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The quad tilt rotor (QTR) has complex dynamics characteristics, and the environmental factors have a great influence on it. This increases the difficulty of its control especially in transition mode. To solve this problem, the design of the controller based on active disturbance rejection control (ADRC) with a novel tuning algorithm is proposed in this paper. The aerodynamic models of propeller, wing, vertical tail and fuselage are build respectively by using the idea of component modeling. The pitch channel of the linearized flight dynamic model is provided for the control system. A simple tuning method of active disturbance rejection control for the quad tilt rotor in transition process that achieves high performance and good robustness is presented. The proposed method makes ADRC become easy to tune and more practical. The problem of parameter tuning is turned into a multi-objective optimization problem, and using radial basis function(RBF) neural network with particle swarm optimization algorithm(PSO) and bacterial foraging optimization algorithm(BFO) hybrid algorithm tuning method(NBPO) to fit the tuning rules. We introduce the control input, the overshoot and rise time of the system into the fitness function. The local and global optimal solutions are introduced into the chemotaxis and migration to improve the information exchange ability of BFO. The correctness and effectiveness of the NBPO tuning method were verified by numerical simulation results, compared with the one parameter tuning method(OPM) and PID, the results showed that the NBPO tuning method can greatly improve the control performance of the system.

Tuning of ADRC for QTR in Transition Process Based on NBPO Hybrid Algorithm