Anti-Tank Guided Missile Performance Enhancement Part-2: Robust Controller Design

The performance of antitank guided missile systems is measured through the minimum missdistance and its capability to overcome target maneuver and different sources of errors including disturbances and noises. Toward these performance constraints, the guidance and control is considered, which is one of the most interesting and challenging problem areas for antitank missile. Therefore, this paper considers an antitank guided missile system belonging to the first generation for the design and analysis. The design and analysis necessitates somehow accurate model (objective of Part-1 of the paper) for the system and a robust control design philosophy (objective of Part-2 of the paper). Transfer functions representing the missile-control system dynamics in pitch and yaw planes are identified via hardware in the loop (HWIL) simulation and considered for investigation and validation against previous work and reference flight data. These transfer functions are obtained and justified in Part-1 of the paper and consequently this part is devoted to design a robust controller and implements it within the 6DOF simulation. The jetvator control loop for both pitch and yaw channels of the intended guided missile system with compensation network are designed using ∞ H and investigated such that the system is stabilized and the performance requirements are satisfied with disturbance rejection and measurement noise attenuation. To stay on the robustness of these controllers and their ability to withstand against disturbances, the measurements are corrupted with noise and the system performance is investigated. The obtained results showed superior features of ∞ H in stabilizing the system with only one controller allover the flight envelope and withstand some of the uncertainty sources. Keyword: Guidance and Control, Hardware-in-Loop Simulation, System Identification, Robust Control. 1Introduction The ever-increasing development of tanks capabilities necessitates the design of accurate control and guidance system for an antitank missile in presence of disturbance, measurement noise, and un-modelled dynamics. To achieve this objective, an adequate nonlinear mathematical model representing the dynamical behaviour of the underlying missile was obtained for different flight phases. However, mathematical model cannot precisely represent a real physical system and there is always uncertainty. This uncertainty is due to unknown or unpredictable inputs (disturbance, noise, etc.) and unpredictable dynamics [11]. To overcome 1 Prof. In Electronics and Electrical Communication Department, MSA University, Cairo, Egypt 2 Graduate Student in Guidance and Radar Department, MTC, Cairo, Egypt 3 Asc. Prof. In Electronics and Electrical Communication Department, MUST, 6 October, Cairo, Egypt Proceedings of the 5 ICEENG Conference, 16-18 May, 2006 GC 10 ٢ the different sources of uncertainty, robust control is used to design the autopilot such that the system is stable with the ability to reject the disturbances and minimize the effects of the measurement noises. The performance specifications include the overshoot, speed of response, steady state error and system stability which are the main objectives to the designer. The main problem for designing classical controllers involves the judicious choice of pole (s) and zero (s) to alter the root locus or frequency response of the uncompensated system so that the required performance specifications are satisfied. Meeting these objectives with guided missiles through classical controllers is usually difficult especially these applications are time varying stochastic. Missile flight control systems must guarantee stability and performance in the face of large modelling uncertainties and noise. This requires the feedback controller to maintain system stability and loop performance for the overall flight envelope. Therefore, it is necessary to design a control system that performs adequately over a range of plant parameters. This control system is said to be robust when it maintains a satisfactory level of stability and performance over a range of plant parameters and disturbances [3, 4]. Thus, the objective is to investigate the robustness of the designed autopilot against uncertainties due to modelling and noise. Therefore, the controller, to be designed and implemented within the missile control system, should be insensitive to model uncertainties and be able to suppress disturbances and noise over the whole envelope of operation, i.e. should be robust. This paper is devoted to design the jetevator control using the H ∞ in state space form and its applications on guidance and control performance analysis. A feedback-control system must satisfy certain performance specifications, and it must tolerate model uncertainties. The most elementary feedback control system has three components: the plant, sensors to measure the outputs of the plant, and a controller to generate the plant's input [4, 10], Fig. 1. r(t) is the command (or reference) input that the system must follow or track. d(t) the disturbance input that must be rejected by the system. Disturbances represent actual physical disturbances acting on the system such as wind gusts, disturbances owing to actuators, or uncertainties resulting from modelling errors in plant or actuator. n(t) is the measurement noise introduced into the system via sensors, and it is usually considered to be random high-frequency signals. y(t) the plant output signal that should track the input command in presence of the disturbance d, sensor noise n and un-modelled dynamics. u(t) actuating signal that should be varying smoothly toward zero effort. e(t) is the tracking error that should be zero, spatially at steady state. The contribution of system inputs to the actual output y(t), the tracking error ) (t e , and the controller/actuator output signal, u(t), is described by the sensitivity function (S), the complementary sensitivity function (T) and the control sensitivity function (M) [1, 2, 3, 13]. From these relationships it can be clarified that: Controller Co Sensor Cf Pla nt P ) (t r ) (t e ) (t u