Normalization of Insulin Delivery to Diabetics by Pulsed Insulin Infusion

The objective was to continuously provide insulin to diabetic patients so as to mimic the time course of natural plasma insulin in response to meal ingestion in normal subjects. The normal curve of plasma insulin was well approximated as a double exponential, and this function was used as the output of a mathematical model of the body compartment plasma insulin-clearance system in order to derive an input expression. This input expression was thus the infusion time function needed to produce the desired plasma time function of insulin concentration in diabetics. The infusion function was implemented with a special purpose computer, designed with logic technics, that was then used to drive a servo infusion pump. The system delivered a 4-5-h pulse of insulin, the parameters of which were tailored for each patient's body weight and clearance rate, and with the different required profile for each of the three daily meals. These pulses rode on top of a constant basal infusion rate, the basal rate being delivered only throughout the night hours. The system was successfully tested on a simulated (hydraulic) patient, and then on one of us as a human volunteer., It has since been used with 10 diabetic patients in which the original objective was accomplished with satisfactory clinical results.     

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.     

Multiple drug hemodynamic control by means of a supervisory-fuzzyrule-based adaptive control system: validation on a model

A control device that uses an expert system approach for a two input-two output system has been developed and evaluated using a mathematical model of the hemodynamic response of a dog. The two inputs are the infusion rates of two drugs: sodium nitroprusside (SNP) and dopamine (DPM). The two controlled variables are the mean arterial pressure and the cardiac output. The control structure is dual mode, i.e., it has two levels: a critical conditions (coarse) control mode and a noncritical conditions (fine) control mode. The system switches from one to the other when threshold conditions are met. Different “controller parameters sets”-including the values. For the threshold conditions-can be given to the system which will lead to different controller outputs. Both control modes are rule-based, and supervisory capabilities are added to ensure adequate drug delivery. The noncritical control mode is a fuzzy logic controller. The system includes heuristic features typically considered by anesthesiologists, like waiting periods and the observance of a “forbidden dosage range” for DPM infusion when used as an inotrope. An adaptation algorithm copes with the wide range of sensitivities to SNP found among different individuals, as well as the time varying sensitivity frequently observed in a single patient. The control device is eventually tested on a nonlinear model, designed to mimic the conditions of congestive heart failure in a dog. The test runs show a highest overshoot of 3 mmHg with nominal SNP sensitivity. When tested with different simulated SNP sensitivities, the controller adaptation produces a faster response to lower sensitivities, and reduced oscillations to higher sensitivities. The simulations seem to show that the system is able to drive and adequately keep the two hemodynamic variables within prescribed limits     

A pressure controller for estimating parameters for a nonlinear CSFmodel

Pressure feedback control of cerebrospinal fluid (CSF) infusion rate was used to estimate the parameters of a nonlinear model of the CSF system. The steady-state pressure and infusion rate were used to estimate the parameters of CSF formation and CSF absorption using the nonlinear least-squares method. The CSF compliance was then estimated using the transient portion of the pressure/infusion rate responses     

Experimental application of a quadratic optimal iterative learning control method for control of wafer temperature uniformity in rapid thermal processing

A quadratic-optimal iterative learning control (ILC) method has been designed and implemented on an experimental rapid thermal processing system used for fabricating 8-in silicon wafers. The controller was designed to control the wafer temperatures at three separate locations by manipulating the power inputs to three groups of tungsten-halogen lamps. The controller design was done based on a time-varying linear state-space model, which was identified using experimental input-output data obtained at two different temperatures. When initialized with the input profiles produced by multiloop PI controllers, the ILC controller was seen to be capable of improving the control performance significantly with repeating runs. In a series of experiments with wafers on which thermocouples are glued, the ILC controller, over the course of ten runs, gradually steered the wafer temperatures very close to the respective reference trajectories despite significant disturbances and model errors.     

The hybrid model: a new pharmacokinetic model forcomputer-controlled infusion pumps

Classical pharmacokinetic models used in computer-controlled infusion pumps (CCIPs) assume instantaneous mixing of drug in blood; however, the average recirculation time of blood in man is approximately one minute. To investigate the effects of recirculation dynamics on the transient performance of CCIPs the authors propose a hybrid physiologically-based pharmacokinetic model for the narcotic alfentanil. A three-compartment model was derived from the response of the hybrid model to a short infusion and used to compute a CCIP infusion targeting 450 μg/l. For this infusion, the hybrid model predicts that the arterial plasma concentration will overshoot the target concentration by 39 percent with an average prediction error of 3 percent. The overshoot and average prediction error increase to 100 and 25 percent respectively when using a three-compartment pharmacokinetic model derived from a bolus. The overshoot can be reduced by decreasing the maximum possible infusion rate, or by increasing the zero-order hold infusion interval     

Continuous Drug Delivery System Design Using Nonlinear Decoupling: A Tutorial

The design of nonlinear, time varying, multivariable, coupled system is a complicated task which offers few intuitive guides. Such guides are by contrast abundant in the much simpler task of designing a linear decoupled control system. Decoupling also allows the independent control of the system outputs in the presence of input interactions. The implications of these ideas in the design of control systems for continuous drug infusion have never been explored. This tutorial demonstrates the usefulness of nonlinear decoupling in the context of drug delivery using simple examples. First, decoupling by differentiation of the output equation is demonstrated. Next, two special cases where decoupling is achievable by input redefinition ann by input and state redefinition are given. Finally, limitations of the approach are discussed together with ongoing research to overcome them. The presentation avoids complex mathematical derivations and demonstrates that nonlinear decoupling can be applied using basic calculus.     

An RMRAC Current Regulator for Permanent-Magnet Synchronous Motor Based on Statistical Model Interpretation

A new robust model reference adaptive control (RMRAC) scheme for the current regulation of a permanent-magnet synchronous motor (PMSM) is proposed in a synchronous frame, which is completely free from the control performance degradation caused by parameter uncertainties. The current regulator of the PMSM is the innermost loop of its electromechanical driving system and plays an important role in the control hierarchy. When the PMSM runs precisely at high speeds, the cross-coupling terms must be compensated for. In the proposed RMRAC, the input signal is composed of the control voltage obtained by the model reference adaptive control (MRAC) law and the output of the disturbance estimator. The gains of the feedforward and feedback controllers are estimated by the proposed modified gradient method, where the system disturbances are filtered out by the estimated current regulation error. A voltage corresponding to the estimated system disturbances is fed forward to the control input in order to filter out the disturbances. The proposed method compensates the cross-coupling terms in a synchronous current model regardless of parameter variations. It also shows a good real-time performance due to the simplicity of control structure. Through simulations and real experiments, the efficiency of the proposed method is verified.     

Adaptive control of blood pressure

Stochastic adaptive controllers have been developed for automatic control of blood pressure during infusions of cardiostimulatory or vasoactive drugs. An adaptive algorithm based upon a minimum variance control law is presented. A more advanced algorithm obtained by augmenting the performance measure to include the rate of charge of the control signal is also presented. An autoregressive-moving-average (ARMA) model, representing the dynamics of the system, and a recursive least-squares parameter estimation technique are used for both algorithms. A series of experiments was performed in dogs, utilizing an electronically activated drug infuser. Stable control was achieved, even when the circulatory state of the animal underwent major changes, using either algorithm. On the basis of theoretical considerations and experimental results, we expect that these adaptive controllers will significantly improve the performance of drug infusion systems in clinical applications.     

Innovative ambulatory drug delivery system using an electrolytichydrogel infusion pump

This report describes an ambulatory infusion device developed to provide parenteral drug delivery at a precisely controlled rate. The device is based on the innovative and unique concept of utilizing electrohydrolysis of a negatively charged hydrogel. The system consists of two modules: a pump unit and an electronic control unit. The pump module, which can be a disposable unit, contains medication separated by a flexible membrane from a gas generating chamber; this latter is an electrolytic cell comprising a hydrogel block and two platinum electrodes. The microcontroller-based control module is constructed with a user interface which includes input keys and a liquid crystal display, as well as a control to alter driving current level, depending on the infusion rate required. A microprocessor instantaneously calculates the current level required; this is based on operator-selected infusion rate, ambient pressure, and temperature sensor output. The accuracy and precision of the device were verified for all flow rates and for different environmental conditions; in vitro test results showed acceptable accuracy with less than +/- 5% error over the whole operating range of 0.1-100 [ml/h]. The device is small, lightweight, simple and easy to manufacture, and is also designed to be comfortably and conveniently worn by patients. It can be used for a variety of regimens including, for example, chemotherapy, insulin delivery, and pain management, antibiotic and AIDS therapy.     

Adaptive Multivarable Drug Delivery: Control of Artenal Pressure and Cardiac Output in Anesthetized Dogs

An adaptive algorithm (CAMAC, control advance moving average controller) to control multiinput/multioutput physiological systems has been implemented and tested. The algorithm is a self-tuning controller that determines the input on the basis of the expected difference between the output and desired output at a time interval equal to or greater than the system dead time. The algorithm was used to simultaneously control mean arterial pressure and cardiac output in anesthetized dogs by the simultaneous computer-controlled infusion of sodium nitroprusside and dobutamine. The results demonstrate the feasibility of using CAMAC for multivariable drug delivery, but they indicate the need for further work before clinical applications are attempted.     

Extensions and performance/robustness tradeoffs of the EWMArun-to-run controller by using the internal model control structure

We consider the run-to-run (RtR) correction of input recipes for semiconductor manufacturing processes using measurement information from previous runs. A RtR control algorithm that has been experimentally tested by industry and academia is the EWMA (exponentially weighted moving average) RtR controller. In this paper we provide extensions to this algorithm to address some of its drawbacks and also provide a rigorous theoretical analysis of its properties based on discrete control theory. By formulating the RtR control problem in the internal model control (IMC) structure used in feedback process control, we are able to extend the algorithm to completely eliminate offsets due to unmodeled process drifts, which is a common problem in semiconductor manufacturing. We also develop conditions for robustness with respect to modeling error and measurement delays. Tradeoffs between robustness guarantees and fast RtR response as well as handling of measurement noise are developed and presented in the form of plots that can be used for tuning the parameters of the RtR-IMC controller to accomplish the objectives set by the process engineer. The results are illustrated through several simulations including control of film deposition uniformity in an epitaxial reactor and tungsten deposition rate in a tungsten CVD reactor     

Accuracy of drug infusion pumps under computer control

Prototype systems implementing algorithms for automated drug infusions are typically constructed by coupling a microcomputer to a drug infusion pump through a serial communications interface. Infusion rates demanded of the infusion pump in many computed-controlled drug delivery applications are made to change at intervals much shorter than those encountered under routine clinical use. Because the ability of infusion pumps to maintain accurate flow rates during high frequency rate changes has not been documented, the purpose of this study was to validate the volumetric accuracy of three commercially available infusion pumps operating in a demanding computer-controlled application. In independent 2-h evaluations, the infusion rate demanded of each pump changed as often as every 5, 10, or 15 s using an algorithm for computer-controlled pharmacokinetic model-driven intravenous infusion. Accuracy of the infusion devices was determined gravimetrically. At all measurement times, each of the infusion pumps was accurate to within approximately +/- 5% of the expected volumetric output under each of the infusion rate intervals tested. Flow rate accuracy of +/- 5% is equal to the nominal expected accuracy of these infusion pumps in conventional clinical use.     

An Open-Loop Computer-Based Drug Infusion System

This study reports the development of a computer-based infusion system and methodology to produce and maintain selected plasma concentrations. The method identifies pharmacokinetic infusion parameters for subjects from bolus injection response data, employs these values in control equations implemented by a portable microcomputer and computer-controlled infusion pump, and achieves and maintains selected stepwise drug levels by intravenous drug infusion. Infusion studies with four dogs and five humans resulted in correlation coefficients of 0.98 for the dogs and 0.94 for the humans, with rms errors in maintaining the drug concentration at the desired level of 13.4 and 19.3 percent, respectively. An analysis of error demonstrated that: 1) the control error was less than the value of the pharmacokinetic parameter estimation error in determining a single parameter value, 2) errors in several parameters can have cancelling or additive effects depending on their sign, and 3) an error in the sum of two of the model parameters (A and B) directly translates to equivalent time-independent error in the controlled level.     

三阶1-1-1级联Σ-Δ调制器的设计及仿真

采用MASH结构,设计了一款三阶(1-1-1)级联Σ-Δ调制器;讨论了各个模块的增益系数,设计了数字校正电路,并运用Matlab/Simulink对调制器进行了行为级仿真.当输入信号带宽为20 kHz,过采样比为64时,仿真模型得到87.7 dB的信噪比,精度为14.28位.与其他结构的调制器相比,该调制器更加稳定,动态范围更大,可应用于处理音频信号的A/D转换器.     

A new paradigm for the closed-loop intraoperative administration of analgesics in humans

We present a new paradigm for the closed-loop administration of analgesics during general anesthesia. The manipulated variable in the control system is the infusion rate of the opiate alfentanil, administered intravenously through a computer-controlled infusion pump (CCIP). The outputs to be controlled are the patient's mean arterial pressure (MAP) and the drug concentration in the plasma. Maintaining MAP within appropriate ranges provides optimal treatment of the patient's reactions to surgical stimuli. Maintaining plasma drug concentrations close to a reference value specified by the anesthesiologist allows to titrate analgesic administration to qualitative clinical end-points of insufficient analgesia. MAP is acquired invasively through a catheter cannula. Since plasma drug concentrations cannot be measured on-line, they are estimated via a pharmacokinetic model. We describe an explicit model-predictive controller which achieves the above-mentioned objectives. An upper constraint on drug concentrations is maintained to avoid overdosing. Constraints on the MAP are introduced to trigger a prompt controller reaction during hypertensive and hypotensive periods. Measurement artifacts in the MAP signal are rejected to prevent harmful misbehavior of the controller. We discuss the results of the clinical validation of the controller on humans.     

Computer Simulation of Adaptive Drug Infusion

Clinical drug infusion protocols, such as a single bolus followed by a constant drip, do not establish and maintain therapeutic drug levels in an optimal manner. We have investigated a system in which the patient, drug pump, drug assay, and a pump controller are incorporated into an adaptive configuration. The system, which we have simulated on a computer, uses an adaptive approach in which the pump controller operates with a model of the subject response. The model is fit to the specific subject by a regression analysis of the subject's response, obtained by assay of the subject's blood.     

Algorithm for optimal linear model-based control with applicationto pharmacokinetic model-driven drug delivery

Computerized pharmacokinetic model-driven administration of intravenous anesthetic agents has been implemented using a variety of algorithms to control the drug infusion regimen. All such algorithms are similar to the extent that they use a linear pharmacokinetic model of the drug being administered to determine drug infusion rates to theoretically achieve and maintain plasma drug concentrations (setpoints) specified by the physician. Since the behavior of the pharmacokinetic model can be computed for any input, it should be possible to achieve regulation of the drug infusion rates that is flexible (i.e., the physician can interactively adjust the setpoint), practical, and analytically optimized; these objectives are realized by the algorithm described in this communication.     

A 0.5-μm CMOS 4.0-Gbit/s serial link transceiver with datarecovery using oversampling

A 4-Gbit/s serial link transceiver is fabricated in a MOSIS 0.5-μm HPCMOS process. To achieve the high data rate without speed critical logic on chip, the data are multiplexed when transmitted and immediately demultiplexed when received. This parallelism is achieved by using multiple phases tapped from a PLL using the phase spacing to determine the bit time. Using an 8:1 multiplexer yields 4 Gbits/s, with an on-chip VCO running at 500 MHz. The internal logic runs at 250 MHz. For robust data recovery, the input is sampled at 3× the bit rate and uses a digital phase-picking logic to recover the data. The digital phase picking can adjust the sample at the clock rate to allow high tracking bandwidth. With a 3.3-V supply, the chip has a measured bit error rate (BER) of <10^-14