scholarly journals Nonlinear Dynamic Model-Based Adaptive Control of a Solenoid-Valve System

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
DongBin Lee ◽  
Peiman Naseradinmousavi ◽  
C. Nataraj
Keyword(s):  
Adaptive Control ◽  
Dynamic Model ◽  
Nonlinear Model ◽  
Nonlinear Dynamic ◽  
Solenoid Valve ◽  
Projection Algorithm ◽  
Control Input ◽  
Control Approach ◽  
Valve System ◽  
Model Based

In this paper, a nonlinear model-based adaptive control approach is proposed for a solenoid-valve system. The challenge is that solenoids and butterfly valves have uncertainties in multiple parameters in the nonlinear model; various kinds of physical appearance such as size and stroke, dynamic parameters including inertia, damping, and torque coefficients, and operational parameters especially, pipe diameters and flow velocities. These uncertainties are making the system not only difficult to adjust to the environment, but also further complicated to develop the appropriate control approach for meeting the system objectives. The main contribution of this research is the application of adaptive control theory and Lyapunov-type stability approach to design a controller for a dynamic model of the solenoid-valve system in the presence of those uncertainties. The control objectives such as set-point regulation, parameter compensation, and stability are supposed to be simultaneously accomplished. The error signals are first formulated based on the nonlinear dynamic models and then the control input is developed using the Lyapunov stability-type analysis to obtain the error bounded while overcoming the uncertainties. The parameter groups are updated by adaptation laws using a projection algorithm. Numerical simulation results are shown to demonstrate good performance of the proposed nonlinear model-based adaptive approach and to compare the performance of the same solenoid-valve system with a non-adaptive method as well.

Model-Based Adaptive Control for a Solenoid-Valve System

2010 ◽  
Author(s):  
C. ‘Nat’ Nataraj ◽  
DongBin Lee
Keyword(s):  
Adaptive Control ◽  
Dynamic Models ◽  
Solenoid Valve ◽  
Projection Algorithm ◽  
Electric Signal ◽  
Control Input ◽  
Butterfly Valve ◽  
Set Point ◽  
Valve System ◽  
Model Based

In this paper, a model-based control algorithm is developed for a solenoid-valve system. The electric-driven machinery system and its sophisticated control give high levels of automation on huge systems such as ships and submarines. It is known that the characteristics between the force versus displacement and fluid dynamics are strongly nonlinear. The system has uncertainties in multiple parameters in the model, which make the system difficult to adjust to the environment and consequently require adaptation for sustainability and capability. The novelty of this research is that the uncertain nonlinear dynamics of the solenoid-valve system is simplified by formulating in dimensionless form. The non-dimensional control approach of the unknown bounded parameters which is approximately twenty parameter groups used in general adaptive control of the solenoid-butterfly valve system dramatically reduced to just four lumped parameter groups. The control objective is to the set-point of the solenoid-valve and accordingly control the angle position of the butterfly valve in spite of the complications presented by the uncertainties in the dynamic model. The estimated parameters are updated by the adaptation laws using the projection algorithm. After combining the translational and rotational dynamic models, the control input is designed by substituting the electric signal such as current from the model of electromagnetic force. Error signals of the trajectory tracking are developed for the solenoid-valve system. A closed-loop stable controller is designed based on the above error dynamics of the nonlinear solenoid-valve system utilizing Lyapunov-type stability which yields a stable result while obtaining the set-point objective.

Nonlinear Model-Based Adaptive Control of a Solenoid-Valve System

2010 ◽  
Author(s):  
DongBin Lee ◽  
C. Nataraj ◽  
Peiman Naseradinmousavi
Keyword(s):  
Dynamic Models ◽  
Controller Design ◽  
Current Source ◽  
Solenoid Valve ◽  
Projection Algorithm ◽  
Control Input ◽  
Valve System ◽  
Multiple Parameters ◽  
Model Based ◽  
Control Objective

In this paper, a model-based control algorithm is developed for a solenoid-valve system. Solenoids and butterfly valves have uncertainties in multiple parameters in the model, which make the system difficult to adjust to the environment. These are further complicated by combining the solenoid and butterfly dynamic models. The control objective of a solenoid-valve system is to position the angle of the butterfly valve through the electric-driven actuator in spite of the complexity presented by uncertainties. The novelty of the controller design is that the current source of the solenoid valve from the model of the electromagnetic force is substituted for the control input in order to reach the set-point of the butterfly disk based on the error signals, overcoming the uncertainties represented by lumped parameters groups, and a stable controller is designed via the Lyapunov-based approach for the stability of the system and obtaining the control objective. The parameter groups are updated by adaptation laws using a projection algorithm. Numerical simulation is shown to demonstrate good performance of the proposed approach.

Dynamic Simulation of Large Flow Solenoid Valve

2016 ◽  
Author(s):  
Z. Liu ◽  
X. Han ◽  
Y. F. Liu
Keyword(s):  
Dynamic Model ◽  
Dynamic Simulation ◽  
Dynamic Characteristics ◽  
Nonlinear Dynamic ◽  
Structural Parameters ◽  
Solenoid Valve ◽  
Simulation Software ◽  
Experimental Results ◽  
Nonlinear Dynamic Model ◽  
Large Flow

A nonlinear dynamic model of a large flow solenoid is presented with the multi-physics dynamic simulation software called SimulationX. Validation is performed by comparing the experimental results with the simulated ones. The dynamic characteristics of the large flow solenoid valve are analyzed. Different structural parameters are modified in this research and the diameter of the orifice is proved to be one of the most important parameters which influences the pressure response most.

Nonlinear Adaptive Engine Speed Control Using an Instrumental Variables Approach and a Truncated Volterra Series

2005 ◽  
Author(s):  
Jonathan W. Anders ◽  
Matthew A. Franchek
Keyword(s):  
Adaptive Control ◽  
Nonlinear Model ◽  
Instrumental Variable ◽  
Engine Speed ◽  
Volterra Series ◽  
Combustion Engine ◽  
Variable Parameter ◽  
Model Based ◽  
Variable Approach ◽  
Instrumental Variables Approach

An instrumental variable approach to nonlinear model-based adaptive control of engine speed is investigated and implemented on a spark ignition internal combustion engine. A four-step version of the instrumental variable parameter estimation algorithm is used to identify a bias-free and noise tolerant model of the engine dynamics between the by-pass air valve voltage and engine speed. The parametric model representing the engine dynamics is a truncated Volterra series with a time delay. Model-based adaptive control is accomplished through a partitioned inversion of the engine model which is minimum phase and OL stable. The desired closed loop throttle response and disturbance rejection dynamics are introduced via a two-degree-of-freedom feedback control structure. Performance of the nonlinear model-based adaptive control algorithm is verified experimentally.

scholarly journals Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control

2017 ◽  
Author(s):  
Carl R. Shapiro ◽  
Johan Meyers ◽  
Charles Meneveau ◽  
Dennice F. Gayme
Keyword(s):  
Dynamic Model ◽  
Wind Farm ◽  
Wind Farms ◽  
Static Model ◽  
Receding Horizon Control ◽  
Frequency Regulation ◽  
Control Approach ◽  
Model Based ◽  
Model Control ◽  
Wake Model

Abstract. We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, "RegA'" and "RegD", which are used by PJM, an independent system operator in the Eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation. Our results demonstrate that the dynamic-model controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower time scales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals.

scholarly journals Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control

2018 ◽  
Vol 3 (1) ◽  
pp. 11-24 ◽  
Author(s):  
Carl R. Shapiro ◽  
Johan Meyers ◽  
Charles Meneveau ◽  
Dennice F. Gayme
Keyword(s):  
Dynamic Model ◽  
Wind Farm ◽  
Wind Farms ◽  
Static Model ◽  
Receding Horizon Control ◽  
Frequency Regulation ◽  
Control Approach ◽  
Model Based ◽  
Model Control ◽  
Wake Model

Abstract. This paper is an extended version of our paper presented at the 2016 TORQUE conference (Shapiro et al., 2016). We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large-eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, “RegA” and “RegD”, which are used by PJM, an independent system operator in the eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation services or markets. Our results demonstrate that the dynamic-model-controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower timescales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals.

Nonlinear Model-Based Control of Pulse Width Modulated Pneumatic Servo Systems

2005 ◽  
Vol 128 (3) ◽  
pp. 663-669 ◽  
Author(s):  
Xiangrong Shen ◽  
Jianlong Zhang ◽  
Eric J. Barth ◽  
Michael Goldfarb
Keyword(s):  
Canonical Form ◽  
Nonlinear Model ◽  
Pulse Width ◽  
Sliding Mode ◽  
Control Input ◽  
Model Based Control ◽  
Pulse Width Modulated ◽  
Time Dynamics ◽  
Model Based ◽  
Actuation System

This paper presents a control methodology that enables nonlinear model-based control of pulse width modulated (PWM) pneumatic servo actuators. An averaging approach is developed to describe the equivalent continuous-time dynamics of a PWM controlled nonlinear system, which renders the system, originally discontinuous and possibly nonaffine in the input, into an equivalent system that is both continuous and affine in control input (i.e., transforms the system to nonlinear control canonical form). This approach is applied to a pneumatic actuator controlled by a pair of three-way solenoid actuated valves. The pneumatic actuation system is transformed into its averaged equivalent control canonical form, and a sliding mode controller is developed based on the resulting model. The controller is implemented on an experimental system, and the effectiveness of the proposed approach validated by experimental trajectory tracking.

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