Linear Quadratic Tracking Design for a Generic Transport Aircraft with Structural Load Constraints

When designing control laws for systems with constraints on the tracking performance, control allocation methods can be utilized. Control allocation methods are used when there are more command inputs than controlled variables. Control allocators can be used to address surface saturation limits, structural load limits, drag reduction constraints, or actuator failures. Most transport aircraft have many actuated surfaces compared to the three control variables (such as angle of attack, roll rate, and angle of sideslip). To distribute the control effort among the redundant set of actuators, a fixed mixer approach or online control allocation techniques can be utilized. The benefit of an online allocator is that complex constraints can be considered in the design; however, an online control allocator has the disadvantage of not guaranteeing a surface schedule, which can then produce unacceptable loads on the aircraft. The load uncertainty and complexity has prevented some controller designs from using advanced online allocation techniques. This paper considers actuator redundancy management for a class of over-actuated systems with real-time structural load limits using linear quadratic tracking applied to the generic transport model (a twin-engine heavy civil transport aircraft). With the inclusion of static load constraints in the allocator, the concern of overstressing the structures should be minimized or even eliminated. The results include three test cases. The first test case shows what happens when load constraints are applied over six left- and right-wing locations, with comparison to the same roll input run without load constraints. Test case two shows what happens when a large commanded roll is executed with the same load constraints as those used in test case one; this run is intended to stress the loads allocator. Test case three shows the robustness of the linear quadratic augmented allocator system to uncertainties; a 35-percent change in the control effectiveness plant model will be shown, in which the controller is kept the same as in test cases one and two with six load constraints.