Helicopter Neural Network Control And Implementation Of Handling Quality Requirements

Handling Quality is one of the principal design requirements in the up-to-date Aeronautical Design Standard (ADS).Helicopters have worse handling quality than the fixed-wing aircrafts because of their natural features, but the excellent quality is required by their missions. It is very difficult to implement high quality only depending upon the stucture design or aerodynamic configuration. It is the important development to adopt the flight control system (PCS) to improve handling quality, and control law design plays an important role in helicopter handling quality design.Currently, one of the hotspots in the research of helicopter flight control technology is to define performances of PCS based on handling quality standard, and to implement criteria requirements directly in PCS. Conventional technology of PCS design cannot meet the requirements for quality design.In order to provide a basic and effective practical engineering tool for handling quality planning, analysing and evaluating, which is needed hi helicopter prototype development, this research work is launched on the fundation of comprehending the newaeronautical standard of United States Army-ADS-33, and has obtained theachievements as following:(1) Performance definition of PCS according to the criteria requirements for an explicit helicopter, beginning at analysis of its missions.(2) Establishment of a helicopter attitude controller, which can meet the criteria requirements, by using the technology of adaptive neural network model-inverse control; Implementation of two response types (RTs) and two control modes; Evaluation of quantitative parameters according to the ADS-33.(3) Establishment of a helicopter trajectory contoller based on the attitude controller; Simulations of mission task elements (MTEs) and evaluation of handling quality.The following conclusions have been drawn from this research program,:(1) The model following architecture allows for straightforward implementation of requirements of handling quality standard, and it can be utilized for helicopter handling quality design.(2) The adaptive model-inverse control theory can provide the referenced helicopter with consistent handling quality throughout its operating envelope, with requiring only an approximate linear model at a single operating point.(3) The technology of adaptive neural network model-inverse control can reduce costs and period associated with PCS development.(4) The adaptive neural network has a potential ability of PCS redesign and maintenance of handling quality, following unexpected part failures and battle damage.(5) The trajectory controller can be utilized for MTEs simulation and handlling quality evaluation.