. This allows the controller to exert its full power without attempting to take on values beyond the bounds imposed by the rudder limit and rudder rate limit. Consequently, under different operating conditions, rapid course-changing maneuvers are achievable without introducing possible instability problem caused by the controller integrator wind-up.

Nonlinear interaction of DC cables and magnetically controlled ship-steering autopilots

This paper presents new results on the interaction of DC cables and magnetically controlled ship-steering autopilots. Simulations with a nonlinear model show that a ship using a steering autopilot with a magnetic compass can be captured by a DC cable. That is, the ship tracks the cable, perhaps in an oscillatory fashion. A full-scale experimental study has been performed at the Kontiskan high voltage direct current link to verify calculations and simulation results. Good agreement was obtained between measurements and computer simulations. This paper presents the simulation study, the dynamic model used, and the test results. Simulation and field test show that if the ship is captured by the cable, it can, under certain conditions, track the cable with limit-cycle oscillation. Steady-state stability analysis explains why the ship does not find a stable capture course. Describing function analysis is used to find the limit-cycle amplitude and frequency.

A Preview Steering Autopilot Control Algorithm for Four-Wheel-Steering Passenger Vehicles

This paper addresses the control law design of a preview steering autopilot for a four-wheel-steering vehicle to perform automatic lane tracking. In the concept, an on-board computer vision system is used in lieu of the driver’s vision to track the roadway. The steering autopilot design is formulated as an optimal, discrete-time preview path tracking problem under the “perfect measurement” assumption. Simulation results indicate that the tracking performance of the steering autopilot was improved by preview relative to that calculated for an autopilot without preview. These results also indicate the existence of an effective preview time with which almost all the benefits of previewing future information can be obtained. This effective preview time is about three times the reciprocal of the autopilot’s bandwidth. Our study also indicates that preview steering autopilots can tolerate the use of actuators with a lower bandwidth than those designed without preview information.

Adaptive Controller to Minimize Ship Steering Propulsion Losses: Time Series Modeling and Statistical Analysis Results

Abstract Statistical time-series and multivariable regression analysis techniques are employed to investigate the properties of a multivariable model for ship/steering and seaway disturbance dynamics. Confidence intervals for the model parameter values to be identified by least-squares in an adaptive steering autopilot scheme are calculated. Residual analysis techniques are used to verify the validity of models via data from ship/steering/seaway simulations. The sufficiency of a firstorder multivariable time-series model within a self-tuning adaptive control algorithm framework is shown to be justified by the results obtained.