params.h)
models, _ = RBPF.setup_rbpf(linsystems, params.C2, params.Q, params.R2)
A = numpy.array([[0.98, 0.00, 0.00, 0.00, 0.00, 0.01, 0.00],
[0.00, 0.98, 0.00, 0.01, 0.01, 0.01, 0.00],
[0.01, 0.00, 0.98, 0.00, 0.00, 0.01, 0.01],
[0.00, 0.00, 0.00, 0.98, 0.00, 0.01, 0.00],
[0.00, 0.01, 0.00, 0.00, 0.99, 0.00, 0.00],
[0.01, 0.01, 0.01, 0.01, 0.00, 0.96, 0.00],
[0.00, 0.00, 0.01, 0.00, 0.00, 0.00, 0.99]])
numModels = len(models)
nP = 500 # number of particles
init_state = linsystems[5].op
sguess = RBPF.get_initial_switches(init_state, linsystems)
particles = RBPF.init_rbpf(sguess, init_state, params.init_state_covar, 2, nP)
switchtrack = numpy.zeros([len(linsystems), params.N])
maxtrack = numpy.zeros([len(linsystems), params.N])
# # Setup the controllers
setpoint = 0.9
H = numpy.matrix([1.0, 0.0])
controllers = [None] * len(models) # type: typing.List[LQR.Controller]
for k in range(len(models)):
ysp = numpy.matrix(setpoint - models[k].b[0]) # set point is set here
x_off, u_off = LQR.offset(models[k].A, models[k].B, params.C2, H, ysp)
K = LQR.lqr(models[k].A, numpy.matrix(models[k].B), params.QQ, params.RR)
controllers[k] = LQR.Controller(K, x_off, u_off)
tend = 200
params = params.Params(tend)
# Get the three linear models about the nominal operating points
linsystems = params.cstr_model.get_nominal_linear_systems(params.h)
# Setup the RBPF
models, _ = RBPF.setup_rbpf(linsystems, params.C2, params.Q, params.R2)
A = numpy.array([[0.99, 0.01, 0.00], [0.01, 0.98, 0.01], [0.00, 0.01, 0.99]])
numModels = len(models) # number of linear models (will be 3)
nP = 500 # number of particles
init_state = linsystems[1].op
sguess = RBPF.get_initial_switches(init_state,
linsystems) # prior switch distribution
particles = RBPF.init_rbpf(sguess, init_state, params.init_state_covar, 2, nP)
switchtrack = numpy.zeros([len(linsystems), params.N])
maxtrack = numpy.zeros([len(linsystems), params.N])
# Setup the controllers
setpoint = 0.9
H = numpy.matrix([1.0, 0.0])
controllers = [None] * len(models) # type: typing.List[LQR.Controller]
for k in range(len(models)):
ysp = numpy.matrix(setpoint - models[k].b[0]) # set point is set here
x_off, u_off = LQR.offset(models[k].A, models[k].B, params.C2, H, ysp)
K = LQR.lqr(models[k].A, numpy.matrix(models[k].B), params.QQ, params.RR)
controllers[k] = LQR.Controller(K, x_off, u_off)