基于状态观测的变量柱塞泵LQ最优控制

LQ Optimal Control of Variable Piston Pump Based on State Observation

针对变量柱塞泵传统控制方法难以实现快速性、稳定性、鲁棒性的兼顾,也不能估计并利用泵的状态参数进行全生命周期内的性能优化等问题,提出了一种基于状态观测器的变量柱塞泵流量LQ最优控制(Linear Quadratic Optimal Control)方法,在改善泵控制性能的同时实现了泵不可测状态参数的在线估计。以A4VSO40柱塞泵为例,建立了变量柱塞泵的数学模型,以状态误差和控制输入的二次型约束为性能指标,设计了变量柱塞泵流量的LQ最优控制器,针对实际中因测量条件或成本限制难以测得全部状态参数以及测量噪声等问题,设计并引入了卡尔曼滤波状态观测器。仿真结果表明,所提出的基于状态观测器的LQ最优控制方法不仅可以实现状态参数的估计、减小噪声对状态参数估计的影响,而且相较于PID控制和LQ最优控制,流量阶跃响应的超调量分别下降了24%和5%,验证了所提控制方法的有效性。

The traditional control method for variable piston pump is difficult to achieve the balance of rapidity,stability and robustness,and cannot estimate and use the pump state parameters for optimization in the whole operation cycle.Accordingly,a linear quadratic optimal control strategy based on state observer for variable piston pump was proposed,which improved the control performance of the pump and realized the online estimation of unobservable pump state parameters.Firstly,the mathematical model of A4 VSO variable piston pump was analyzed and established.Then a LQ optimal controller based on the quadratic constraint of state error and control input was designed to control the flow rate of the variable piston pump.Finally,in order to solve the problem of measurement noise and the difficulty of measuring all state parameters due to the measurement condition or cost limitation,the Kalman filter state observer was designed and introduced to eliminate the noise and reduce the dependence on the model.Simulation results show that the proposed method can realize the estimation of state parameters and reduce the noise influence on state parameters estimation.The overshoot decreased by 24%and 5%respectively compared with PID control and LQ optimal control,which can verify the effectiveness of the proposed control method.