Semi-empirical model for a hydraulic servo-solenoid valve

2002 ◽  
Vol 216 (3) ◽  
pp. 237-248 ◽  
Author(s):  
J A Ferreira ◽  
F Gomes de Almeida ◽  
M R Quintas
Keyword(s):  
Frequency Response ◽  
High Performance ◽  
Closed Loop ◽  
Optimization Techniques ◽  
Order System ◽  
Model Parameters ◽  
Empirical Modelling ◽  
Non Linear ◽  
Spool Valves ◽  
Semi Empirical

High-performance proportional valves, also called servo-solenoid valves, can be used today in closed-loop applications that previously were only possible with servo-valves. The valve spool motion is controlled in a closed loop with a dedicated hardware controller that enhances the valve frequency response and minimizes some non-linear effects. Owing to their lower cost and maintenance requirements as well as increasing performance they can compete with servo-valves in a large number of applications. This paper describes a new semi-empirical modelling approach for hydraulic proportional spool valves to be used in hardware-in-the-loop simulation experiments. The developed models use either data sheet or experimental values to fit the model parameters in order to reproduce both static (pressure gain, leakage flowrate and flow gain) and dynamic (frequency response) valve characteristics. Valve behaviour is divided into two parts: the static behaviour and the dynamic behaviour. A parameter decoupled model, with a variable equation structure, and a flexible model, with a fixed equation structure, are proposed for the static part. Spool dynamics are modelled by a non-linear second-order system, with limited velocity and acceleration, the parameters being adjusted using optimization techniques.

On the control of a single flexible arm robot via Youla-Kucera parameterization

Robotica ◽  
2014 ◽  
Vol 34 (1) ◽  
pp. 150-172 ◽  
Author(s):  
Habib Esfandiar ◽  
Saeed Daneshmand ◽  
Roozbeh Dargahi Kermani
Keyword(s):  
Closed Loop ◽  
Optimization Techniques ◽  
Loop System ◽  
Flexible Manipulator ◽  
Order System ◽  
Flexible Beam ◽  
Closed Loop System ◽  
Stabilizing Controller ◽  
Main Challenge ◽  
Tip Mass

SUMMARYIn this paper, based on the Youla-Kucera (Y-K) parameterization, the control of a flexible beam acting as a flexible robotic manipulator is investigated. The method of Youla parameterization is the simple solution and proper method for describing the collection of all controllers that stabilize the closed-loop system. This collection comprises function of the Youla parameter which can be any proper transfer function that is stable. The main challenge in this approach is to obtain a Youla parameter with infinite dimension. This parameter is approximated by a subspace with finite dimensions, which makes the problem tractable. It is required to be generated from a finite number of bases within that space and the considered system can be approximated by an expansion of the orthonormal bases such as FIR, Laguerre, Kautz and generalized bases. To calculate the coefficients for each basis, it is necessary to define the problem in the form of an optimization problem that is solved by optimization techniques. The Linear Quadratic Regulator (LQR) optimization tool is employed in order to optimize the controller gains. The main aim in controller design is to merge the closed-loop system and the second order system with the desirable time response characteristic. The results of the Youla stabilizing controller for a planar flexible manipulator with lumped tip mass indicate that the proposed method is very efficient and robust for the time-continuous instances.

Identifying parametric variation in second-order system from frequency response measurement

2016 ◽  
Vol 24 (5) ◽  
pp. 879-891 ◽  
Author(s):  
A Hegde ◽  
J Tang
Keyword(s):  
Frequency Response ◽  
Parametric Identification ◽  
Second Order ◽  
Order System ◽  
Model Parameters ◽  
Order Model ◽  
Response Measurement ◽  
Electrical Systems ◽  
Angle Measurements ◽  
Second Order Model

Fundamentally, second-order model is the foundation of describing the dynamic characteristics of many mechanical and electrical systems. This paper investigates a parametric identification scheme for single degree-of-freedom second-order model in which the model parameters are subject to normal variation. By utilizing frequency response magnitude and phase angle measurements, we construct a linear-in-the-parameters model and build a related maximum likelihood estimator for both parametric means as well as variances. The validity of the approach is demonstrated through a collection of case analyses, and the results show considerable levels of accuracy in the presence of sufficient data.

scholarly journals Parametric space-frequency reduction for second-order system models

2018 ◽  
Author(s):  
Vanessa Cool ◽  
Frank Naets ◽  
Ward Rottiers ◽  
Wim Desmet
Keyword(s):  
Frequency Response ◽  
Cost Reduction ◽  
Frequency Response Function ◽  
Performance Metrics ◽  
Computational Cost ◽  
Order System ◽  
Model Parameters ◽  
Frequency Content ◽  
Space Frequency ◽  
Set Up

This research focusses on the computational cost reduction of frequency domain simulations in many-query applications with varying model parameters. These analyses are often encountered during the design of mechanical structures, where frequency response function (FRF) amplitudes are still one of the key performance metrics to be considered. Moreover, often inputs (number and frequency content) can vary broadly, which makes it all the more challenging to set up the reduced model.

scholarly journals Static and Dynamic Characterization and Control of a High-Performance Electro-Hydraulic Actuator

Actuators ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 46
Author(s):  
Govind N. Sahu ◽  
Suyash Singh ◽  
Aditya Singh ◽  
Mohit Law
Keyword(s):  
Machine Tool ◽  
High Performance ◽  
Closed Loop ◽  
Dynamic Models ◽  
Static Model ◽  
Dynamical Model ◽  
Model Parameters ◽  
Closed Loop Control ◽  
Hydraulic Actuator ◽  
Loop Control

This paper characterizes the static, dynamic, and controlled behavior of a high-performance electro-hydraulic actuator to assess its suitability for use in evaluating machine tool behavior. The actuator consists of a double-acting piston and cylinder arrangement controlled by a servo valve and a separate rear chamber controlled by a separate valve, designed to work in conjunction to generate static forces of up to 7000 N that can be superposed with dynamic forces of up to ±1500 N. This superposition of periodic forces with a non-zero mean makes the actuator capable of applying realistic loading conditions like those experienced by machines during cutting processes. To characterize the performance of this actuator, linearized static and dynamic models are described. Since experiments with the actuator exhibit nonlinear characteristics, the linearized static model is expanded to include the influence of nonlinearities due to flow, leakages, saturations, and due to friction and hysteresis. Since all major nonlinearities are accounted for in the expanded static model, the dynamical model remains linear. Unknown static and dynamical model parameters are calibrated from experiments, and the updated models are observed to capture experimentally observed behavior very well. Validated models are used to tune the proportional and integral gains for the closed-loop control strategy, and the model-based tuning in turn guides appropriate closed-loop control of the actuator to increase its bandwidth to 200 Hz. The statically and dynamically characterized actuator can aid machine tool structural testing. Moreover, the validated models can instruct the design and development of other higher-performance electro-hydraulic actuators, guide the conversion of the actuator into a damper, and also test other advanced control strategies to further improve actuator performance.

scholarly journals Non-linear frequency response of non-isothermal adsorption controlled by micropore diffusion with variable diffusivity

2000 ◽  
Vol 65 (12) ◽  
pp. 939-961 ◽  
Author(s):  
Menka Petkovska
Keyword(s):  
Frequency Response ◽  
Solid Phase ◽  
Second Order ◽  
Model Parameters ◽  
Sufficient Information ◽  
Isothermal Adsorption ◽  
Variable Diffusivity ◽  
Micropore Diffusion ◽  
Non Linear ◽  
Kinetic Mechanisms

The concept of higher order frequency response functions (FRFs) is used for the analysis of non-linear adsorption kinetics on a particle scale, for the case of non-isothermal micropore diffusion with variable diffusivity. Six series of FRFs are defined for the general non-isothermal case. A non-linerar mathematical model is postulated and the first and second order FRFs derived and simulated. A variable diffusivity influences the shapes of the second order FRFs relating the sorbate concentration in the solid phase and t he gas pressure significantly, but they still keep their characteristics which can be used for discrimination of this from other kinetic mechanisms. It is also shown that first and second order particle FRFs offter sufficient information for an easy and fast estimation of all model parameters, including those defining the system non-linearity.

Remote Concrete Spraying in Shafts and Tunnels With Closed Loop Control

1996 ◽  
Author(s):  
Liu Hongzhao ◽  
E. Appleton
Keyword(s):  
High Performance ◽  
Closed Loop ◽  
Transformation Method ◽  
Emission Angle ◽  
Impact Angle ◽  
Order System ◽  
Closed Loop Control ◽  
Loop Control ◽  
Loop Control System ◽  
Velocity Measuring

Abstract In this paper, a closed-loop control system for the remote concrete spraying in shafts and tunnels is presented. The design includes a velocity measuring element, a PID controller, and a DC servo-motor drive system which is used to control the relative velocity of the grout, emission velocity, emission angle, and rotation to impact angle. The mathematical model of this system has been established and its transfer function obtained by the Laplace Transformation method. A set of stability conditions for this fourth-order system has been developed by means of the modified Hurwitz criterion. These studies provide the possibility of creating high-performance remote concrete spraying machines that operate in shafts and tunnels and have directional spray capability.

Adaptive control of time-varying non-linear plants by speed-gradient algorithms

2019 ◽  
pp. 37-44 ◽  
Author(s):  
O. P. Tomchina ◽  
D. N. Polyakhov ◽  
O. I. Tokareva ◽  
A. L. Fradkov
Keyword(s):  
Adaptive Control ◽  
Adaptive Systems ◽  
Reference Model ◽  
Maximum Deviation ◽  
Model Parameters ◽  
Time Varying ◽  
System Solution ◽  
Non Linear ◽  
Initial Uncertainty ◽  
Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models*

2021 ◽  
Author(s):  
Marcello Pericoli ◽  
Marco Taboga
Keyword(s):  
Bayesian Estimation ◽  
Term Structure ◽  
Broad Class ◽  
Model Parameters ◽  
State Variables ◽  
Computationally Efficient ◽  
Macroeconomic Factors ◽  
No Arbitrage ◽  
Term Structure Models ◽  
Non Linear

Abstract We propose a general method for the Bayesian estimation of a very broad class of non-linear no-arbitrage term-structure models. The main innovation we introduce is a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree of accuracy. Once the pricing function is approximated, the posterior distribution of model parameters and unobservable state variables can be estimated by standard Markov Chain Monte Carlo methods. As an illustrative example, we apply the proposed techniques to the estimation of a shadow-rate model with a time-varying lower bound and unspanned macroeconomic factors.

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