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.

[1]  Gene F. Franklin,et al.  Digital control of dynamic systems , 1980 .

[2]  Thomas Kailath,et al.  Linear Systems , 1980 .

[3]  K. Jørgensen,et al.  Modern Control Systems for MSW Plants , 2000 .

[4]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[5]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .