A valve stiction tolerant formulation of MPC for industrial processes

This paper presents three different formulations of MPC to face static friction in control valves for industrial processes. A pure linear formulation, a stiction embedding structure, and a stiction inversion controller are designed. The controllers are derived for SISO systems with linear process dynamics, where valve stiction is the only nonlinearity present in the control loop. A novel smoothed stiction model is introduced to improve and fasten the dynamic optimization module of stiction embedding MPC. A stiction compensation method is revised and used as a warm-start to build a suitable trajectory for the predictive controller. The different MPC formulations are tested and compared on some simulation examples

Model predictive control design for multivariable processes in the presence of valve stiction

This paper presents different formulations of Model Predictive Control (MPC) to handle static friction in control valves for industrial processes. A fully unaware formulation, a stiction embedding structure, and a stiction inversion controller are considered. These controllers are applied to multivariable systems, with linear and nonlinear process dynamics. A semiphysical model is used for valve stiction dynamics and the corresponding inverse model is derived and used within the stiction inversion controller. The two-move stiction compensation method is revised and used as warm-start to build a feasible trajectory for the MPC optimal control problem. Some appropriate choices of objective functions and constraints are used with the aim of improving performance in set-points tracking. The different MPC formulations are reviewed, compared, and tested on several simulation examples. Stiction embedding MPC proves to guarantee good performance in set-points tracking and also stiction compensation, at the expense of a lower robustness with respect to other two formulations

MODEL PREDICTIVE CONTROL DESIGN FOR LINEAR MULTIVARIABLE SYSTEMS UNDER CONTROL VALVE STICTION

Product quality and production costs are dependent on optimal control of the process. Product variability and oscillation of the process would indicate poor control. Such is the consequence of nonlinearity in the response of the control valves towards controller instructions. The most common cause of nonlinearities is static friction (stiction) in the mechanical assembly of the valve. The ability of a hybrid model predictive control (MPC) formulation to compensate for stiction was to be tested. The formulation was previously shown to be able to compensate for backlash by solving a mixed integer quadratic programming (MIQP) problem. Simulation studies were conducted using a model of a paper machine headbox model in Simulink. The hybrid MPC formulation was updated to run on current software versions and the Choudhury stiction model was integrated into the system. Due to errors in the simulation, the ability of hybrid MPC to compensate for stiction finally could not be determined. The errors encountered are documented as well as recommendations to overcome the shortcomings of the simulation

Fault simulator for proportional solenoid valves

Proportional Solenoid Valves (PSV) have been successfully used in the hydraulic industry for many years due to the benefits associated with higher accuracy compared to on/off solenoid valves, and the robustness and cost compared to servo valves. Because the PSV plays an important role in the performance of a hydraulic system, a technique commonly referred to as Condition Monitoring Scheme (CMS) has been used extensively to monitor the progress of faults in the PSV. But before any CMS can be implemented on a system, it needs to be thoroughly tested for its reliability of fault detection since, a failure of the CMS to detect any potential fault can be economically disastrous, and dangerous in terms of the safety of personnel. The motivation of this research was to develop a fault simulator which could reliably and repeatedly induce user defined faults in the PSV and thereby aid in testing the efficacy of the CMS for monitoring such simulated faults.Industry research has revealed that the most common mode of failure in spool valves is an increase in the friction between the spool and valve, due to wear, contamination and dirt, which renders the valve inoperable. In this research, a non-destructive fault simulator was developed which induced artificial friction faults in the PSV. The PSV consisted of two solenoids on the opposite sides of the valve spool by virtue of which, bi-directional position control could be achieved. The PSV with the spool and one of the solenoids was used as the system in which the faults were simulated, and the second solenoid was used an a fault simulator for inducing the desired friction characteristics in the system. The friction characteristics induced in the valve were similar to those in the classical friction curve, i.e., stiction at low velocities and Coulomb and viscous friction at higher velocities. By employing a closed loop position control scheme, one of the solenoids was used to generate a linearly increasing velocity profile by virtue of which the desired friction characteristics could be induced in different velocity regimes. The other solenoid was used to generate the desired friction force. A closed loop force control strategy, which used the feedback from a force transducer, allowed for the accurate control of the friction characteristics. stiction was induced at low velocities by passing the required current in both the solenoids that resulted in no net force on the valve spool. Due to the absence of any driving force the spool was stalled at the desired location, thus achieving the same effect of stiction at low velocities. The coulomb and viscous friction were induced at higher velocities by employing an algorithm which was a function of the spool velocity. Different magnitudes of static, coulomb and viscous friction were induced to achieve the friction characteristics represented by the classical friction curve. Since the change in force characteristics of the valve results in a corresponding change in the current drawn by the position control solenoid, a rudimentary CMS for monitoring the current characteristics is presented. Based on the experimental results and validation using the CMS it was concluded that the fault simulator was able to accurately produce the desired frictional loading on the valve spool and was able to do so with a high degree of repeatability. Proportional Solenoid Valves (PSV) have been successfully used in the hydraulic industry for many years due to the benefits associated with higher accuracy compared to on/off solenoid valves, and the robustness and cost compared to servo valves. Because the PSV plays an important role in the performance of a hydraulic system, a technique commonly referred to as Condition Monitoring Scheme (CMS) has been used extensively to monitor the progress of faults in the PSV. But before any CMS can be implemented on a system, it needs to be thoroughly tested for its reliability of fault detection since, a failure of the CMS to detect any potential fault can be economically disastrous, and dangerous in terms of the safety of personnel. The motivation of this research was to develop a fault simulator which could reliably and repeatedly induce user defined faults in the PSV and thereby aid in testing the efficacy of the CMS for monitoring such simulated faults. Industry research has revealed that the most common mode of failure in spool valves is an increase in the friction between the spool and valve, due to wear, contamination and dirt, which renders the valve inoperable. In this research, a non-destructive fault simulator was developed which induced artificial friction faults in the PSV. The PSV consisted of two solenoids on the opposite sides of the valve spool by virtue of which, bi-directional position control could be achieved.The PSV with the spool and one of the solenoids was used as the system in which the faults were simulated, and the second solenoid was used an a fault simulator for inducing the desired friction characteristics in the system. The friction characteristics induced in the valve were similar to those in the classical friction curve, i.e., stiction at low velocities and Coulomb and viscous friction at higher velocities. By employing a closed loop position control scheme, one of the solenoids was used to generate a linearly increasing velocity profile by virtue of which the desired friction characteristics could be induced in different velocity regimes. The other solenoid was used to generate the desired friction force. A closed loop force control strategy, which used the feedback from a force transducer, allowed for the accurate control of the friction characteristics. stiction was induced at low velocities by passing the required current in both the solenoids that resulted in no net force on the valve spool. Due to the absence of any driving force the spool was stalled at the desired location, thus achieving the same effect of stiction at low velocities. The coulomb and viscous friction were induced at higher velocities by employing an algorithm which was a function of the spool velocity. Different magnitudes of static, coulomb and viscous friction were induced to achieve the friction characteristics represented by the classical friction curve. Since the change in force characteristics of the valve results in a corresponding change in the current drawn by the position control solenoid, a rudimentary CMS for monitoring the current characteristics is presented. Based on the experimental results and validation using the CMS it was concluded that the fault simulator was able to accurately produce the desired frictional loading on the valve spool and was able to do so with a high degree of repeatability

MODEL PREDICTIVE CONTROL DESIGN FOR LINEAR MULTIVARIABLE SYSTEMS UNDER CONTROL VALVE STICTION

Product quality and production costs are dependent on optimal control of the process. Product variability and oscillation of the process would indicate poor control. Such is the consequence of nonlinearity in the response of the control valves towards controller instructions. The most common cause of nonlinearities is static friction (stiction) in the mechanical assembly of the valve. The ability of a hybrid model predictive control (MPC) formulation to compensate for stiction was to be tested. The formulation was previously shown to be able to compensate for backlash by solving a mixed integer quadratic programming (MIQP) problem. Simulation studies were conducted using a model of a paper machine headbox model in Simulink. The hybrid MPC formulation was updated to run on current software versions and the Choudhury stiction model was integrated into the system. Due to errors in the simulation, the ability of hybrid MPC to compensate for stiction finally could not be determined. The errors encountered are documented as well as recommendations to overcome the shortcomings of the simulation

Modeling of precision motion control systems: a relay feedback approach

Ph.DDOCTOR OF PHILOSOPH

Root cause isolation of propagated oscillations in process plants

Persistent whole-plant disturbances can have an especially large impact on product quality and running costs. There is thus a motivation for the automated detection of a plant-wide disturbance and for the isolation of its sources. Oscillations increase variability and can prevent a plant from operating close to optimal constraints. They can also camouflage other behaviour that may need attention such as upsets due to external disturbances. A large petrochemical plant may have a 1000 or more control loops and indicators, so a key requirement of an industrial control engineer is for an automated means to detect and isolate the root cause of these oscillations so that maintenance effort can be directed efficiently. The propagation model that is proposed is represented by a log-ratio plot, which is shown to be ‘bell’ shaped in most industrial situations. Theoretical and practical issues are addressed to derive guidelines for determining the cut-off frequencies of the ‘bell’ from data sets requiring little knowledge of the plant schematic and controller settings. The alternative method for isolation is based on the bispectrum and makes explicit use of this model representation. A comparison is then made with other techniques. These techniques include nonlinear time series analysis tools like Correlation dimension and maximal Lyapunov Exponent and a new interpretation of the Spectral ICA method, which is proposed to accommodate our revised understanding of harmonic propagation. Both simulated and real plant data are used to test the proposed approaches. Results demonstrate and compare their ability to detect and isolate the root cause of whole plant oscillations. Being based on higher order statistics (HOS), the bispectrum also provides a means to detect nonlinearity when oscillatory measurement records exist in process systems. Its comparison with previous HOS based nonlinearity detection method is made and the bispectrum-based is preferred