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djulzz1982
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- Homework Statement
- . A point-mass not subjected to gravity is "floating" in space.
. The point-mass has a mass m, and has two lateral thrusters, opposite one another.
. The first thruster generates a max force T1, the second thruster generates a max force T2.
. For the sake of problem formulation, the point-mass can move along the x direction.
. Assume no friction (the point-mass is in space).
1) Write the equations of motion (EOM) for the 1D point-mass
2) Convert the derived EOS(s) to a state space representation
3) If feasible, design an Linear Quadratic Regulator (LQR), that drives the point-mass from x(0) = 0 to x(t) = 4
- Relevant Equations
- According to Newton's 2nd Law, Sum of forces = m . a, so
(T1-T2) = m a, where:
- T1 is the maximum force generated by the first thruster
- T2 is the maximum force generated by the second thruster
- a is the point-mass' acceleration, so a = d^2(x) / d^2(t).
(u1*T1) + (u2*T2) = m (x dot dot), [1.1]
where (x dot dot) is the 2nd derivative of the point-mass position with respect to time, u1 is the control input for the 1st thruster, u2 is the control input for the second thruster.
Rearranging equation 1.1 yields
(x dot dot) = (T1/m)*u1+ (T2/m)*u2 [1.2]
In order to design an LQR controller for such system, its state space formulation is required, as doing so allows to determine if the system is controllable.
The following states are thus defined
- x1 = x dot ↔ x dot dot = x1 dot
- x2 = x ↔ x2 dot = x1 [1.3]
Rearranging equation [1.2] with the state space variables defined in [1.3] yields:
- x1 dot = (T1/m)*u1 + (T2/m)*u2
- x2 dot = x1 [1.4]
The state space vector is thus x = [x1 x2]T
where (x dot dot) is the 2nd derivative of the point-mass position with respect to time, u1 is the control input for the 1st thruster, u2 is the control input for the second thruster.
Rearranging equation 1.1 yields
(x dot dot) = (T1/m)*u1+ (T2/m)*u2 [1.2]
In order to design an LQR controller for such system, its state space formulation is required, as doing so allows to determine if the system is controllable.
The following states are thus defined
- x1 = x dot ↔ x dot dot = x1 dot
- x2 = x ↔ x2 dot = x1 [1.3]
Rearranging equation [1.2] with the state space variables defined in [1.3] yields:
- x1 dot = (T1/m)*u1 + (T2/m)*u2
- x2 dot = x1 [1.4]
The state space vector is thus x = [x1 x2]T