Non-linear modelling and optimal control of a hydraulically actuated seismic isolator test rig

Accurate state estimation for a hydraulic actuator via a SDRE nonlinear filter

“…The hydraulic actuator has been modeled by means of (10), in which the parameters have been determined by means of an identification procedure [20] and are: The performances of the SDRE filter will be evaluated by comparison with the EKF estimator and the real state. The observers have been designed taking into account as input the signal u and the measurements given by displacement y, the load pressure P L and the spool valve displacement v e .…”

“…The equations in (11) function if an overlapped valve is adopted [20]. The proportional valve dynamics can be well represented by a second order differential equation [28]:…”

“…With the computation of the filter gain (19) and evaluating the measurement residual, the updates of the state estimates (20) and of the estimation of the error covariance (21) can be determined:…”

“…The SDRE filter (SDREF) originates from a suboptimal nonlinear regulator technique that uses parameterization to bring the nonlinear system into a linear-like structure with state-dependent coefficients (SDC) and is characterized by the structure of the steady state Kalman filter and the Kalman gain is obtained by solving an algebraic Riccati equation. The SDRE based techniques have been adopted in advanced guidance [18,19], in the control of hydraulic seismic isolator test rig [20], in sensor fusion applications [21], in output feedback nonlinear H2 autopilot [22]. Optimality, suboptimality, and stability properties have been discussed in [23], while the SDRE filter formulation has been used in [24].…”

A SDRE-based tracking control for a hydraulic actuation system

“…The adoption of Ψ(v e ) is particularly efficient to describe a dead zone function if an overlapped valve is adopted [29]. The proportional valve dynamics can be well represented by a second order differential equation [31] € v e…”