Showing papers by "Isabela Roxana Birs published in 2022"

A Review of Recent Developments in Autotuning Methods for Fractional-Order Controllers

Abstract: The scientific community has recently seen a fast-growing number of publications tackling the topic of fractional-order controllers in general, with a focus on the fractional order PID. Several versions of this controller have been proposed, including different tuning methods and implementation possibilities. Quite a few recent papers discuss the practical use of such controllers. However, the industrial acceptance of these controllers is still far from being reached. Autotuning methods for such fractional order PIDs could possibly make them more appealing to industrial applications, as well. In this paper, the current autotuning methods for fractional order PIDs are reviewed. The focus is on the most recent findings. A comparison between several autotuning approaches is considered for various types of processes. Numerical examples are given to highlight the practicality of the methods that could be extended to simple industrial processes.

Fractional-Order Control Strategy for Anesthesia–Hemodynamic Stabilization in Patients Undergoing Surgical Procedures

Abstract: Fractional calculus has been opening new doors in terms of better modeling and control of several phenomena and processes. Biomedical engineering has seen a lot of combined attention from clinicians, control engineers and researchers in their attempt to offer individualized treatment. A large number of medical procedures require anesthesia, which in turn requires a closely monitored and controlled level of hypnosis, analgesia and neuromuscular blockade, as well maintenance of hemodynamic variables in a safe range. Computer-controlled anesthesia has been given a tremendous amount of attention lately. Hemodynamic stabilization via computer-based control is also a hot topic. However, very few studies on automatic control of combined anesthesia–hemodynamic systems exist despite the fact that hemodynamics is strongly influenced by hypnotic drugs, while the depth of hypnosis is affected by drugs used in hemodynamic control. The very first multivariable fractional-order controller is developed in this paper for the combined anesthesia–hemodynamic system. Simulation studies on 24 patients show the effectiveness of the proposed approach.

Ergonomic and Economic Office Light Level Control

Abstract: Light regulation systems in industrial or office buildings play an important role in minimizing the use of fossil energy resources, while providing both economic and ergonomic optimal functionality. Although industrial buildings resolve the problem of interaction or disturbance mitigation by providing constant light levels exclusively from artificial sources, office landscapes may benefit from up to a 20% decrease in costs if mixed light sources are optimized properly. In this paper, we propose a theoretical framework based on model predictive control (MPC) to resolve a multi-system with strong dynamic interactions and multi-objective cost optimization. Centralized and distributed predictive control strategies are compared on various office landscaping structures and functionality conditions. Economic and ergonomic indexes are evaluated in a scaled laboratory setting.

Fractional-Order PI Controller Design Based on Reference–to–Disturbance Ratio

Abstract: The presence of disturbances in practical control engineering applications is unavoidable. At the same time, they drive the closed-loop system’s response away from the desired behavior. For this reason, the attenuation of disturbance effects is a primary goal of the control loop. Fractional-order controllers have now been researched intensively in terms of improving the closed-loop results and robustness of the control system, compared to the standard integer-order controllers. In this study, a novel tuning method for fractional-order controllers is developed. The tuning is based on improving the disturbance attenuation of periodic disturbances with an estimated frequency. For this, the reference–to–disturbance ratio is used as a quantitative measure of the control system’s ability to reject disturbances. Numerical examples are included to justify the approach, quantify the advantages and demonstrate the robustness. The simulation results provide for a validation of the proposed tuning method.

Impedance Spectroscopy Sensing Material Properties for Self-Tuning Ratio Control in Pharmaceutical Industry

Abstract: : Following the paradigm shift in the pharmaceutical industry from batch to continuous production, additional instrumentation and revision of control strategies to optimize material flow throughout the downstream processes are required. Tableting manufacturing is one of the most productive in terms of turnover and investment into new sensor technologies is an important decision-making step. This paper proposes a continuous solution to detect changes in material properties, and a control algorithm to aid in minimizing risk at the end-product line. Some of the sub-processes involved in tableting manufacturing perform changes in powder and liquid mixtures, granulation, density, therefore changing flow conditions of the raw material. Using impedance spectroscopy in a continuous sensing and monitoring context, it is possible to perform online identification of generalized (fractional) order parametric models where the coefficients are correlated to changes in material properties. The model parameters are then included in a self-tuning control gain used in ratio control as part of the local process control loop. The solution proposed here is easy to implement and poses a significant added value to the current state of art in pharmaceutical manufacturing technologies.

A low-order approximation method for fractional order PID controllers

Abstract: The control community recognizes the improved performance, stability and intrinsic robustness brought by fractional orders of differentiation and integration. However, the full potential of Fractional Order Proportional Integral Derivative (FOPID) controllers is yet to be grasped in the modern industrial setting. Mass adoption is hindered by implementation difficulties associated to fractional order terms. Available approximation methods usually obtain high order equivalent integer order transfer functions that could be difficult to implement. The present study introduces a novel frequency-domain approximation strategy based on non-linear least squares optimization routine. The result is an alternative approximation strategy that obtains an accurate frequency domain approximation with a reduced order transfer function. Validations are performed on various numerical examples, also highlighting the efficiency of the method for fractional orders greater than 1.

Optimal Fractional Order PID based on a Modified Ziegler-Nichols method

Abstract: Industry requires simple, yet efficient tuning methods for controllers. One of these tuning methodologies is the popular Ziegler-Nichols approach that requires little information regarding the process and has some pre-definite tuning rules. Although intensive research has been done in non-integer order controllers and their advantages have been demonstrated, their complexity and tedious tuning kept them away from industrial acceptance. In this manuscript, an existing Ziegler-Nichols method for fractional order controllers is modified to yield optimal parameters. The tuning rules and the optimization algorithm are simple, yet they lead to efficient fractional orders controllers. Simulation results are included to validate the proposed method.

A robust self-tuning PID-type control for time-varying process in the pharmaceutical industry

Abstract: In this work, we present a comparison between three PID-type controllers designed via different methods for a process with time-varying properties. Such a process is commonly encountered in the process industry, with prevalence in the chemical, food and pharmaceutical manufacturing industries. The controllers are varying in complexity from operator level (rule-based) to expert tuning (computer-aided design) and beyond state of art (generalized fractional-order control). Experimental tests indicate the feasibility of the controllers for variations in time constant with varying operation conditions originating from physical changes in the process. This is rather a common problem in practice and highly relevant for control engineering. Furthermore, an analysis of the system properties reveals the opportunity to operate in closed loop in a self-tuning manner, which avoids the necessity to re-design the controller parameter values.

Uncertainty Minimization and Feasibility Study for Managing the Complex and Interacting Anesthesia-Hemodynamic System *

Abstract: A novel control strategy is proposed to enable uncertainty minimization through knowledge infusion into the closed loop. The developed methodology aims the application of predictive control to regulate the complex anesthetic- hemodynamic (AH) interaction in a set of patients during general anesthesia. A special focus is given to solutions for minimizing the risk of instability arising from large uncertainty in the patient model dynamics. The paper explores the concept of digitalizing surgical actions as part of the natural mimicking strategy of actual anesthesiologists’ real-life decision-making process. The simulations supporting the claims use an AH simulator. A feasibility study for solutions in an actual constrained input-output variable set is performed. Results confirm that the feasibility is enhanced when minimizing uncertainty conditions, having important clinical relevance in multi-drug optimization.

Versatile Solutions for the Combine Harvester Header Height Control Problem

Abstract: Combine harvesters are considered challenging from control optimization point of view as they operate as factory on wheels, whereas multiple sub-systems with strong nonlinearities and dynamic interactions need to be managed simultaneously. The task of each sub-system is to execute its part with high performance under strongly varying operating conditions. The environment, from the machine itself, or from the outside area, is a strong disturbance to various interconnected control variables. A solution is provided here for the header height control problem, subject to external load disturbances coming from the field surface profile. The solution is versatile and enables multiple pathways to reached control structures ranging from simple PID tuners to predictive control. The simulated and field test results and their comparison indicates the feasibility of the proposed techniques in practice.

Closed-loop control of multi-drug infusion for anesthesia and hemodynamic management

Abstract: This paper proposes the first MIMO closed-loop control of both anesthesia and hemodynamic system. The designed control strategies have been validated on a novel patient simulator. The aim of this paper is to evaluate the feasibility MIMO closed-loop control of anesthesia and hemodynamic variables taking into account the interaction (synergic and antagonistic) between subsystems. MPC control algorithm have been implemented and the results obtained reveal the feasibility of the patient simulator. The proposed methodology takes into account patient variability, is robust to subsystems interaction and meets the clinical objectives. The control algorithms are combined with the action of the anesthesiologist. Moreover, a disturbance signal to mimic surgical excitation has been introduced in the control architecture. The results given in this paper show the antagonistic effect in closed loop of the intervention from the anesthesiologist when additional bolus intake is present.

Control of Nonlinear Mechatronic Systems with Context-Dependent Varying Dynamics

Abstract: In this paper, a novel approach to nonlinear control techniques based on material properties of handling objects in a class of nonlinear actuators is presented. A modified nonlinear fractional order sliding mode control is proposed with adaptation mechanisms to various material densities. The application domain of these techniques are well suited in agricultural, heavy-duty machines, including those featuring flexible joint manipulators. Experimental data indicates the feasibility of the proposed techniques in practice.

Time-frequency varying tissue impedance properties from noxious stimulation protocols

Abstract: Tissue impedance can be an evaluation factor for noxious stimulation in humans. It has been shown in several studies that bioimpedance can be used as a direct evaluation tool of pain. In this study, we evaluated the changes in perception of different stimuli (mechanical and thermal) applied to subjects in a safe laboratory environment. The measurements are performed with the in-house developed pain monitoring device ANSPEC-PRO, employing impedance evaluation as a function of time and frequency. In this paper the following hypotheses have been investigated: i) the time-frequency response is nonlinear and independent of stimuli type, ii) there are differences in energy between mechanical and thermal-induced pain as indicated by impedance changes.

Optimizing radiotherapy with chemotherapy using PKPD modeling for lung cancer *

Abstract: Targeting a high-precision treatment in lung cancer assumes a good knowledge of the mechanisms that underlie tumor dynamics and drug kinetics. In this work, we consider a mathematical model for tumor radiotherapy and chemotherapy as an optimal solution for local tumor control. The prediction model encompasses the understanding of cancer biology and radiation response, incorporating dose fractionation, tumor volume, and therapies effect. The results are commonly found in practice and stress the importance of computer simulations as a tool for adjusting the therapy in the pre-treatment phase if needed. Significant gain in curative cancer therapy can be achieved by applying mathematically based treatment planning and obtaining a predicted outcome for a specific treatment schedule.

Lumped Parametric Model for Skin Impedance Data in Patients with Postoperative Pain

Abstract: The societal and economic burden of unassessed and unmodeled postoperative pain is high and predicted to rise over the next decade, leading to over-dosing as a result of subjective (NRS-based) over-estimation by the patient. This study identifies how post-surgical trauma alters the parameters of impedance models, to detect and examine acute pain variability. Model identification is performed on clinical data captured from post-anesthetized patients, using Anspec-PRO prototype apriori validated for clinical pain assessment. The multisine excitation of this in-house developed device enables utilizing the complex skin impedance frequency response in data-driven electrical models. The single-dispersion Cole model is proposed to fit the clinical curve in the given frequency range. Changes in identified parameters are analyzed for correlation with the patient's reported pain for the same time moment. The results suggest a significant correlation for the capacitor component. Clinical Relevance— Individual model parameters validated on patients in the post-anesthesia care unit extend the knowledge for objective pain detection to positively influence the outcome of clinical analgesia management