No abstract

This paper introduces the implementation of intelligent motion control and planning for autonomous underwater vehicle (AUV). Previously developed control system features intelligent motion control and planning subsystem, based on artificial neural networks. It allows detecting and avoiding moving obstacles in front of the AUV. The motion control subsystem uses position-trajectory control method to position AUV, move from point to point and along given path with given speed. Control system was tested in the multi-module simulation complex. Simulation showed good results – AUV successfully achieved given goals avoiding collisions not only with static obstacles, but also with mobile ones. That allows using the proposed control system for the groups of vehicles. Besides simulation, control system was implemented in hardware. AUV prototype passed tests in Azov Sea and proved its efficiency.

In this paper we consider one of the problems in the development of control system for the feeder for MAAT transportation system. This problem is connected with estimation of inboard energy requirements. Traditionally such estimation is made on the basis of static relations. They allow assessing the power required to move a solid body with a constant air speed. However a contribution from aerodynamic forces and moments can vary depending on a regime of motion (value of linear and angular accelerations, angle of attack, etc). Because of that fact, this work investigates the estimation of the total required inboard energy and contribution of aerodynamic forces and moments to it in specified feeder motion regimes. The method of assessment is based on the feeder model, which is built on the equations of the rigid body. This paper contains general structure of feeder mathematical model, which includes equations of statics, dynamics and control mechanisms. The example of the exact feeder shape gives the application of this models with the details in terms of aerodynamic characteristics, inertial mass parameters and locations of control mechanisms. Feeder model is complemented by the external environment model, including the wind flow model. Development of the latter models is investigated in the talk ???Probabilistic Approaches to Estimation of Flight Environment for Feeder of Multibody Transport Airship System???, presented on this conference. Three main feeder motion regimes were chosen for the estimation of the required power. These three regimes are hovering in one point, motion along a straight line and motion along a specified circle. Steady motion is considered along with transient regimes, when the feeder is moving to the specified trajectories. The results allow assessing the required power for steady and transient regimes for each considered trajectory, different values of air speed, different locations of centre of gravity and different angles of attack. Additionally, study of Kalman controllability and Lyapunov stability was made for the special feeder motion regimes. The conclusions about the optimal feeder shape are given based on this work

No abstract

Abstract. The paper presents an automatic control system for autonomous airship. The system is designed to organize autonomous flight of the mini-airship performing flight mission defined from ground control station. Structure, hardware and software implementation of indoor autonomous airship and its navigation and control system as well as experiment results are described.