Solid State Phenomena Vol. 210

Abstract: The article presents the discussion focused on specific features of the problem of flying objects motion when performing an example of anti collision manoeuvre. To realise this task, the structure of automatic control system with appropriate control laws are proposed. The nature of discussed manoeuvre needs the appropriate numerical method for computing desired values of state variables for subsequent phases of objects motion. These values are obtained adequately for their roles in several phases of motion. Numerical simulations are completed for the aircraft performing the anti collision manoeuvre consisted in abrupt change of yaw. Objects behaviour was tested in case of motion affected by disturbances. The analysis of results obtained by numerical simulations makes possible conclusions on stability of objects motion and control system robustness to assumed kind and level of disturbances.

Abstract: In this paper a comparison of single and multi-population evolutionary algorithm is presented. Tested algorithms are used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of single-population and multi-population evolutionary algorithm is described. Using presented algorithms the simulations on three close to real sea environments were performed. Regardless of the test situation constant time simulation was maintained. Obtained results are presented in graphical form (sequences of successive stages of the simulation) and in form of table in which the values of fitness function for best individual in each simulation were compared. Undertaken research allow to select evolutionary algorithm that, assuming constant simulation time, will determine a better path in close to real collision avoidance situation at sea.

Abstract: This article presents an application of the hybrid position-force control of the robotic manipulator with use of artificial neural networks and fuzzy logic systems in complex control system. The mathematical description of the manipulator and a closed-loop system are presented. In the position control were used the PD controller and artificial neural networks, which compensate nonlinearities of the manipulator. The paper presents mainly the application of various strategies of the force control. The force control strategies using conventional controllers P, PI, PD, PID and fuzzy controllers are presented and discussed. All of the control methods were verified on the real object in order to make a comparison of a control quality.

Abstract: This article presents a hybrid expert system which consists of a symbolic expert system and a genetic algorithm being connected to it. When a fault location diagnosis is not correct or the symbolic expert system is not able to locate a fault due to the lack of knowledge, the user may use the knowledge of the genetic algorithm. A MOS transistors were chosen as the object of diagnosing for the purpose of testing of the hybrid expert system.

Abstract: The article presents an application of the neural hybrid position/force control of the robotic manipulator. Realisation of many machining processes requires an application of the hybrid position/force control in order to perform the desired robot trajectory, which results from the machined surface geometry, and the desired tool downforce. The application of the robotic manipulator for realisation of the machining process enables to elimination of human handwork and ensures greater accuracy and repeatability of products. In the article is presented mainly the application of the hybrid position/force control system, in which a multilayer neural network is applied in order to manipulator nonlinearities compensation.

Abstract: Electrical energy production from renewable energy sources is currently one of the key directions of conducted research. This paper describes a developed laboratory control system for the operation of a dual-fuel compression ignition engine in which the main fuel charge is fed in the form of biogas with variable composition, it also describes a system enabling the measurement of waste heat from this engine.

Abstract: This paper presents a new approach to the control problem of the ball and beam system, with a Neuro-Dynamic Programming algorithm implemented as the main part of the control system. The controlled system is included in the group of underactuated systems, which are nonlinear dynamical objects with the number of control signals smaller than the number of degrees of freedom. This results in problems in the formulation of a stable control algorithm, that guarantees stabilization of the ball in the desired position on the beam. The type of ball and beam material has a noticeable influence on the difficulties in stabilization of the ball, because of a smaller rolling friction and big inertia of the used metallic ball in comparison to other, for example made of non-metallic materials. The main part of the proposed discrete control system is the Neuro-Dynamic Programming algorithm in a Dual-Heuristic Dynamic Programming configuration, realized in a form of two neural networks: the actor and the critic. Neuro-Dynamic Programming algorithms use the Reinforcement Learning idea for adaptation of artificial neural network weights. Additional elements of the control system are the PD controller and the supervisory term, that ensures stability of the closed system loop. The control algorithm works on-line and does not require a preliminary learning phase of the neural network weights. Performance of the control algorithm was verified using the physical system controlled by the dSpace digital signal processing board.

Abstract: This paper analyses optimization methods and game theory to support decision making by a navigator when controlling a vessel in various real navigational situations at sea. We have demonstrated the structure of a computer system for supporting manoeuvring decisions by a navigator. Navigational situations of an optimal and game ship control have been classified. We have also described game algorithms for supporting decision-making in a form of non-cooperative and cooperative positional and matrix games, respectively. The considerations have been illustrated with a computer simulation, using the Matlab/Simulink software, of algorithms for determining safe trajectories of a vessel in a real navigational situation at sea.

Abstract: When designing a control system for a ship gun, the problem is to predict orientation of the ship in an assumed reference frame. This problem can be solved with different regression tools out of which one are neural networks. To verify their abilities to predict spatial orientation of a ship, experiments were carried out. In the experiments, the task of neural networks was to predict the roll angle which changed according to seven model sinusoid functions with different parameters and higher harmonic components.

Abstract: Nowadays Integrated Bridge Systems are applied on board a ship to increase safety of navigation. These systems consist of many electronic devices such as radar, ECDIS and autopilot, which aid the deck officer in the process of conducting navigation. Despite that, ship accidents caused by human error still occur. The paper presents new method of safe ship control in collision situations. Ant Colony Optimization is applied to determine safe ship trajectory. Developed algorithm is applicable for situations in restricted waters, where most of collision situations occur. International Regulations for Preventing Collisions at Sea (COLREGs) are taken into consideration in the process of solution construction. The task of collision avoidance at sea is defined as dynamic optimization problem with the use of static and dynamic constraints. Static constraints are represented by lands, canals, shallows, fairways, while other ships constitute dynamic constraints. Described method was implemented in MATLAB programming language. Performed simulation tests results of encounter situations with one target ship as well as with many target vessels are presented. Received solutions confirm successful application of this method to the problem of ships collisions avoidance. Developed algorithm deals also with more complex situations. This new algorithm is planned to be implemented in anti-collision decision support system on board a ship, what would contribute to enhance safety of maritime transport.