Application of neural networks for synthesizing flight control algorithms. I neural network inverse dynamics method for aircraft flight control

Abstract

The application of artificial neural networks for aircraft motion control, in particular, for creation of nonlinear algorithms of the aircraft remote control system (RCS) is considered. Aircraft as a control object is represented as a multidimensional nonlinear dynamic system and nonlinear control methods are used to operate this system. The control loop is constructed using the method of inverse dynamics based on the feedback linearization principle. The nonlinear control law is represented as a neural network being learned (adjusted) by recorded or incoming measurements of motion parameters. Synthesis and testing of neural network control algorithms is performed with the fully nonlinear mathematical model of a maneuverable aircraft for three control channels. Simulation results of the closed system are presented.In this paper, we solve the problem of obtaining desired aircraft controllability characteristics by means of automation. The problem being solved by algorithmic methods consists of the high-precision control throughout the flight envelope, including the predominance of nonlinear object characteristics. A classic way of eliminating nonlinearity is an increase of gain factors in the control loop, which linearizes the control object to some extent. However, the possibilities of this approach are limited by stability of the closed system.Another way is to use nonlinear control methods. Linearization of output feedback (the basis of the inverse dynamics method) has become a generally accepted technique for constructing the control loop for nonlinear dynamic systems. Furthermore, the aim is to use the measurements of flight parameters, that is to "automate" acquisition of the nonlinear control law.The artificial neural networks are used to solve this problem that is due to their two properties, namely, first, neural networks have a property of universal approximation and, therefore, they can approximately implement a wide class of nonlinear functions; second, they are nonlinear statistical models and they are adjusted (trained) by incoming or recorded measurement signals. Thus, from the practical point of view, neural networks are of interest as universal models of nonlinear regression. In this paper, the controlling neural network implements the nonlinear control law being used in the main loop.Synthesis and testing of neural network control algorithms is performed on the fully nonlinear mathematical model of a maneuverable aircraft through three control channels for the current flight conditions. Control actuators are presented by oscillating elements with a frequency of 20 rad/s and restrictions on speed and position. Due to specific character of the configuration methods of the neural network control law, an internal loop of angular velocity control is distinguished in the structure of the system. This loop is built by the inverse dynamics method, and an external angle of attack control loop includes the PI controller.

Comparative Study of Different Algorithms for a Flight Control System Design and the Potentiality of Their Integration with a Sidestick

“…The same two-loop approach is used in [10], where the inner loop uses the inverse dynamics technique to linearize the nonlinear plant, and the outer loop uses an H∞-based controller to provide robustness. Flight controllers based on inverse dynamics principles can also be designed using machine learning principles as in [11], where inverse dynamics is approximated using a nonlinear regression neural network and used in the same fashion as feedback linearization to allow the application of a PI controller.…”

Research on the Application of Computer Network Remote Control System

“…If the computer network using HTTP protocol, so it should be selected to carry out centralized mode of computer network management, control and so on, because this type of configuration will effectively enhance the efficiency of the system, and has good coordination performance and flexible performance, which can promote the development of computer hardware and software resources supervision work carried out smoothly. [2] The advantage of the application of computer network remote control system is not only conducive to the smooth development of computer management, but also to enhance the level of enlightened computer services. Due to the coming of the network era, the maturity and development of computer network technology are becoming more and more important.…”