Stephen V. Lunzman

An observer design for a poppet type pressure reducing valve

This paper presents an observer design that may be used to improve the response and stability characteristics of a solenoid operated pressure-reducing valve. Most pressure-reducing valves have very little inherent damping, and can potentially exhibit unstable behavior due to fluid velocity effects during the opening of the poppet. One solution is to improve the dynamic characteristics of the valve by using a closed-loop control strategy. Here, the solenoid current, poppet position, the poppet velocity and the control pressure are feedback signals, used to increase the stability margin and the response time. The cost of the sensors and problems associated with taking derivatives make direct measurement infeasible. We propose to obtain estimates of the poppet position and poppet velocity from only measurements of the valve control pressure and the solenoid current. This is done using a state observer that estimates the poppet position and the poppet velocity without calculating derivatives. These estimates may then be used in a feedback controller that is designed to meet the valve transient response specifications.

Modeling and analysis of an electronic load sensing pump

This paper describes the modeling and analysis of the dynamics of an electronic load sensing hydraulic system consisting of a load sensing pump, a flow control valve, a hydraulic cylinder and an effective mass representing the linkage inertia. Load sensing hydraulic circuits are prone to instabilities and frequently require hydraulic filters in the form of orifices and control volumes to remove unwanted oscillations. Closed loop controllers for such systems are difficult to design due to the nonlinearities and high order transfer functions. In this paper a linear model is derived from equations of motion, and validated against a nonlinear simulation model based on MATLAB. Then, a third order model is derived that can be used for controller design.

Parameter estimation of an electronic load sensing pump using the Recursive Least Squares algorithm

This paper describes a method to estimate in realtime the parameters of a linear model of an electronic load sensing (ELS) pump. It consists of a pressure sensor to measure the load pressure, a pressure sensor to measure the pump discharge pressure, and a Recursive Least Squares (RLS) algorithm implemented in software that runs on an Electronic Control (ECM) in real-time. The RLS algorithm estimates a linear model of the electronic load-sensing pump by measuring the load pressure data, which is the input to the model, the pump discharge pressure data which is the output of the model, and obtaining recursively a least-squares fit to the input-output data. This method can be used to design robust, adaptive controllers for load-sensing systems, or simply to monitor the dynamic performance of the load-sensing pump. The feasibility of this concept has been verified using models of the electronic load-sensing system, and a floating-point implementation of the RLS algorithm.