This paper presents a multi-objective optimal design of cascade controllers applied to an aircraft wing with a leading and trailing control surface driven by electromagnetic actuators (EMAs). The design of the control system is decoupled into an inner (slave or secondary) and outer (master or primary) control algorithm. The master control algorithm is applied to the dynamics of the wing and its ailerons while two salve control loops are designed for the two EMAs. Then, a multi-objective and optimal design of the control algorithms is carried out. Three objectives are considered : 1) the speed of response of the slave controlled system must be faster than that of the master one, 2) the controlled system must be robust against external upsets, and 3) optimal energy consumption. The multi-objective optimization problem (MOP) is solved by the non-dominated sorting genetic algorithm (NSGA-II), which is one of the widely algorithms in solving MOPs. The setup parameters of the primary and secondary control algorithms are tuned during the optimization and the design objectives are evaluated. The solution of the MOP is a set of optimal cascade controllers that represent the trade-offs among the design objectives. Computer simulations show that the design objectives are achieved. However, some of the optimal solutions are practically in-feasible because they respond poorly to external disturbances. Presented study may become the basis for multi-objective optimal design of active aeroelastic control systems.

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