You should make the critical assumption for this technique is that one can observe the inner...

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You should make the critical assumption for this technique is that one can observe the inner states, XN(S), of the plant. This assumption is not always valid, but you can use it here. Given a plant, as described by this transfer function: G(s) 1 1s³-4 s² +41s-74 Compute the Poles of this plant. Note that all of the poles are in the Right-Half plane, so this system is inherently Unstable. Convert this plant into a State Space representation, with matrices A, B, C, and D. Now, Derive a gain matrix, K, that will place the poles at: s = -1, -2, and -3 State your gain matrix, K. Original State Space Equation: For Reference, this gain matrix K is a (1 x N) multiplied by the (Nx 1) state vector X to create a single (1 x 1) feedback signal added to the input of the system, according to this equation X = AX + Bu y = CX + Du Pole Placement State Space Equation with K matrix: X= AX + B (u – (KX)) = (A-BK) X + Bu You should make the critical assumption for this technique is that one can observe the inner states, XN(S), of the plant. This assumption is not always valid, but you can use it here. Given a plant, as described by this transfer function: G(s) 1 1s³-4 s² +41s-74 Compute the Poles of this plant. Note that all of the poles are in the Right-Half plane, so this system is inherently Unstable. Convert this plant into a State Space representation, with matrices A, B, C, and D. Now, Derive a gain matrix, K, that will place the poles at: s = -1, -2, and -3 State your gain matrix, K. Original State Space Equation: For Reference, this gain matrix K is a (1 x N) multiplied by the (Nx 1) state vector X to create a single (1 x 1) feedback signal added to the input of the system, according to this equation X = AX + Bu y = CX + Du Pole Placement State Space Equation with K matrix: X= AX + B (u – (KX)) = (A-BK) X + Bu