I want you to help me with question C:

Need to see the simulink to how implement X hat to get estimated State.

Problem 1) 50 points The below system represents the longitudinal dynamics of an aircraft trimmed as some flight condition. The control input is the elevator position in degrees and the states and outputs are as follows : pitch angle,rad pitch rate,rad/sec u : x- axis velocity,ft/sec w: z- axis velocity,ft/sec V: aircraft total velocity,ft/sec a:angle of attack,rad 0 pitch angle,rad q: pitch rate, rad/sec Implement this aircraft in Simulink (using the State-Space block?) and use the below figure to create the control input to the system using the Signal Builder block from the Sources pallet. Plot the state (X) and output (Y) response to the below control input. (How to extract the states, X?) (15 points) Now, create the measurement (Z) by adding normal random noise to each of the outputs. Use the variance values of [0.0001, 0.00000005, 0.00002, 0.00002] (assume these are also the values in the R matrix) for the noise, respectively, and add the noise to the output. Change the sample time on the random noise to 0.0 seconds. Generate the measurement time histories. (15 points) a) b) c) Next, implement the maximum likelihood estimator and create the time history of the estimated states (Xhat). (15 points) Problem 1) 50 points The below system represents the longitudinal dynamics of an aircraft trimmed as some flight condition. The control input is the elevator position in degrees and the states and outputs are as follows : pitch angle,rad pitch rate,rad/sec u : x- axis velocity,ft/sec w: z- axis velocity,ft/sec V: aircraft total velocity,ft/sec a:angle of attack,rad 0 pitch angle,rad q: pitch rate, rad/sec Implement this aircraft in Simulink (using the State-Space block?) and use the below figure to create the control input to the system using the Signal Builder block from the Sources pallet. Plot the state (X) and output (Y) response to the below control input. (How to extract the states, X?) (15 points) Now, create the measurement (Z) by adding normal random noise to each of the outputs. Use the variance values of [0.0001, 0.00000005, 0.00002, 0.00002] (assume these are also the values in the R matrix) for the noise, respectively, and add the noise to the output. Change the sample time on the random noise to 0.0 seconds. Generate the measurement time histories. (15 points) a) b) c) Next, implement the maximum likelihood estimator and create the time history of the estimated states (Xhat). (15 points)