Nonovershooting and nonundershooting exact output regulation

We consider the classic problem of exact output regulation for a linear time invariant plant. Under the assumption that either a state feedback or measurement feedback output regulator exists, we give design methods to obtain a regulator that avoids overshoot and undershoot in the transient response

A nonovershooting controller with integral action for multi-input multi-output drug dosing control

In this paper, a nonovershooting tracking controller is proposed for the continuous infusion of multiple drugs that have interactive effects. The proposed controller design method exploits the freedom of eigenstructure assignment pertinent to the design of feedback controllers for multi-input, multi-output (MIMO) systems. For drug dosing, a nonovershooting tracking controller restricts the undesirable side effects of drug overdosing. The proposed tracking controller is based on an estimate of the full state using a hybrid extended Kalman filter (EKF) that is used to reconstruct the system states from the measurable system outputs. An integral control action is included in the controller design to achieve robust tracking in the presence of patient parameter uncertainty. Simulation results and performance analysis of the proposed control strategy are also presented using 20 simulated patients. 2018Qatar National Research FundScopu

Radiotherapy Cancer Treatment: Investigating Real-Time Position and Dose Control, the Sensor-Delayed Plant Output Estimation Problem, and the Nonovershooting Step Response Problem

For over a century, physicians have prescribed x-ray radiation to destroy or impede the growth of cancerous tumours. Modern radiation therapy machines shape the radiation beam to balance the competing goals of maximizing irradiation of cancerous tissue and minimizing irradiation of healthy tissue, an objective complicated by tumour motion during the treatment and errors positioning the patient to align the tumour with the radiation beam. Recent medical imaging advances have motivated interest in using feedback during radiation therapy to track the tumour in real time and mitigate these complications. This thesis investigates how real-time feedback control can be used to track the tumour and focus the radiation beam tightly around the tumour. Improving on these results, a feedback control system is proposed for intensity modulated radiation therapy which allows a non-uniform radiation dose to be applied to the tumour. Motivated by the results of the proposed control systems, this thesis also examines two theoretical control problems: estimating the output of an unknown system when a sensor delay prevents its direct measurement, and designing a controller to provide an arbitrarily fast nonovershooting step response

An open source patient simulator for design and evaluation of computer based multiple drug dosing control for anesthetic and hemodynamic variables

We are witnessing a notable rise in the translational use of information technology and control systems engineering tools in clinical practice. This paper empowers the computer based drug dosing optimization of general anesthesia management by means of multiple variables for patient state stabilization. The patient simulator platform is designed through an interdisciplinary combination of medical, clinical practice and systems engineering expertise gathered in the last decades by our team. The result is an open source patient simulator in Matlab/Simulink from Mathworks(R). Simulator features include complex synergic and antagonistic interaction aspects between general anesthesia and hemodynamic stabilization variables. The anesthetic system includes the hypnosis, analgesia and neuromuscular blockade states, while the hemodynamic system includes the cardiac output and mean arterial pressure. Nociceptor stimulation is also described and acts as a disturbance together with predefined surgery profiles from a translation into signal form of most commonly encountered events in clinical practice. A broad population set of pharmacokinetic and pharmacodynamic (PKPD) variables are available for the user to describe both intra- and inter-patient variability. This simulator has some unique features, such as: i) additional bolus administration from anesthesiologist, ii) variable time-delays introduced by data window averaging when poor signal quality is detected, iii) drug trapping from heterogeneous tissue diffusion in high body mass index patients. We successfully reproduced the clinical expected effects of various drugs interacting among the anesthetic and hemodynamic states. Our work is uniquely defined in current state of the art and first of its kind for this application of dose management problem in anesthesia. This simulator provides the research community with accessible tools to allow a systematic design, evaluation and comparison of various control algorithms for multi-drug dosing optimization objectives in anesthesia

Closed-loop control of anesthesia : survey on actual trends, challenges and perspectives

Automation empowers self-sustainable adaptive processes and personalized services in many industries. The implementation of the integrated healthcare paradigm built on Health 4.0 is expected to transform any area in medicine due to the lightning-speed advances in control, robotics, artificial intelligence, sensors etc. The two objectives of this article, as addressed to different entities, are: i) to raise awareness throughout the anesthesiologists about the usefulness of integrating automation and data exchange in their clinical practice for providing increased attention to alarming situations, ii) to provide the actualized insights of drug-delivery research in order to create an opening horizon towards precision medicine with significantly improved human outcomes. This article presents a concise overview on the recent evolution of closed-loop anesthesia delivery control systems by means of control strategies, depth of anesthesia monitors, patient modelling, safety systems, and validation in clinical trials. For decades, anesthesia control has been in the midst of transformative changes, going from simple controllers to integrative strategies of two or more components, but not achieving yet the breakthrough of an integrated system. However, the scientific advances that happen at high speed need a modern review to identify the current technological gaps, societal implications, and implementation barriers. This article provides a good basis for control research in clinical anesthesia to endorse new challenges for intelligent systems towards individualized patient care. At this connection point of clinical and engineering frameworks through (semi-) automation, the following can be granted: patient safety, economical efficiency, and clinicians' efficacy

Control Systems: New Approaches to Analysis and Design

This dissertation deals with two open problems in control theory. The first problem concerns the synthesis of fixed structure controllers for Linear Time Invariant (LTI) systems. The problem of synthesizing fixed structure/order controllers has practical importance when simplicity, hardware limitations, or reliability in the implementation of a controller dictates a low order of stabilization. A new method is proposed to simplify the calculation of the set of fixed structure stabilizing controllers for any given plant. The method makes use of computational algebraic geometry techniques and sign-definite decomposition method. Although designing a stabilizing controller of a fixed structure is important, in many practical applications it is also desirable to control the transient response of the closed loop system. This dissertation proposes a novel approach to approximate the set of stabilizing Proportional-Integral-Derivative (PID) controllers guaranteeing transient response specifications. Such desirable set of PID controllers can be constructed upon an application of Widder's theorem and Markov-Lukacs representation of non-negative polynomials. The second problem explored in this dissertation handles the design and control of linear systems without requiring the knowledge of the mathematical model of the system and directly from a small set of measurements, processed appropriately. The traditional approach to deal with the analysis and control of complex systems has been to describe them mathematically with sets of algebraic or differential equations. The objective of the proposed approach is to determine the design variables directly from a small set of measurements. In particular, it will be shown that the functional dependency of any system variable on any set of system design parameters can be determined by a small number of measurements. Once the functional dependency is obtained, it can be used to extract the values of the design parameters