Fal!2001 16.3118-1 Combined estimators and requlators mal regulator to design the controller, the compensator is called A When we use the combination of an optimal estimator and an op Linear Quadratic Gaussian(LQG) Special case of the controllers that can be designed using the separation principle The great news about an lqg design is that stability of the closed loop system is guaranteed The designer is freed from having to perform any detailed me- chanics- the entire process is fast and can be automated Now the designer just focuses on How to specify the state cost function (i.e. selecting z= C2 a) and what value of r to use Determine how the process and sensor noise enter into the system and what their relative sizes are(i.e. select Ru ru So the designer can focus on the "performance"related issues, be- ing confident that the lQg design will produce a controller that stabilizes the system This sounds great-so what is the catch??Fall 2001 16.31 18—1 Combined Estimators and Regulators • When we use the combination of an optimal estimator and an opti￾mal regulator to design the controller, the compensator is called Linear Quadratic Gaussian (LQG) — Special case of the controllers that can be designed using the separation principle. • The great news about an LQG design is that stability of the closed￾loop system is guaranteed. — The designer is freed from having to perform any detailed me￾chanics - the entire process is fast and can be automated. • Now the designer just focuses on: — How to specify the state cost function (i.e. selecting z = Czx) and what value of r to use. — Determine how the process and sensor noise enter into the system and what their relative sizes are (i.e. select Rw & Rv) • So the designer can focus on the “performance” related issues, be￾ing confident that the LQG design will produce a controller that stabilizes the system. • This sounds great — so what is the catch??