1)u=model.add_variable('u',1)# 定义系统动态方程model.set_rhs('x',x+u)# 创建MPC控制器mpc=do_mpc.controller.MPC(model)# 定义控制参数mpc.set_param(H=10)# 预测步长mpc.set_param(R=1)# 控制权重#
zeros((4,)) simu_freq = 100 # Hz ctrl_freq = 50 traj = Trajectory("diamond") quad_controller = Linear_MPC(traj, ctrl_freq, use_obsv=False) simu_time = 40 # sec cur_time = 0 dt = 1 / simu_freq num_iter = int(simu_time * simu_freq) start = time.time() for i in ...
acceleration_constraint(u): 定义了加速度的约束条件,限制加速度在[-2, 2] m/s²之间,模拟了实际车辆中油门和刹车的物理限制。 mpc_controller(v0, target_speed, N, dt): 这是MPC控制器,预测未来N个时间步内的加速度,并返回最优的第一个时间步的控制输入。minimize的使用可以参考:minimize 使用 simulate...
importmatplotlib.pyplotasplt# 初始化mpc=MPCController(A,B)x0=np.array([0.0])# 初始状态target=10.0# 目标状态timesteps=50# 记录状态states=[x0[0]]for_inrange(timesteps):u=mpc.control(x0,target)# 计算控制输入x0=mpc.A @ x0+mpc.B @ u[0]# 更新状态states.append(x0[0])# 结果可视化...
0. 参考与前言 Python 代码:github AtsushiSakai/PythonRobotics C++ 代码:github jchengai/gpir/mpc_controller 相关参考博文: 无人车系统(十一):轨迹跟踪模型预测控制(MPC)原理与python实现【40行代码】 P
The controller in this example is configured with aneconomic objective, where the task is to maximize the potential energy of the system while minimizing the kinetic energy. An animation of the obtained controller results is shown below:
This code snippets illustrates the use of the MPCController class: from pyMPC.mpc import MPCController K = MPCController(Ad,Bd,Np=20, x0=x0,xref=xref,uminus1=uminus1, Qx=Qx, QxN=QxN, Qu=Qu,QDu=QDu, xmin=xmin,xmax=xmax,umin=umin,umax=umax,Dumin=Dumin,Dumax=Dumax) K.setup(...
there was a significant barrier to integrating PyTorch learning systems with control methods. The appropriate data and tensors would have to be transferred to the CPU, converted to numpy, and then passed into 1) one of the few Python control libraries, like python-control, 2) a hand-coded ...
dt # 累加一次时间周期 # MPC delta_f, target_ind, e_y = MPCController(vehicle, ref_path) if delta_f is None: print("An error occurred, exit...") sys.exit(1) # 横向误差 lat_err.append(e_y) # 更新车辆状态 vehicle.update(0.0, delta_f, np.pi / 10) # 由于假设纵向匀速运动,...
MPC implementation with Python, solved by PANOC/IPOPT This repository provides samples of Model Predictive Controller(MPC) implementation with python. The options of optimization solver is PANOC and IPOPT. Just change "solver_type" in simulation_setting.yaml as you like. What is IPOPT? It is a...