Dead Time Model Research Articles

A new dead-time determination method for gamma-ray detectors using attenuation law

This study presents a new dead-time measurement method using the gamma attenuation law and generalized dead-time models for nuclear gamma-ray detectors. The dead-time of the NaI(Tl) detection system was obtained to validate the new dead-time determination method using very thin lead and polyethylene absorbers. Non-paralyzing dead-time was found to be 8.39 μs, and paralyzing dead-time was found to be 8.35 μs using lead absorber for NaI(Tl) scintillator detection system. These dead-time values are consistent with the previously reported dead-time values for scintillator detection systems. The gamma build-up factor's contribution to the dead-time was neglected because a very thin material was used.

Design of delayed PID‐type controllers for high‐order recycling systems with time delays using model reduction

AbstractIn even the simplest recycling system with a first‐order plus dead time model for the direct and recycling paths, the characteristic equation for the open‐loop transfer function contains an infinite number of poles. This is due to the presence of time delays in the internal dynamics. The task of designing a controller is therefore challenging from the perspective of control. This paper considers the problem of stabilising a high‐order delayed recycling system (with a possible unstable direct path) through the use of a reduced model in conjunction with a new PID (proportional‐integral‐derivative)‐type delayed controller. We state the condition under which the stability of the closed‐loop system is guaranteed and determine the sets of stabilising control parameters. The performance of our proposed strategy is illustrated using several numerical simulations of industrial processes, including an industrial quench column, two continuous stirred tank reactor systems with recycling and a reactor–separator process.

Design and Implementation of GSO Based PI Controller for Non Linear Spherical Tank System

From literature point of view process parameter control for non linear process found to be issue in process control industries. The main dilemma lies on managing liquid level in globular tank which is non linear in nature owing to its area disparity in cross section consequent to the change in shape. System identification is made with black box model which is nonlinear and approximated to first order plus dead time model using the worst case model parameter criterion. Group Search Optimization based Proportional Integral controller is implemented to control the non linear system. The real time work is implemented in MATLAB using VMAT-01 module. The servo and regulatory responses of GSO based proportional integral controller intended for different operating region is noted and results are compared with the algorithms such as Big Bang - Big Crunch optimization, Particle swarm optimization and Bacterial Foraging optimization . The most admirable controlling method is determined based on indices such as reduced overshoot, better set point tracking, disturbance rejection , lower performance indices, faster settling time and rise time.

Pole‐zero assignment in model predictive control, using analytical tuning approach

AbstractThis paper proposes a new analytical tuning strategy for Model Predictive Control (MPC). In the proposed approach, MPC tuning problem is restated as a pole‐zero placement problem. New analytically tuning equations are given and a deep study on the places of poles and zeros of the closed‐loop system is performed. It is known that, appropriate zero placement can improve the robust stability of the closed‐loop system, so the proposed tuning strategy can be applicable. In MPC tuning strategies, analytical equations are very interesting and useful. To achieve analytical equations, First Order plus Dead Time models are used in this work. These models with adequate accuracy can describe many industrial processes. With simulation studies, the effectiveness of the proposed pole‐zero assignment strategy is indicated.

Dead time corrections for Bonner sphere measurements of secondary neutrons at a proton therapy facility

Radiation therapy with proton beams allows the deposition of high doses to the tumour while minimising dose to the surrounding tissue. During such treatment, the patient is also exposed to secondary radiation which produces an out-of-field dose that affects healthy tissue. The largest contribution to this out-of-field dose comes from neutron radiation; therefore, it is of interest to fully characterise the neutron field in the therapy room with measurements. This is usually done with Bonner sphere spectrometers using active detectors, typically 3He-filled proportional counters, as central thermal neutron sensors. Under the experimental conditions encountered in proton therapy facilities, a proper analysis of the measurements is impossible unless dead time corrections are implemented. In this paper, we present a method using a paralysable dead time model for carrying out such corrections for Bonner sphere measurements with 3He-filled proportional counters and apply it to data taken at the University Proton Therapy Dresden (UPTD) facility in double scattering mode. The neutron events were recorded with time stamps and, based on this time-resolved data, the measured neutron rate distribution was sampled. Since the neutron flux is proportional to the proton flux, the integral neutron flux is directly related to the proton dose. Hence, we were able to estimate the detector dead time from the measured rate distributions recorded for a set of measurements with different proton dose rates. Experimental measurements with different intensities of the proton field show that the corrections are in agreement within 0.5% for measured signal rates smaller than 15 × 103 counts per second and do not exceed 1% at 25 × 103 counts per second.

Observation probability estimation of dead-time models using Monte Carlo simulations

Observation probability estimation of dead-time models using Monte Carlo simulations

A Set of Active Disturbance Rejection Controllers Based on Integrator Plus Dead-Time Models

The paper develops and investigates a novel set of constrained-output robust controllers with selectable response smoothing degree designed for an integrator-plus-dead-time (IPDT) plant model. The input-output response of the IPDT system is internally approximated by several time-delayed, possibly higher-order plant models of increasing complexity. Since they all contain a single integrator, the presented approach can be considered as a generalization of active disturbance rejection control (ADRC). Due to the input/output model used, the controller commissioning can be based on a simplified process modeling, similar to the one proposed by Ziegler and Nichols. This allows it to be compared with several alternative controllers commonly used in practice. Its main advantage is simplicity, since it uses only two identified process parameters, even when dealing with more complex systems with distributed parameters. The proposed set of controllers with increasing complexity includes the stabilizing proportional (P), proportional-derivative (PD), or proportional-derivative-acceleration (PDA) controllers. These controllers can be complemented by extended state observers (ESO) for the reconstruction of all required state variables and non-measurable input disturbances, which also cover imperfections of a simplified plant modeling. A holistic performance evaluation on a laboratory heat transfer plant shows interesting results from the point of view of the optimal least sensitive solution with smooth input and output.

Model predictive control of a miniaturized linear single-piston cryocooler

Remote Sensing Satellites use IR (Infra-Red) detectors for imaging in 1 um to 15 um bands. Most of these detectors are operated at cryogenic temperatures to extract the low-level signal from the background noise. Stirling cycle based miniature active linear cryocoolers are now being widely used for cooling these IR detectors to cryogenic temperatures. The Cryocooler Control Electronics (CCE) used for driving the cryocoolers, often uses a proportional-Integral-Derivative (PID) controller for controlling the cold tip temperature. Besides, the CCE for most space-borne missions uses a Feed-Forward (FF) control to reduce the vibration export coming from the movement of compressor pistons. The stringent cold-tip temperature stability and vibration control requirements pose a challenge to traditional cryocooler controllers, motivating to investigate and design more appropriate control structure and well-tuned well-performing controllers. This paper presents a novel scheme of simultaneous temperature and vibration control for a single-piston linear cryocooler based on an advanced Model Predictive Control (MPC) algorithm using multivariable (SIMO/MIMO) model of a miniature linear cryocooler. The MPC is one of the most popular advanced control algorithm which uses mathematical model of the underlying system or plant to predict the future response i.e. predicts future errors (in controlled variables) and uses constrained optimization to compute as decision variables a set of control actions (or manipulated variables) to minimize certain error-norm of controlled variables for specified horizon in future optimally respecting specified operational constraints. Because of its inherent capabilities to predict future errors using the multivariable model, and systematic handling of operational constraints, the proposed approach can provide better performance compared to existing cryocooler control approaches. Data-driven First Order Plus Dead Time (FOPDT) model of cryocooler has been developed and a low-cost speaker based actuator has been used for controlling the cryocooler vibration export. The paper presents the comparisons of simulated and measured control performance obtained using PI (SIMO case), PI + FF Control (MIMO case) and proposed MPC schemes (SIMO and MIMO cases) for the temperature and vibration control of a single-piston Stirling cryocooler. Significant improvement in the controller performance parameters such as Integral Absolute Error (ISE) and Integral Square Error (ISE) has been achieved with the MPC scheme. Besides, MPC is found to demonstrate significantly better performance in terms of satisfying the specific operational constraints, e.g. vibrations limits.

Dead time model for X-ray photon counting detectors with retrigger capability

We developed an analytical dead time model able to correctly describe the behavior of X-ray photon counting detectors equipped with retrigger capability, which allows the system to work in non-paralyzable mode by counting the time-over-threshold of piled-up signals in multiples of a predefined and selectable retrigger time. Having an analytical form relating the true interaction rate to the recorded interaction rate will help improving count rate correction routines with respect to the existing techniques, based so far on look-up tables generated through Monte Carlo simulations. The proposed model was validated through comparison with dedicated Monte Carlo simulations. We then used the derived formula as fitting function on a set of more realistic, arbitrary-shaped (non-rectangle) signals, exploring the limits of its validity and proposing an empirical interpretation of the fitting parameters when necessary.

Comparison of Model Predictive Controller and Neural Network Controller on Nonconventional Distillation Demethanizer/Deethanizer Rectifier/Column System

Nonconventional distillation demethanizer/deethanizer rectifier/column offers an economic advantage compared to conventional configurations by using sidestream from second column to remove the use of reboiler. However, this configuration brings a complex system that needs attention in its process control to ensure its operability. This work explores the use of neural network model predictive control (NNMPC) for this system. Aspen HYSYS was used to simulate the process, generate input-output data to develop the plant model and to conduct performance tests. MATLAB was used to conduct model identification, design the MPC and implement the multivariable control action. Sufficient time series data, where reflux valve positions and distillate compositions from each column act as input and output respectively, can be obtained from simulation and then utilized to train a nonlinear autoregressive exogenous (NARX) neural network which will be used as a predictive model. Model predictive Control based on this neural network model is designed to control distillate compositions for each column by the changes of reflux valve positions for each column as control signal. Least square algorithm from MATLAB function wass employed to optimize the cost function. A comparison has been made between NNMPC and conventional MPC configurations with first order plus dead time (FOPDT) model to test the performance of the controller based on disturbance rejection and set-point tracking test. Quantitative calculation was done using integral absolute error (IAE) with trapezoidal rule used as numerical integral method. NNMPC shows better performance than MPC with FOPDT model in set-point tracking test. However, NNMPC has a disadvantage on the cost function calculation algorithm, which did not account for the difference between plant and model value thus cause the MPC with FOPDT model to give better performance on disturbance rejection. Bias addition on NNMPC cost function algorithm made the controller has better responses to disturbance rejection compared to MPC.

Analytical tuning rules for Reduced-order Active Disturbance Rejection Control with FOPDT models through Multi-Objective optimization and multi-criteria decision-making

Active Disturbance Rejection Control (ADRC) emerged as a promising control solution in various engineering domains. However, increased ADRC order makes it difficult to implement and tune in practice. On the other hand, Reduced-order ADRC (RADRC) structure solves this issue with the appropriate tuning of its parameters to achieve the desired performance. This paper aims to develop analytical tuning rules for RADRC for processes approximated as First-order plus dead-time models (FOPDT). These rules meet the conflicting goals of tracking and disturbance rejection restricted by robustness specification. The tuning rules are derived based on a multi-stage approach. In the first stage, the tuning problem is formulated as a multi-objective optimization problem with appropriate constraints. A Multi-objective Quasi-Oppositional Rao-1 (MOQO-Rao-1) Algorithm solves the optimization problem to produce a collection of Pareto-optimal solutions (alternatives) in the second stage. In the third stage, using the Best-Worst based PROMETHEE method, the best one is chosen among the available options. Finally, using linear regression, analytical tuning rules are developed. Separate tuning rules are proposed for lag-dominated and dead-time dominated cases. Simulation experiments on benchmark industrial processes are performed, and the findings assess the efficacy of the suggested tuning rules relative to the methods recently published. The proposed tuning rules are experimentally validated to assess their applicability in the practical scenario. Besides, the closed-loop system’s stability with the suggested tuning rules is confirmed by the small-gain theorem and the dual-locus process.

Pulse shape analysis of signals from SiPM-based CsI(Tl) detectors for low-energy protons: Saturation correction and particle identification

CsI(Tl) scintillation detectors based on a silicon photomultiplier (SiPM) were tested for low-energy proton detection. Pulse shape analysis of the SiPM signals with a transimpedance amplifier was conducted to investigate the saturation effect due to the recovery time of a pixel and to evaluate particle identification capability. To recover energy linearity, a saturation correction method based on a non-paralyzable dead time model was proposed. The setup using the SiPM with a 25 μm pixel pitch well separated protons and deuterons at energies from 3 to 12 MeV. Additionally, a readout circuit without an amplifier was tested to investigate another type of saturation due to the voltage drop effect.

Linear Algebra Controller Design Based on the Integral of Desired Closed-Loop Behavior: Application to Regulation and Trajectory Tracking in a Typical Chemical Process

This work presents a novel control technique that combines linear algebra-based controller (LABC) methodology with sliding surface concepts. An LABC is developed from a first-order plus dead time model of the process, which is improved to work under uncertainties by the use of sliding surface concepts. Two different strategies are proposed to reject constant and variable uncertainties. The result is two linear controllers, which are tuned using four parameters at most. Results of the control of two level tanks connected in series, a mixing tank with variable dead time, and a laboratory batch reactor using this novel technique are presented, including experimental and simulated results. The efficiency of the proposed controller is tested under nominal operating conditions and under parametric uncertainty and persistent process disturbances. Proof of convergence to zero of tracking errors is analyzed and included in this article.

Backwards extrapolation activation diagnostics and their dynamic range for pulsed neutron source measurements

Activation materials implanted within radiation detectors can be used to measure pulsed neutron fields. This work develops an instrument concept with the aim to maximise sensitivity to pulsed fusion neutron fields and, using a data-rejection algorithm combined with backwards extrapolation, enable neutron fluence estimates to be made over a large dynamic range. Through high-fidelity modelling of residual temporal emissions, and a parameterised approach, we study the sensitivity to neutrons of a plastic scintillator–Ag foil layer detector concept. For an optimal design we apply paralysable and non-paralysable deadtime models to the predicted response to D–D fusion neutron fields at various neutron field intensities. In high neutron fluence irradiation scenarios, where deadtime effects are strongly evident, we use our approach to make estimates of the fluence from instrument response data. We discuss the practical applications of such diagnostics used for plasma focus (PF) fusion experiments, such as at the PF-1000U facility in IPPLM, Poland, inertial confinement fusion and pulsed tokamak experiments, for example at MAST-U, where such diagnostics could complement fission counter-based neutron diagnostics in the future. Finally, we show that the calibration of such detection systems may be achieved using relatively low emission rate, steady state neutron sources, with calibration factors that are straightforward to apply to pulsed neutron field measurements.

Generalization of the FOPDT Model for Identification and Control Purposes

This paper proposes a theoretical framework for generalization of the well established first order plus dead time (FOPDT) model for linear systems. The FOPDT model has been broadly used in practice to capture essential dynamic response of real life processes for the purpose of control design systems. Recently, the model has been revisited towards a generalization of its orders, i.e., non-integer Laplace order and fractional order delay. This paper investigates the stability margins as they vary with each generalization step. The relevance of this generalization has great implications in both the identification of dynamic processes as well as in the controller parameter design of dynamic feedback closed loops. The discussion section addresses in detail each of this aspect and points the reader towards the potential unlocked by this contribution.

Optimal design of discrete-time fractional-order PID controller for idle speed control of an IC engine

This paper aims at proposing a discrete-time fractional-order PID (FOPID) controller, which can stabilise the variation of the idle speed of an internal combustion engine due to the occurrence of the external load disturbance. The nonlinear idle speed dynamics is linearised to be approximated by a first order plus dead time (FOPDT) model so that the FOPID controller can be initialised by a Ziegler-Nichols type tuning rule. The initialised FOPID controller can stabilise the linearised model, but it may lose its control capability in nonlinear idle speed dynamics. Therefore, an optimisation problem is solved through genetic algorithm (GA) to minimise a cost function within a small region around the FOPID's initial parameters. The optimal discrete-time FOPID controller are compared to a conventional discrete-time PID controller. The simulation study reveals that the optimal discrete-time FOPID controller secures an excellent control performance to the nonlinear idle speed model.

Optimal design of discrete-time fractional-order PID controller for idle speed control of an IC engine

This paper aims at proposing a discrete-time fractional-order PID (FOPID) controller, which can stabilise the variation of the idle speed of an internal combustion engine due to the occurrence of the external load disturbance. The nonlinear idle speed dynamics is linearised to be approximated by a first order plus dead time (FOPDT) model so that the FOPID controller can be initialised by a Ziegler-Nichols type tuning rule. The initialised FOPID controller can stabilise the linearised model, but it may lose its control capability in nonlinear idle speed dynamics. Therefore, an optimisation problem is solved through genetic algorithm (GA) to minimise a cost function within a small region around the FOPID's initial parameters. The optimal discrete-time FOPID controller are compared to a conventional discrete-time PID controller. The simulation study reveals that the optimal discrete-time FOPID controller secures an excellent control performance to the nonlinear idle speed model.

Pre‐computed GPC of a DC–DC buck converter

This study presents the control mechanism of a DC-DC buck converter using generalised predictive control by approximating the plant model to a stable first-order plus dead time (FOPDT) model. As most of the higher order plant dynamics can be represented by an FOPDT model, this study is limited only to a stable FOPDT dynamics system. In this work, a relation between FOPDT model parameters and weights of the cost function is derived. The controller design procedure is then verified by implementing voltage mode control of the DC-DC buck converter in the case of inactive constraints. Jury's stability criteria are used to analyse the stability of the closed-loop system. The implemented algorithm is then verified using simulation in MATLAB/Simulink, as well as the hardware implementation of the pre-computed control algorithm.

Paralyzable and non-paralyzable dead-time corrections for the neutron detectors of the KUCA facility driven by external neutron sources

ABSTRACT This study examines dead-time corrections for the neutron detectors of the Kyoto University Critical Assembly (KUCA) driven by a stationary or pulsed external neutron sources. For the stationary (californium) external neutron source, the MCNP simulations producing the detector timestamps and the MATLAB scripts correcting for the dead-time effect have been validated with analytical formulae from literature. For the pulsed external neutron source (produced by a proton accelerator), the experimental detector timestamps have been corrected for the dead-time effect using the aforementioned MATLAB scripts utilizing the backward extrapolation method and the paralyzable or non-paralyzable dead-time model. Then, the keff obtained from the dead-time corrected timestamps has been corrected for the detector position and type. Finally, the corrected experimental keff has been compared with the one obtained from MCNP criticality simulations.

Dead-time correction for spectroscopic photon-counting pixel detectors.

Modern photon-counting pixel detectors have enabled a revolution in applications at synchrotron light sources and beyond in the last decade. One of the limitations of the current detectors is their reduced counting linearity or even paralysis at high counting rates, due to dead-time which results in photon pile-up. Existing dead-time and pile-up models fail to reproduce the complexity of dead-time effects on photon-counting, resulting in empirical calibrations for particular detectors at best, imprecise linearization methods, or no linearization. This problem will increase in the future as many synchrotron light sources plan significant brilliance upgrades and free-electron lasers plan moving to a quasi-continuous operation mode. Presented here are the first models that use the actual behavior of the analog pre-amplifiers in spectroscopic photon-counting pixel detectors with constant current discharge (e.g. the Medipix and CPix families of detectors) to deduce more accurate analytical models and optimal linearization methods. In particular, for detectors with at least two counters per pixel, the need for calibration, or previous knowledge of the detector and beam parameters (dead-time, integration time, large sets of synchrotron filling patterns), is completely eliminated. This is summarized in several models of increasing complexity and accuracy. Finally, a general empirical approach is presented, applicable to any particular cases where the analytical approach is not sufficiently precise.