针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重...针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重和势函数。在每个采样时间点根据墙体信息和机器人的状态进行计算获得控制输入。此外,还提出了为NMPC在线配置性能指标的视距评估方法。研究结果表明:随着视距的减小,控制输入的计算时间也随之减少,有效降低了计算成本;与将墙体上的所有支撑都纳入视距范围的情况相比,攀爬时间最多能减少36.4%,有效适应了复杂的墙体模型。展开更多
In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinet...In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinetic and kinematic virtual constraints of Single Support Phase (SSP) and three subphases of Double Support Phase (DSP) ,complex realtime gait programming problem was simplified to four online NMPC dynamic optimization problems. A numerical approach was proposed to transform the dynamical optimization problem to the finite dimensional static optimization problem which can be solved by Sequential Quadratic Programming (SQP) . It can be concluded from simulation that using this method on BIP model can realize online gait programming of dynamic walking with foot rotation and the biped stability can be satisfied such that there is no sliding during walking.展开更多
针对欠驱动水面船舶轨迹跟踪控制问题,根据模型预测控制(Model Predictive Control, MPC)原理,提出一种基于参数化模型的非线性模型预测控制(Parameterized Model-Nonlinear Model Predictive Control, PM-NMPC)方法。采用最小二乘法对...针对欠驱动水面船舶轨迹跟踪控制问题,根据模型预测控制(Model Predictive Control, MPC)原理,提出一种基于参数化模型的非线性模型预测控制(Parameterized Model-Nonlinear Model Predictive Control, PM-NMPC)方法。采用最小二乘法对船舶的参数化模型进行辩识,设计PM-NMPC控制器。对环境干扰下的某集装箱船艏向角控制和轨迹跟踪进行试验,验证控制算法的有效性,并将该控制器与比例积分微分控制器(Proportional plus Integral plus Derivative cotroller, PID cotroller)控制器进行对比。仿真结果表明,PM-NMPC控制器轨迹跟踪效果更好,对未知干扰具有更强的稳健性。展开更多
文摘针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重和势函数。在每个采样时间点根据墙体信息和机器人的状态进行计算获得控制输入。此外,还提出了为NMPC在线配置性能指标的视距评估方法。研究结果表明:随着视距的减小,控制输入的计算时间也随之减少,有效降低了计算成本;与将墙体上的所有支撑都纳入视距范围的情况相比,攀爬时间最多能减少36.4%,有效适应了复杂的墙体模型。
基金Sponsored by the National High Technology Research and Development Program of China ( 863 Program) ( Grant No. 2006AA04Z201)
文摘In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinetic and kinematic virtual constraints of Single Support Phase (SSP) and three subphases of Double Support Phase (DSP) ,complex realtime gait programming problem was simplified to four online NMPC dynamic optimization problems. A numerical approach was proposed to transform the dynamical optimization problem to the finite dimensional static optimization problem which can be solved by Sequential Quadratic Programming (SQP) . It can be concluded from simulation that using this method on BIP model can realize online gait programming of dynamic walking with foot rotation and the biped stability can be satisfied such that there is no sliding during walking.
文摘针对欠驱动水面船舶轨迹跟踪控制问题,根据模型预测控制(Model Predictive Control, MPC)原理,提出一种基于参数化模型的非线性模型预测控制(Parameterized Model-Nonlinear Model Predictive Control, PM-NMPC)方法。采用最小二乘法对船舶的参数化模型进行辩识,设计PM-NMPC控制器。对环境干扰下的某集装箱船艏向角控制和轨迹跟踪进行试验,验证控制算法的有效性,并将该控制器与比例积分微分控制器(Proportional plus Integral plus Derivative cotroller, PID cotroller)控制器进行对比。仿真结果表明,PM-NMPC控制器轨迹跟踪效果更好,对未知干扰具有更强的稳健性。
