论文标题
人形机器人螺距轴线使用线性二次调节器具有模糊逻辑和捕获点
Humanoid Robot Pitch Axis Stabilization using Linear Quadratic Regulator with Fuzzy Logic and Capture Point
论文作者
论文摘要
本文旨在使用一个控制器，该控制器可以在站立时稳定位置控制的人形机器人或在合成草上行走，即使受到外部干扰。设计和实施了两种类型的控制器：踝关节策略和踩踏策略。机器人的关节由位置控制的伺服器组成，由于非线性和不可衡量的参数，可以通过分析模型变得复杂，因此使用非恢复性最小二乘系统识别获得了类人体机器人的动态模型。该模型还用于设计Kalman滤波器，以估算系统状态从嘈杂的惯性测量单元（IMU）传感器和设计线性二次调节器（LQR）控制器中。为了处理非线性，使用模糊逻辑算法扩展了LQR控制器，该算法会根据角度和角速度成员函数更改LQR增益值。当受到摆动障碍，甚至从弹簧平衡中限制力时，提出的控制系统可以维持螺距轴周围的人形机器人的稳定性。
This paper aims for a controller that can stabilize a position-controlled humanoid robot when standing still or walking on synthetic grass even when subjected to external disturbances. Two types of controllers are designed and implemented: ankle strategy and stepping strategy. The robot's joints consist of position-controlled servos which can be complicated to model analytically due to nonlinearities and non-measurable parameters, hence the dynamic model of the humanoid robot is acquired using a non-recursive least squares system identification. This model is also used to design a Kalman Filter to estimate the system states from noisy inertial measurement unit (IMU) sensor and design a linear quadratic regulator (LQR) controller. To handle the nonlinearities, the LQR controller is extended with fuzzy logic algorithm that changes the LQR gain value based on angle and angular velocity membership functions. The proposed control system can maintain the humanoid robot's stability around the pitch axis when subject to pendulum disturbances or even restraining force from a spring balance.
