Auto-calibration Based Control and Its Application to a Kind of Electrohydraulic Poppet Valves

Abstract

This paper describes a novel learning/adaptive state trajectory control method and its application to electronic hydraulic pressure control. The control algorithm presented herein learns the inverse input-state mapping of the plant at the same time this map is employed in the feedforward loop to force the state of the plant to asymptotically converge to a prescribed state trajectory. The algorithm accomplishes this task without requiring prior exact information about the state transition map of the plant. The novel controller is applied to an electrohydraulic poppet valve with the objective of tracking a desired supply pressure signal. In this application, the controller learns the inverse conductance characteristics of the valve. The supply pressure tracking performance subject to the proposed controller is validated through experimental data.

Model-free learning control of nonlinear discrete-time systems

“…The following Lemma (see Appendix A for a proof) shows that the difference equations given by (10) and (9) for the disturbance free linearized error system is uniformly exponentially stable if the PE Assumption (A 4 ) is satisfied. To state the lemma, we first need to express the evolution of the parameter error matrix (W k ) for the linearized error system.…”

“…The learning control techniques evolved during the last two decades [1], [2], [3], [4], [5], [6] offer an effective solution for many applications ranging from robotics [7], [8] to fluid power applications [9], [10], [11] to disk drive actuation [6] and magnetic levitation [5].…”

Intelligent controls for electro-hydraulic poppet valves

“…See Opdenbosch (2007) and Opdenbosch, Sadegh, and Book (2011). & Theorem 2 requires that the initial state tracking error be sufficiently small, the state to be persistently excited, and that there exists an initial input-state map to initializeŴ.…”

“…The response of the 'SR' EHPV subject to the control law is now presented for the case in which the hydraulic actuator remains stationary (i.e. _ y ¼ 0) (see Opdenbosch et al, 2011, for more extended results including the case _ y a 0). Tracking of the desired flow conductance is illustrated in Fig.…”

Advanced Flow Control for Supersonic Blowdown Wind Tunnel Using Extended Kalman Filter

“…Some early work can be traced back to 1980s when a classical PID controller has been proposed to tune the stagnation pressure automatically [2], Following this design methodology, many Pi-based controllers have been derived since then [1,[3][4][5][6][7]. There have also been some work concerning with the precise valve control [9], However, present methods for the control of blowdown wind tunnels suffer from common limitations concluded as follows: There have also been some work concerning with the precise valve control [9], However, present methods for the control of blowdown wind tunnels suffer from common limitations concluded as follows:…”