tailieunhanh - Artificial Neural Networks Industrial and Control Engineering Applications Part 13

Tham khảo tài liệu 'artificial neural networks industrial and control engineering applications part 13', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | System Identification of NN-based Model Reference Control of RUAV during Hover 409 Fig. 12. Transfer function of system 5. Experimental results and analysis In this experiment we used NN approach to train MIMO model and capture the phenomena of flight dynamics. This simulation is divided into two parts longitudinal mode and Lateral mode. The NN approach considers separate lateral and longitudinal network with inertial coupling between the networks taken into consideration. These networks trained individually by making it MIMO model. Basically system identification process consists of gathering experimental data estimate model from data and validate model with independent data. NN controller is designed in such a way that makes the plant output to follow the output of a reference model. The main target is to play with fine tuning of controller in order to minimize the state error. The experiment is carried out with System identification procedures with Prediction Error Method PEM algorithm using System Identification Toolbox using Levenberg-Marquardt LM algorithm. We observe NN approach to get better result of System identification that shows the perfect matching and shown as RUAV Longitudinal Dynamics and RUAV Lateral Dynamics in the following fig. 13-18 The prediction error of the output responses is described in Fig. 14. The autocorrelation function almost tend to zero and the cross correlation function vary in the range of . This shows the dependency between prediction error and Scoii 3long but the dependency rate is very less. 410 Artificial Neural Networks - Industrial and Control Engineering Applications Longitudinal Dynamics Mode Analysis a Pitch Angle 0 b Forward Velocity u c Vertical velocity w System Identification of NN-based Model Reference Control of RUAV during Hover 411 d Pitch Angular Rate q Fig. 13. Output response with network response in Longitudinal dynamics mode a Pitch Angle 0

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