عنوان مقاله [English]
Abstract - In the past, the field of missile guidance and control system design has been dominated by classical control techniques. Typically these techniques are either time domain or frequency domain based, are applicable to linearized and time-invariant plants. Nonlinearities and time-varying effects must be coped with by a robustness margin of the control loop. The performance of the loop is hence not constant but will change with the operating point. When the time variation and nonlinearities are severe, it may not be an easy task to find a controller that can cope with it all. In recent years, we have seen a growing interest in applications of robust, nonlinear, adaptive and intelligent control theories to missile flight guidance and control systems. The main
advantage of intelligent over classical control is that the former can provide robust systems when there are model and environmental uncertainties. Fuzzy logic, by giving control laws based on input-output relationships, avoids the need for accurate knowledge of system dynamics, and is thus insensitive to their changes. In simple systems the classical controller may be preferred while systems with more complex requirements and capabilities, the increased abilities of the fuzzy controller may be useful. In such a system, it is frequently advantageous to use hybrid intelligent systems. The resulting control system can incorporate many desirable qualities, such as robustness, ease of adaptability to new tasks, and is faster to produce than traditional methods that are heavily model dependent. Another feature of intelligent systems is that they could combine knowledge, techniques, and methodologies from various sources. These intelligent systems supposed adapt themselves and learn to enhance the performance in changing environments. In this paper, an adaptive control structure based on fuzzy logic theory is presented. In this structure the control objective is track the command of Euler angles. In the
aforementioned control system, fuzzy controllers knowledge-base, rule base are updated with continuous adjustment of membership function and weight of fuzzy controller though online learning. In this approach, fuzzy systems are used to approximate unknown ideal controllers. The adjustable parameters of the fuzzy
systems are updated by an adaptive law based on a Lyapunov approach, i.e., the parameter adaptive laws are designed in such a way to ensure the convergence of a Lyapunov function. Finally the Simulation results for an air to ground short range missile with uncertain aerodynamic coefficients are presented to proof the proposed control law.