DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM

Adaptive backstepping controller is designed for tracking purpose of nonlinear system with unknown parameter is injected to it. Gravitational search algorithm (GSA) is integrated with the designed controller in order to automatically tune its control parameters and adaptation gain since the tracking performance of the controller relies on these parameters. Performance evaluation is observed based on the tracking output and the tracking error between reference input and the system’s output. The effectiveness of the adaptive backstepping controller is verified by looking at the lowest amount value of Sum of Squared Error (SSE) attained from the simulation process. The results show that the system’s output follow the reference input given with remarkably small tracking error

MODEL REFERENCE ADAPTIVE CONTROL-BASED GENETIC ALGORITHM DESIGN FOR HEADING SHIP MOTION

In this paper, the heading control of a large ship is enhanced with a specific end goal, to check the unwanted impact of the waves on the actuator framework. The Nomoto model is investigated to describe the ship’s guiding progression. First and second order models are considered here. The viability of the models is examined based on the principal properties of the Nomoto model. Different controllers are proposed, these are Proportional Integral Derivative (PID), Linear Quadratic Regulator (LQR) and Model Reference Adaptive Control Genetic optimization Algorithm (MRAC-GA) for a ship heading control. The results show that the MRAC-GA controller provides the best results to satisfy the design requirements. The Matlab/Simulink tool is utilized to demonstrate the proposed arrangement in the control loop

Ant Colony Optimization Algorithm Applied to Ship Steering Control

AbstractThe article describes the application of an ant algorithm to optimize parameters of the ship course controller, based on the algorithm of PID control. The ant algorithm is a method of combinatorial optimization, which utilizes the pattern of ants search for the shortest path from the nest to the place where the food is located. The procedure of parameter tuning for the ship course controller was applied to the case when the controller was changing the course of the ship and the integral action was turned off. Tuned parameters of the ship course controller are evaluated by the ant colony algorithm, which makes use of the course error based objective function and a given rudder deflection. The results were compared with equivalent results obtained using a genetic algorithm. Moreover, the effectiveness of PID controller parameter tuning was assessed using the ant colony optimization algorithm

Iterated Nonlinear Control of Ship's Manoeuvring Models

This paper addresses the control design for a nonlinear vessel manoeuvring model. The authors consider a highly nonlinear vessel 4 DOF model. The proposed control algorithm consists of a combination of an iteration technique that approximates the original nonlinear model by a sequence of linear time varying (LTV) equations whose solution converge to the solution of the original nonlinear problem and, a lead compensation design in which for each of the iterated linear time varying systems, the controller is optimized at each time on the interval. The control designed for the last iteration is then applied to the original nonlinear problem. Simulations results show good performance of this approximation methodology and accurate tracking for certain manoeuvring cases under the control of the designed lead controller. The main characteristic of the nonlinear system's response are the reduction of the settling time and the elimination of the steady state error and overshoot

Automatic Control and Routing of Marine Vessels

Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

Nonlinear steering control under input magnitude and rate constraints with exponential convergence

A ship steering control is designed for a nonlinear maneuvering model whose rudder manipulation is constrained in both magnitude and rate. In our method, the tracking problem of the target heading angle with input constraints is converted into the tracking problem for a strict-feedback system without any input constraints. To derive this system, hyperbolic tangent ($\tanh$) function and auxiliary variables are introduced to deal with the input constraints. Furthermore, using the feature of the derivative of $\tanh$ function, auxiliary systems are successfully derived in the strict-feedback form. The backstepping method is utilized to construct the feedback control law for the resulting cascade system. The proposed steering control is verified in numerical experiments, and the result shows that the tracking of the target heading angle is successful using the proposed control law.Comment: 12 pages, 6 figures, a preprint submitted to the Journal of Marine Science and Technolog

Iterative Self-Tuning Minimum Variance Control of a Nonlinear Autonomous Underwater Vehicle Maneuvering Model

This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control. This work makes use of self-tuning minimum variance principles. The benefit of this approach is that the nonlinearities and couplings of the system are preserved, unlike in the cases of control design based on linearized systems, reducing in this manner the uncertainty in the model and increasing the robustness of the controller. The simulations here presented use a torpedo-shaped underwater vehicle model and show the good performance of the controller and accurate tracking for certain maneuvering cases

Iterative lead compensation control of nonlinear marine vessels manoeuvring models

This paper addresses the problem of control design and implementation for a nonlinear marine vessel manoeuvring model. The authors consider a highly nonlinear vessel 4 DOF model as the basis of this work. The control algorithm here proposed consists of a combination of two methodologies: (i) an iteration technique that approximates the original nonlinear model by a sequence of linear time varying equations whose solution converge to the solution of the original nonlinear problem and (ii) a lead compensation design in which for each of the iterated linear time varying system generated, the controller is optimized at each time on the interval for better tracking performance. The control designed for the last iteration is then applied to the original nonlinear problem. Simulations and results here presented show a good performance of the approximation methodology and also an accurate tracking for certain manoeuvring cases under the control of the designed lead controller. The main characteristic of the nonlinear system's response is the reduction of the settling time and the elimination of the steady state error and overshoot

Integrated Computing, Communication, and Distributed Control of Deregulated Electric Power Systems

Restructuring of the electricity market has affected all aspects of the power industry from generation to transmission, distribution, and consumption. Transmission circuits, in particular, are stressed often exceeding their stability limits because of the difficulty in building new transmission lines due to environmental concerns and financial risk. Deregulation has resulted in the need for tighter control strategies to maintain reliability even in the event of considerable structural changes, such as loss of a large generating unit or a transmission line, and changes in loading conditions due to the continuously varying power consumption. Our research efforts under the DOE EPSCoR Grant focused on Integrated Computing, Communication and Distributed Control of Deregulated Electric Power Systems. This research is applicable to operating and controlling modern electric energy systems. The controls developed by APERC provide for a more efficient, economical, reliable, and secure operation of these systems. Under this program, we developed distributed control algorithms suitable for large-scale geographically dispersed power systems and also economic tools to evaluate their effectiveness and impact on power markets. Progress was made in the development of distributed intelligent control agents for reliable and automated operation of integrated electric power systems. The methodologies employed combine information technology, control and communication, agent technology, and power systems engineering in the development of intelligent control agents for reliable and automated operation of integrated electric power systems. In the event of scheduled load changes or unforeseen disturbances, the power system is expected to minimize the effects and costs of disturbances and to maintain critical infrastructure operational