An LMS-like algorithm is applied for estimating the time-varying parameter theta-n in the linear model y(n) = phi-n-tau-theta-n + upsilon-n, which is general in the sense that none of the probabilistic properties such...An LMS-like algorithm is applied for estimating the time-varying parameter theta-n in the linear model y(n) = phi-n-tau-theta-n + upsilon-n, which is general in the sense that none of the probabilistic properties such as stationarity, Markov property, independence and ergodicity is imposed on any of the processes {y(n)}, {phi-n}, {theta-n} and {upsilon-n}. It is shown that the alpha-th moment of the estimation error is of order of the alpha-th moment of the observation noise and the parameter variation w(n) change in equivalence theta-n - theta-n-1.展开更多
针对常见控制策略在大型液压设备控制方面存在控制精度低与算法太复杂的问题,提出了基于线性扩张状态观测器(linear extended state observer,LESO)的线性时变模型预测控制(linear time-varying model predictive control,LTV-MPC)策略...针对常见控制策略在大型液压设备控制方面存在控制精度低与算法太复杂的问题,提出了基于线性扩张状态观测器(linear extended state observer,LESO)的线性时变模型预测控制(linear time-varying model predictive control,LTV-MPC)策略。通过起竖液压系统状态空间方程,设计了LESO实时估计系统当前状态;通过LTV-MPC输出比例阀电压信号的最优解。通过仿真与试验,验证所提方法的有效性。结果表明:无干扰时,相较于其他控制策略,LESO-LTV-MPC控制误差为0.014%,具有较高的控制精度;施加大干扰时,LESO-LTV-MPC控制误差为0.223%,具有较强的鲁棒性。因此,该控制策略能够有效提升起竖液压系统的性能。展开更多
文摘An LMS-like algorithm is applied for estimating the time-varying parameter theta-n in the linear model y(n) = phi-n-tau-theta-n + upsilon-n, which is general in the sense that none of the probabilistic properties such as stationarity, Markov property, independence and ergodicity is imposed on any of the processes {y(n)}, {phi-n}, {theta-n} and {upsilon-n}. It is shown that the alpha-th moment of the estimation error is of order of the alpha-th moment of the observation noise and the parameter variation w(n) change in equivalence theta-n - theta-n-1.
文摘针对常见控制策略在大型液压设备控制方面存在控制精度低与算法太复杂的问题,提出了基于线性扩张状态观测器(linear extended state observer,LESO)的线性时变模型预测控制(linear time-varying model predictive control,LTV-MPC)策略。通过起竖液压系统状态空间方程,设计了LESO实时估计系统当前状态;通过LTV-MPC输出比例阀电压信号的最优解。通过仿真与试验,验证所提方法的有效性。结果表明:无干扰时,相较于其他控制策略,LESO-LTV-MPC控制误差为0.014%,具有较高的控制精度;施加大干扰时,LESO-LTV-MPC控制误差为0.223%,具有较强的鲁棒性。因此,该控制策略能够有效提升起竖液压系统的性能。
