質問編集履歴
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追加説明
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@@ -5,16 +5,65 @@
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ネット上に乗っていたコードをそのまま実行してもエラーが出るので，
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実行できるようにプログラムを変更しています．
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まず初めに
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プログラム内
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x = Variable(n, T + 1)
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u = Variable(m, T)
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だと以下のエラーが出たので
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```
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PS C:\Users\N\Desktop> python test.py
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Simulation start
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Traceback (most recent call last):
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File "test.py", line 21, in <module>
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x = Variable(n, T + 1)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\variable.py", line 75, in __init__
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raise TypeError("Variable name %s must be a string." % name)
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TypeError: Variable name 51 must be a string.
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```
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x = Variable((n, T + 1))
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u = Variable((m, T))
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に変更しました．
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そして実行すると
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プログラム上のprob.constraints += [x[:,T] == 0, x[:,0] == x_0]に対してエラーが出て
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プログラム上のprob.constraints += [x[:,T] == 0, x[:,0] == x_0]に対してエラーが出てたのですが，他のサイト等を調べても同様に書かれているのでどこが違うのかわかりません．
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prob.constraints += [x[:,T] == 0, x[:,0] == x_0]を記述することで制約条件を2つ追加できるそうなのですが．．．．
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載せているソースコードは
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x = Variable((n, T + 1))
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u = Variable((m, T))
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に変更したものを載せています．
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### 発生している問題・エラーメッセージ
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```
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PS C:\Users\N\Desktop> python test.py
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Simulation start
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Traceback (most recent call last):
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File "test.py", line 32, in <module>
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prob.constraints += [x[:,T] == 0, x[:,0] == x_0]
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prob.constraints += [x[:, T] == 0, x[:, 0] == x_0]
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 46, in cast_op
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return binary_op(self, other)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 575, in __eq__
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return Equality(self, other)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\constraints\zero.py", line 114, in __init__
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self._expr = lhs - rhs
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 46, in cast_op
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return binary_op(self, other)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 464, in __sub__
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return self + -other
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 46, in cast_op
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return binary_op(self, other)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\expressions\expression.py", line 452, in __add__
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return cvxtypes.add_expr()([self, other])
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\atoms\affine\add_expr.py", line 33, in __init__
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super(AddExpression, self).__init__(*arg_groups)
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\atoms\atom.py", line 45, in __init__
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self._shape = self.shape_from_args()
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\atoms\affine\add_expr.py", line 41, in shape_from_args
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return u.shape.sum_shapes([arg.shape for arg in self.args])
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File "C:\Users\N\AppData\Local\Programs\Python\Python37\lib\site-packages\cvxpy\utilities\shape.py", line 49, in sum_shapes
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len(shapes)*" %s" % tuple(shapes))
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ValueError: Cannot broadcast dimensions (4,) (4, 1)
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```
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### 該当のソースコード
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print("Simulation start")
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np.random.seed(1)
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n =
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n = 4 # state size
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m =
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m = 2 # input size
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T = 50 #number of horizon
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T = 50 # number of horizon
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#simulation parameter
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# simulation parameter
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alpha = 0.2
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beta = 5.0
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# Model Parameter
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A = np.eye(n) + alpha*np.random.randn(n,n)
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A = np.eye(n) + alpha * np.random.randn(n, n)
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B = np.random.randn(n,m)
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B = np.random.randn(n, m)
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x_0 = beta*np.random.randn(n,1)
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x_0 = beta * np.random.randn(n, 1)
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x = Variable((n, T+1))
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x = Variable((n, T + 1))
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u = Variable((m, T))
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states = []
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for t in range(T):
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cost = sum_squares(x[:,t+1]) + sum_squares(u[:,t])
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cost = sum_squares(x[:, t + 1]) + sum_squares(u[:, t])
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constr = [x[:,t+1] == A*x[:,t] + B*u[:,t],
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constr = [x[:, t + 1] == A * x[:, t] + B * u[:, t],
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norm(u[:,t], 'inf') <= 1]
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norm(u[:, t], 'inf') <= 1]
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states.append(
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states.append(Problem(Minimize(cost), constr))
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# sums problem objectives and concatenates constraints.
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prob = sum(states)
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prob.constraints += [x[:,T] == 0, x[:,0] == x_0]
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prob.constraints += [x[:, T] == 0, x[:, 0] == x_0]
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start = time.time()
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result=prob.solve(verbose=True)
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result = prob.solve(verbose=True)
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elapsed_time = time.time() - start
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print ("calc time:{0}".format(elapsed_time)
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print ("calc time:{0}".format(elapsed_time) + "[sec]")
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if result == float("inf"):
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print("Cannot optimize")
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import sys
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sys.exit()
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# return
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#以下グラフの表示
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f = plt.figure()
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# Plot (u_t)_1.
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ax = f.add_subplot(211)
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u1 = np.array(u[0, :].value[0, :])[0].tolist()
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u2 = np.array(u[1, :].value[0, :])[0].tolist()
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plt.plot(u1, '-r', label="u1")
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plt.plot(u2, '-b', label="u2")
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plt.ylabel(r"$u_t$", fontsize=16)
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plt.yticks(np.linspace(-1.0, 1.0, 3))
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plt.legend()
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plt.grid(True)
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# Plot (u_t)_2.
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plt.subplot(2, 1, 2)
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x1 = np.array(x[0, :].value[0, :])[0].tolist()
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x2 = np.array(x[1, :].value[0, :])[0].tolist()
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x3 = np.array(x[2, :].value[0, :])[0].tolist()
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x4 = np.array(x[3, :].value[0, :])[0].tolist()
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plt.plot(range(T + 1), x1, '-r', label="x1")
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plt.plot(range(T + 1), x2, '-b', label="x2")
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plt.plot(range(T + 1), x3, '-g', label="x3")
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plt.plot(range(T + 1), x4, '-k', label="x4")
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plt.yticks([-25, 0, 25])
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plt.ylim([-25, 25])
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plt.ylabel(r"$x_t$", fontsize=16)
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plt.xlabel(r"$t$", fontsize=16)
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plt.grid(True)
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plt.legend()
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plt.tight_layout()
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plt.show()
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```
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### 試したこと
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1
追加説明
title
CHANGED
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File without changes
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body
CHANGED
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@@ -6,6 +6,7 @@
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6
6
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実行できるようにプログラムを変更しています．
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プログラム上のprob.constraints += [x[:,T] == 0, x[:,0] == x_0]に対してエラーが出ているのですが，他のサイト等を調べても同様に書かれているのでどこが違うのかわかりません．
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prob.constraints += [x[:,T] == 0, x[:,0] == x_0]を記述することで制約条件を2つ追加できるそうなのですが．．．．
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### 発生している問題・エラーメッセージ
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```
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