Matlab Expert -- 2
Budget: $10 – $30 USD
1) You are supplied with a solution of the 2R planar manipulator IK using the ANFIS tool from the MATLAB Fuzzy Logic Toolbox. You are required to extend this to model the IK of a 3R planar manipulator with the following geometry:
Link Lengths:
Link Length
1 7
2 5
3 3
With all angles being limited from 0 to ( π)/2
Explain the methods used to extend the model.
2) Train the system with a known closed-form forwards kinematics solution at a fixed number of positions and then for ANFIS to provide approximate solutions to the IK over the whole usable workspace of the manipulator. Then demonstrate the results obtained through calculations, coding, and experiments.
3) You will need to experiment with a number of parameters to find a system which learns with sufficient accuracy but without unacceptably long training times. It is particularly important to demonstrate that the trained network generalises well using suitable validation methods. Explain validation testing you used including mathematical formulas and critical assess the performance of your system.
4) Design an MLPL Neural Network to achieve the task of the system you designed in 1.
5) Compare the ANFIS model with MLP Neural Network in terms of performance including (error, training time, size of network, etc).
Use Proper references, layout/presentation.
Link Lengths:
Link Length
1 7
2 5
3 3
With all angles being limited from 0 to ( π)/2
Explain the methods used to extend the model.
2) Train the system with a known closed-form forwards kinematics solution at a fixed number of positions and then for ANFIS to provide approximate solutions to the IK over the whole usable workspace of the manipulator. Then demonstrate the results obtained through calculations, coding, and experiments.
3) You will need to experiment with a number of parameters to find a system which learns with sufficient accuracy but without unacceptably long training times. It is particularly important to demonstrate that the trained network generalises well using suitable validation methods. Explain validation testing you used including mathematical formulas and critical assess the performance of your system.
4) Design an MLPL Neural Network to achieve the task of the system you designed in 1.
5) Compare the ANFIS model with MLP Neural Network in terms of performance including (error, training time, size of network, etc).
Use Proper references, layout/presentation.