def create_mpc(self, mpc_type, N, opts={}, tuning=None):
""" Create MPC controller of user-defined type and horizon
for given system dynamics, constraints and cost function.
"""
if mpc_type not in ['economic', 'tuned', 'tracking']:
raise ValueError('Provided MPC type not supported.')
if 'slack_flag' in opts.keys():
mpc_sys = preprocessing.add_mpc_slacks(
copy.deepcopy(self.__sys),
self.__ocp.lam_g,
self.__ocp.indeces_As,
slack_flag=opts['slack_flag'])
else:
mpc_sys = self.__sys
if mpc_type == 'economic':
mpc = pmpc.Pmpc(N=N,
sys=mpc_sys,
cost=self.__l,
wref=self.__w_sol,
lam_g_ref=self.__ocp.lam_g,
options=opts)
else:
cost = self.__tracking_cost(self.__nx + self.__nu + self.__nus)
lam_g0 = copy.deepcopy(self.__ocp.lam_g)
lam_g0['dyn'] = 0.0
if 'g' in lam_g0.keys():
lam_g0['g'] = 0.0
if mpc_type == 'tracking':
if tuning is None:
raise ValueError(
'Tracking type MPC controller requires user-provided tuning!'
)
elif mpc_type == 'tuned':
tuning = {'H': self.__S['Hc'], 'q': self.__S['q']}
mpc = pmpc.Pmpc(N=N,
sys=mpc_sys,
cost=cost,
wref=self.__w_sol,
tuning=tuning,
lam_g_ref=lam_g0,
options=opts)
return mpc
def test_add_mpc_slacks_no_constraints():
""" Test automatic soft constraint generation if no constraints are present.
"""
x = ca.MX.sym('x',1)
u = ca.MX.sym('u',2)
# case of no constraints
sys = {}
sys['F'] = ca.Function('F',[x,u],[x])
sys['vars'] = collections.OrderedDict()
sys['vars']['x'] = x
sys['vars']['u'] = u
sys = preprocessing.add_mpc_slacks(sys, None, None, slack_flag = 'active')
assert 'h' not in sys, 'non-existent lin. inequalities are being created'
assert 'usc' not in sys['vars'], 'non-existent slack variables are being created'
def test_add_mpc_slacks_no_active_constraints():
""" Test automatic soft constraint generation if no active constraints are present.
"""
x = ca.MX.sym('x',1)
u = ca.MX.sym('u',2)
# case of no active constraints
sys = {}
sys['F'] = ca.Function('F',[x,u],[x])
h = ca.Function('h',[x,u],[ca.vertcat(x+u[0], u[1])])
sys['h'] = h
sys['vars'] = collections.OrderedDict()
sys['vars']['x'] = x
sys['vars']['u'] = u
active_set = [[],[]]
sys = preprocessing.add_mpc_slacks(sys, None, active_set, slack_flag = 'active')
assert 'h' in sys, 'lin. inequalities are being removed'
assert 'usc' not in sys['vars'], 'non-existent slack variables are being created'
def test_add_mpc_slacks_active_constraints():
""" Test automatic soft constraint generation if active constraints are present.
"""
x = ca.MX.sym('x', 1)
u = ca.MX.sym('u', 2)
# case of no active constraints
sys = {}
sys['f'] = ca.Function('f', [x, u], [x])
h = ca.Function('h', [x, u], [ca.vertcat(x + u[0], u[1])])
sys['h'] = h
sys['vars'] = collections.OrderedDict()
sys['vars']['x'] = x
sys['vars']['u'] = u
lam_g_struct = ca.tools.struct_symMX(
[ca.tools.entry('h', shape=(2, 1), repeat=2)])
lam_g = lam_g_struct(0.0)
lam_g['h', 0, 0] = -5.0
active_set = [[0], []]
sys = preprocessing.add_mpc_slacks(sys,
lam_g,
active_set,
slack_flag='active')
assert 'h' in sys, 'lin. inequalities are being removed'
assert 'usc' in sys['vars'], 'slack variables are not being created'
assert sys['vars']['usc'].shape[
0] == 1, 'slack variables are not being created'
assert 'scost' in sys, 'slack cost is not being created'
x_num = 1.0
u_num = ca.vertcat(0.0, 2.0)
usc_num = ca.vertcat(3.0)
h_eval = sys['h'](x_num, u_num, usc_num).full()
scost_eval = sys['scost'].full()
print(scost_eval)
assert ca.vertsplit(h_eval) == [4.0, 2.0, 3.0]
assert scost_eval[0][0] == 5000.
sol['wsol']['x',0][2]**2
)
opts = {}
# add projection operator for terminal constraint
opts['p_operator'] = ca.Function(
'p_operator',
[sol['sys']['vars']['x']],
[ct.vertcat(sol['sys']['vars']['x'][1:3],
sol['sys']['vars']['x'][4:])]
)
# add MPC slacks to active constraints
mpc_sys = preprocessing.add_mpc_slacks(
sol['sys'],
sol['lam_g'],
sol['indeces_As'],
slack_flag = 'active'
)
# create controllers
ctrls = {}
# # economic MPC
tuning = {'H': sol['S']['Hc'], 'q': sol['S']['q']}
ctrls['EMPC'] = pmpc.Pmpc(
N = Nmpc,
sys = mpc_sys,
cost = user_input['l'],
wref = sol['wsol'],
lam_g_ref = sol['lam_g'],
sensitivities= sol['S'],
options = opts