一种基于卡尔曼滤波器的单级倒立摆的LQR方法

倒立摆的控制因其系统动态模型是非最小相位系统而很难用经典控制算法得到较好的控制效果.提出利用最优控制LQR方法来完成控制.由于利用最优控制,系统状态必须全部已知.考虑到系统噪声和量测噪声,根据分离性原理,利用LQR方法设计控制律,利用卡尔曼状态估计来完成系统状态的重构.仿真结果显示该方法具有良好的控制效果.

Inverted Pendulum LQR Control Strategy Based on Kalman Filter

The control of the inverted pendulum system using classic control methods is very hard and has poor performances for its non-minimum phase property. LQR strategy is proposed in this paper, assuming state variables are measurable. However not all of the system state variables are measurable, so we must use an observer to reconstruct the variables of the system. Considering that there exists system noise and measurement noise,we use Kalman estimator to reconstruct the state variables of the system. The simulation result gives good control effect.