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  • Jih-Gau Juang
  • 2000
In this paper, a learning scheme using a fuzzy controller to generate walking gaits is developed. The learning scheme uses a fuzzy controller combined with a linearized inverse biped model. The controller provides the control signals at each control time instant. The algorithm used to train the controller is "backpropagation through time". The linearized(More)
The atmospheric disturbances affect not only flying qualities of an airplane but also flight safety. According to flight records, most aircraft accidents occurred during final approach or landing. If the flight conditions are beyond the preset envelope, the automatic landing system (ALS) is disabled and the pilot takes over. An inexperienced pilot may not(More)
Computational intelligence that utilizes adaptive fuzzy cerebellar model articulation controller (FCMAC) to aircraft automatic landing system is proposed in this paper. The proposed intelligent scheme uses CMAC and type-2 fuzzy system. Current flight control law is adopted in the controller design. Lyapunov stability theory is applied to obtain adaptive(More)
Nonlinear system identification using recurrent neural network with genetic algorithm is presented. A continuous-time model of Hopfield neural network is used in this study. Its convergence properties are first evaluated. Then the model is implemented to identify nonlinear systems. Recurrent network's operational factors of the system identification scheme(More)