auto pilot ship heading angle control using adaptive...

© The 2017 International Conference on Artificial Life and Robotics (ICAROB 2017), Jan. 19-22, Seagaia Convention Center, Miyazaki, Japan

Auto Pilot Ship Heading Angle Control Using Adaptive Control Algorithm

Abadal-Salam T. Hussaina,b aCenter of Excellence for Unmanned Aerial Systems (CoEUAS)

Universiti Malaysia Perlis, 01000 Kangar, Perlis, Malaysia.

Hazry D.a, S. Faiz Ahmeda, Wail A. A. Alwardb, Zuradzman M. Razlana & Taha A. Tahab aCentre of Excellence for Unmanned Aerial Systems (CoEUAS)

bCenter of Excellence for Renewable Energy (CERE) Universiti Malaysia Perlis, 01000 Kangar, Perlis, Malaysia.

E-mail: [email protected], [email protected] www.unimap.edu.my

Abstract

In this paper discussed about development of an auto pilot system for ships using adaptive filter. Adaptive filter in the application of auto pilots for ships is presented for controlling the ship such that it follows its predetermined trajectory. Due to random environmental effects such as wind speed or direction and sea current, the path of the ship may alter. The objective of this research is to investigate that whether proposed system will adapts to the random changes and maintain the desired ship trajectory. The proposed auto pilot system is developed using Least Mean Square algorithm (LMS) adaptive filter. The performances of the system are analyzed based on accuracy and computational times. MATLAB Simulink model tool is used for execute the simulations of the auto pilot system for ships.

Keywords: Autonomous Controls, Ship Heading Angle, Adaptive Controls

1. Introduction

The history of ships, boats and sailing is spread over centuries. Ship steering control has been an essential topic for researchers for more than 95 years. Early steering control systems were based on an instrument called gyroscope, which was used to determine the direction of travel. In 1911, Elmer Sperry invented an automatic mechanism for ship steering control based on the gyroscope (Sperry, 1992).

In 1922, Minorsky published his work on automatic ship steering, which was an essential breakthrough in the field (Minsky, 1954). Later in the same year, Sperry presented the first automatic ship control system. These

early autopilot for ships were entirely mechanical in nature and had a very simple process, wherein the rudder was proportional to the heading error.

Major disadvantage s of traditional controllers such as PID and PD are their inability to adjust with alterations automatically in the environmental and operating conditions. These settings had to be adjusted manually by the user which in many cases may not be completely optimal. Moreover, these obligatory setting which had to be done repeatedly were exhausting and time consuming.

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Abadal-Salam T. Hussain, S. Faiz Ahmed, Hazry D., Wail A. A. Alward, Zuradzman M. Razlan & Taha A. Taha


1.1 Steering Control Overview

Fig. 1 shows a general block diagram of a ship steering control system made up of reference model, sensor system and feedback control system. The reference model receives the data on the position and speed of the ship from the DGPS (Differential Global Position System) and also receives external data provided by an operator (Deck Officer) and other data concerning the environmental conditions (height and slope of the waves and speed and direction of the wind and currents). The control system also receives information that supplied by the measurement system and determines the forces and moments which are to be supplied to the ship in accordance with the established control objective in most cases together with the reference model system. In this thesis, we will be focusing only on the course keeping characteristics of the auto pilot controller.

Fig. 1. Steering control

2. Modeling

2.1. Adaptive Controllers in Auto Pilot Ship System

Autopilot is one of the most important section used in ships. Autopilots are not just used to lead the ship on a desired trajectory, but also raise the safety level of the journey and control the ship economically. A good autopilot can help to avoid undesired situations on maneuvering and remarkably reduce the numbers of ship operators. In the last few decades, taking the advantage of drastic development of electronics and control theory, several new and effective methods have been proposed

and developed for designing ship-autopilots (Barbos, 2008), (M. Kamran Joyo, 2014), ( Hussain, 2011).

2.2. Adaptive Filter

Fig. 2 represents the general block diagram of any adaptive filter. In this application i.e. the ship steering auto-pilot is designed using an adaptive filter and completely replacing the traditional controllers.

Fig. 2. Adaptive filter

2.3 Least Mean Square (LMS)

The LMS algorithm was established by Widrow and Hoff in 1959. Compared to other algorithms, LMS algorithm is relatively simple; it does not require correlation function calculation nor does it require matrix inversions. This algorithm is basically the type of adaptive filter known as stochastic gradient-based algorithms and it consists of two major processes: Filtering process and adaptive process (A.T. Hussain, 2015). LMS algorithm worked on steepest decent method and also took help from the theory of Wiener solution (optimal filter tap weights). This algorithm is basically using the formulas which updates the filter coefficients by using the tap weight vectors w and also update the gradient of the cost function accordingly to the filter tap weight coefficient vector

)(n . )()()1( nnwnw

w(n+1) = w(n)+mE e(n)x*(n){ } (1)

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Auto Pilot Ship Heading


In practice, the value of the expectation E { } is normally unknown, therefore we need to introduces the approximation or estimated as the sample mean.

1

0

** )()(1)()(L

llnxlne

LnxneE

(2)

With this estimate we obtain the updating weight vector as,

1

0

* )()()()1(L

llnxlne

Lnwnw

(3)

And finally, the weight vector update equation become the simple form. w(n+1) = w(n)+me(n)x*(n) (4)

2.4. Ship Dynamics & Model

In this research, Norrbin Model of the ship is considered. This model is extension of the Nomoto's first-order model (Syed Faiz Ahmed, 2014) in an empirical way. To describe large rudder angles as well as course instability, the following model is proposed:

(5)

Where a1 = +1 for course-stable and 11 for course-unstable ships. Of course, this model can also be extended with a constant and a quadratic term. This

yield, in the steady state, when 0

012

23

3)(NH (6

)

With Eq. 5 and Eq. 6 can be rewritten as:

KHT N )()(

(7)

2.5 Ships Use for Simulation Purposes

For simulation purpose ROV Zeefakkel ship (ferry) is taken in account which is 45m ferry. The ship model of the ferry can be formed using table 1. The desired heading response is represented by the third order model of Eq 8 with am= 0.9341, bm= 0.2040 and cm= 0.0182. The maximum rudder limit selected is and the maximum rudder rate is.

mmm

m

r

d

csbsasc

23 (8)

Where am, bm and cmare constants. Van Amerongen demonstrates that the motion of this ship can be described adequately by the Norrbin’s nonlinear model with the following parameter values: When the speed of the ship changes, the values of K and T also vary as found out by Van Amerongen and illustrated in the table below:

3. Results

ROV Zeefakkel performance of LMS Adaptive Controller with Reference heading angle: 20° & 50°, Constant speed: 5m/s, Step Size = Optimal (1x10-5for LMS ) and Filter Length : Larger than the optimal value and Smaller than the optimal value.

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Abadal-Salam T. Hussain, S. Faiz Ahmed, Hazry D., Wail A. A. Alward, Zuradzman M. Razlan & Taha A. Taha


U(m/s) T K 1 155.0000 0.1 2 077.5000 0.2 3 051.6667 0.3 4 038.7500 0.4 5 031.0000 0.5 6 025.8333 0.6 7 022.1429 0.7 8 019.3750 0.8

9 017.2222 0.9 10 015.5000 1.0

Fig.4. LMS 50° at 5m/s, µ =1x10-6, step size = 40

4. Conclusions

The LMS filter gives very good results in terms of achieving the heading angle that is desired for both 20° and 50°. It is ascertained from the simulation results that

the performance of LMS algorithm is better to minimize Mean Square Error (MSE) for different heading degree angles to maintain the desired trajectory using the performance function of the algorithm that minimized the average power in the error signal. As the degree of heading angle was switched from 20° to 50°, we can observe that the filter length and step size µ has to be changed to get an optimum performance from the controller. References 1. Sperry, E. A. (1922). Automatic steering. Transactions,

Society of Naval, Architects and Marine Engineers, 61–63;

2. Minsky, M. L., 1954. Theory of Neural-Analog Reinforcement Systems and Its Application to the Brain Model Problem, PhD Thesis, Princeton, University, Princeton, NJ;

3. Barbos, M. ; Cristescu, C. , Technical Overview on Designing Wireless Remote Control Steering Mechanisms for Small Ships and Scaled Model Ships, IEEE International Conference on Automation, Quality and Testing, Robotics, 2008 Vol. 3, pp. 287 – 291;

4. M. Kamran Joyo, D. Hazry, S. Faiz Ahmed, M. Hassan Tanveer, Faizan. A. Warsi, A. T. Hussain, “Altitude and Horizontal Motion Control of Quadrotor UAV in the presence of Air Turbulence”, Systems, Process & Control (ICSPC2), 2013 IEEE International Conference, Published at IEEE Xplore, PP (16-20), ISBN: 978-1-4799-2208-6, (2013) ;

5. Hussain, A.T., et al.; “Real-Time Robot-Human Interaction by Tracking Hand Movement & Orientation Based on Morphology”, International Conference on Signal and Image Processing Applications (ICSIPA 2011), Published at IEEE Xplore, PP (283-288), ISBN: 978-1-4577-0243-3, (Feb. 2012) ;

6. A.T. Hussain, S. Faiz Ahmed & D. Hazry; "Tracking and Replication of Hand Movements by Teleguided Intelligent Manipulator Robot", Robotica, Cambridge University Press, Vol. 33, Issue 01, Jan. 2015, pp 141-156. DOI: http://dx.doi.org/10.1017/S0263574714000083 (ISSN: 0263-5747 EISSN: 1469-8668) ;

7. Syed Faiz Ahmed, Ch. Fahad Azim, Hazry Desa, Abadal-Salam T. Hussain, "Model Predictive Controller-based, Single Phase Pulse Width Modulation (PWM) Inverter for UPS Systems", Acta Polytechnica Hungarica, Journal of applied science (ISSN 1785-8860), Volume 11, Issue Number 6, pp. 23-38, (2014).

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auto pilot ship heading angle control using adaptive...

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