Arbitrary‐order sliding mode‐based robust control algorithm for the developing artificial pancreas mechanism

In Diabetes Mellitus, the pancreas remains incapable of insulin administration that leads to hyperglycaemia, an escalated glycaemic concentration, which may stimulate many complications. To circumvent this situation, a closed‐loop control strategy is much needed for the exogenous insulin infusion in diabetic patients. This closed‐loop structure is often termed as an artificial pancreas that is generally established by the employment of different feedback control strategies. In this work, the authors have proposed an arbitrary‐order sliding mode control approach for development of the said mechanism. The term, arbitrary, is exercised in the sense of its applicability to any n ‐order controllable canonical system. The proposed control algorithm affirms the finite‐time effective stabilisation of the glucose–insulin regulatory system, at the desired level, with the alleviation of sharp fluctuations. The novelty of this work lies in the sliding manifold that incorporates indirect non‐linear terms. In addition, the necessary discontinuous terms are filtered‐out once before its employment to the plant, i.e. diabetic patient. The robustness, in the presence of external disturbances, i.e. meal intake is confirmed via rigorous mathematical stability analysis. In addition, the effectiveness of the proposed control strategy is ascertained by comparing the results with the standard literature.Inspec keywords: diseases, blood, control system synthesis, medical control systems, feedback, sugar, stability, closed loop systems, robust control, variable structure systemsOther keywords: finite‐time effective stabilisation, glucose–insulin regulatory system, sliding manifold, nonlinear terms, necessary discontinuous terms, employment, diabetic patient, arbitrary‐order sliding mode‐based robust control algorithm, developing artificial pancreas mechanism, Diabetes Mellitus, insulin administration, escalated glycaemic concentration, closed‐loop control strategy, exogenous insulin infusion, closed‐loop structure, different feedback control strategies, mode control approach, n‐order controllable canonical system, control algorithm affirms     

Robust observer based control for plasma glucose regulation in type 1 diabetes patient using attractive ellipsoid method

This paper deals with the design of robust observer based output feedback control law for the stabilisation of an uncertain nonlinear system and subsequently apply the developed method for the regulation of plasma glucose concentration in Type 1 diabetes (T1D) patients. The principal objective behind the proposed design is to deal with the issues of intra‐patient parametric variation and non‐availability of all state variables for measurement. The proposed control technique for the T1D patient model is based on the attractive ellipsoid method (AEM). The observer and controller conditions are obtained in terms of linear matrix inequality (LMI), thus allowing to compute easily both the observer and controller gains. The closed‐loop response obtained using the designed controller avoids adverse situations of hypoglycemia and post‐prandial hyperglycemia under uncertain conditions. Further to validate the robustness of the design, closed‐loop simulations of random 200 virtual T1D patients considering parameters within the considered ranges are presented. The results indicate that hypoglycemia and post‐prandial hyperglycemia are significantly reduced in the presence of bounded (±30% ) parametric variability and uncertain exogenous meal disturbance.Inspec keywords: medical control systems, observers, uncertain systems, nonlinear control systems, robust control, control system synthesis, linear matrix inequalities, feedback, sugar, closed loop systems, diseasesOther keywords: virtual T1D patients, type 1 diabetes patients, closed‐loop simulations, uncertain conditions, post‐prandial hyperglycemia, designed controller, closed‐loop response, controller gains, linear matrix inequality, controller conditions, T1D patient model, control technique, intra‐patient parametric variation, principal objective, plasma glucose concentration, uncertain nonlinear system, robust observer based output feedback control law, attractive ellipsoid method, plasma glucose regulation     

Rehabilitation of the Parkinson's tremor by using robust adaptive sliding mode controller: a simulation study

One of the efficient methods in controlling the Parkinson''s tremor is Deep Brain Stimulation (DBS) therapy. The stimulation of Basal Ganglia (BG) by DBS brings no feedback though the existence of feedback reduces the additional stimulatory signal delivered to the brain. So this study offers a new adaptive architecture of a closed‐loop control system in which two areas of BG are stimulated simultaneously to decrease the following three indicators: hand tremor, the level of a delivered stimulation signal in the disease condition, and the level of a delivered stimulation signal in health condition to the disease condition. One area (STN: subthalamic nucleus) is stimulated with an adaptive sliding mode controller and the other area (GPi: Globus Pallidus internal) with partial state feedback controller. The simulation results of stimulating two areas of BG showed satisfactory performance.Inspec keywords: bioelectric phenomena, diseases, variable structure systems, brain models, biomedical electrodes, adaptive control, closed loop systems, state feedback, feedback, neurophysiology, brain, robust controlOther keywords: DBS, additional stimulatory signal, adaptive architecture, closed‐loop control system, hand tremor, delivered stimulation signal, disease condition, health condition, partial state feedback controller, Parkinson''s tremor, robust adaptive sliding mode controller, simulation study, efficient methods, Deep Brain Stimulation therapy, Basal Ganglia     

Chattering‐ free hybrid adaptive neuro‐fuzzy inference system‐particle swarm optimisation data fusion‐based BG‐level control

In this study, a closed‐loop control scheme is proposed for the glucose–insulin regulatory system in type‐1 diabetic mellitus (T1DM) patients. Some innovative hybrid glucose–insulin regulators have combined artificial intelligence such as fuzzy logic and genetic algorithm with well known Palumbo model to regulate the blood glucose (BG) level in T1DM patients. However, most of these approaches have focused on the glucose reference tracking, and the qualitative of this tracking such as chattering reduction of insulin injection has not been well‐studied. Higher‐order sliding mode (HoSM) controllers have been employed to attenuate the effect of chattering. Owing to the delayed nature and non‐linear property of glucose–insulin mechanism as well as various unmeasurable disturbances, even the HoSM methods are partly successful. In this study, data fusion of adaptive neuro‐fuzzy inference systems optimised by particle swarm optimisation has been presented. The excellent performance of the proposed hybrid controller, i.e. desired BG‐level tracking and chattering reduction in the presence of daily glucose‐level disturbances is verified.Inspec keywords: fuzzy control, variable structure systems, particle swarm optimisation, neurocontrollers, fuzzy neural nets, blood, genetic algorithms, closed loop systems, medical control systems, fuzzy reasoning, diseases, nonlinear control systems, sugarOther keywords: data fusion, adaptive neuro‐fuzzy inference systems, particle swarm optimisation, hybrid controller, desired BG‐level tracking, chattering reduction, daily glucose‐level disturbances, closed‐loop control scheme, glucose–insulin regulatory system, type‐1 diabetic mellitus patients, innovative hybrid glucose–insulin regulators, artificial intelligence, fuzzy logic, genetic algorithm, Palumbo model, blood glucose level, T1DM patients, glucose reference tracking, insulin injection, mode controllers, glucose–insulin mechanism, chattering‐free hybrid adaptive neuro‐fuzzy inference system, particle swarm optimisation data fusion‐based BG‐level control     

Robust multi‐objective blood glucose control in Type‐1 diabetic patient

In this study, an automatic robust multi‐objective controller has been proposed for blood glucose (BG) regulation in Type‐1 Diabetic Mellitus (T1DM) patient through subcutaneous route. The main objective of this work is to control the BG level in T1DM patient in the presence of unannounced meal disturbances and other external noises with a minimum amount of insulin infusion rate. The multi‐objective output‐feedback controller with H_∞, H₂ and pole‐placement constraints has been designed using linear matrix inequality technique. The designed controller for subcutaneous insulin delivery was tested on in silico adult and adolescent subjects of UVa/Padova T1DM metabolic simulator. The experimental results show that the closed‐loop system tracks the reference BG level very well and does not show any hypoglycaemia effect even during the long gap of a meal at night both for in silico adults and adolescent. In the presence of 50 gm meal disturbance, average adult experience normoglycaemia 92% of the total simulation time and hypoglycaemia 0% of total simulation time. The robustness of the controller has been tested in the presence of irregular meals and insulin pump noise and error. The controller yielded robust performance with a lesser amount of insulin infusion rate than the other designed controllers reported earlier.Inspec keywords: robust control, patient treatment, diseases, closed loop systems, patient monitoring, biochemistry, medical control systems, blood, organic compoundsOther keywords: robust multiobjective blood glucose control, automatic robust multiobjective controller, blood glucose regulation, Type‐1 Diabetic Mellitus patient, BG level, T1DM patient, insulin infusion rate, multiobjective output‐feedback controller, pole‐placement constraints, linear matrix inequality technique, subcutaneous insulin delivery, total simulation time, insulin pump noise, adolescent subjects, meal disturbance, normoglycaemia 92, in silico adults, UVa‐Padova T1DM metabolic simulator, closed‐loop system, hypoglycaemia effect     

Adaptive fractional‐order blood glucose regulator based on high‐order sliding mode observer

Type I diabetes is described by the destruction of the insulin‐producing beta‐cells in the pancreas. Hence, exogenous insulin administration is necessary for Type I diabetes patients. In this study, to estimate the states that are not directly available from the Bergman minimal model a high‐order sliding mode observer is proposed. Then fractional calculus is combined with sliding mode control (SMC) for blood glucose regulation to create more robustness performance and make more degree of freedom and flexibility for the proposed method. Then an adaptive fractional‐order SMC is proposed. The adaptive SMC protect controller against disturbance and uncertainties while the fractional calculus provides robust performance. Numerical simulation verifies that the proposed controllers have better performance in the presence of disturbance and uncertainties without chattering.Inspec keywords: variable structure systems, biochemistry, blood, robust control, medical control systems, observers, sugar, diseases, calculus, adaptive control, cellular biophysicsOther keywords: fractional‐order SMC, adaptive SMC, fractional calculus, robust performance, adaptive fractional‐order blood glucose regulator, insulin‐producing beta‐cells, exogenous insulin administration, diabetes patients, Bergman minimal model, mode control, blood glucose regulation, pancreas, type I diabetes, state estimation, high‐order sliding mode observer, sliding mode control, degree of freedom, numerical simulation     

Hypoglycaemia‐free artificial pancreas project

Driving blood glycaemia from hyperglycaemia to euglycaemia as fast as possible while avoiding hypoglycaemia is a major problem for decades for type‐1 diabetes and is solved in this study. A control algorithm is designed that guaranties hypoglycaemia avoidance for the first time both from the theory of positive systems point of view and from the most pragmatic clinical practice. The solution consists of a state feedback control law that computes the required hyperglycaemia correction bolus in real‐time to safely steer glycaemia to the target. A rigorous proof is given that shows that the control‐law respects the positivity of the control and of the glucose concentration error: as a result, no hypoglycaemic episode occurs. The so‐called hypo‐free strategy control is tested with all the UVA/Padova T1DM simulator patients (i.e. ten adults, ten adolescents, and ten children) during a fasting‐night scenario and in a hybrid closed‐loop scenario including three meals. The theoretical results are assessed by the simulations on a large cohort of virtual patients and encourage clinical trials.Inspec keywords: biochemistry, medical control systems, blood, diseases, medical computing, closed loop systems, biomedical equipment, state feedback, patient treatment, patient monitoring, biomedical measurement, physiological models, sugarOther keywords: fasting‐night scenario, hybrid closed‐loop scenario, hypoglycaemia‐free artificial pancreas project, blood glycaemia, euglycaemia, type‐1 diabetes, control algorithm, guaranties hypoglycaemia avoidance, pragmatic clinical practice, state feedback control law, required hyperglycaemia correction bolus, rigorous proof, control‐law, glucose concentration error, hypo‐free strategy control     

Blood glucose concentration control for type 1 diabetic patients: a multiple‐model strategy

In this study, a multiple‐model strategy is evaluated as an alternative closed‐loop method for subcutaneous insulin delivery in type 1 diabetes. Non‐linearities of the glucose–insulin regulatory system are considered by modelling the system around five different operating points. After conducting some identification experiments in the UVA/Padova metabolic simulator (accepted simulator by the US Food and Drug Administration (FDA)), five transfer functions are obtained for these operating points. Paying attention to some physiological facts, the control objectives such as the required settling time and permissible bounds of overshoots and undershoots are determined for any transfer functions. Then, five PID controllers are tuned to achieve these objectives and a bank of controllers is constructed. To cope with difficulties of the presence of delays in subcutaneous blood glucose (BG) measuring and in administration of insulin, a glucose‐dependent setpoint is considered as the desired trajectory for the BG concentration. The performance of the obtained closed‐loop glucose–insulin regulatory system is investigated on the in silico adult cohort of the UVA/Padova metabolic simulator. The obtained results show that the proposed multiple‐model strategy leads to a closed‐loop mechanism with limited hyperglycemia and no severe hypoglycemia.Inspec keywords: blood, patient diagnosis, medical control systems, biochemistry, three‐term control, closed loop systems, diseases, patient treatment, drugs, sugarOther keywords: blood glucose concentration control, type 1 diabetic patients, multiple‐model strategy, alternative closed‐loop method, subcutaneous insulin delivery, type 1 diabetes, transfer functions, control objectives, PID controllers, subcutaneous blood glucose measuring, glucose‐dependent setpoint, closed‐loop glucose–insulin regulatory system, closed‐loop mechanism     

Sliding‐mode‐based controllers for automation of blood glucose concentration for type 1 diabetes

Destruction of β‐cells in pancreas causes deficiency in insulin production that leads to diabetes in the human body. To cope with this problem, insulin is either taken orally during the day or injected into the patient''s body using artificial pancreas (AP) during sleeping hours. Some mathematical models indicate that AP uses control algorithms to regulate blood glucose concentration (BGC). The extended Bergman minimal model (EBMM) incorporates, as a state variable, the disturbance in insulin level during medication due to either meal intake or burning sugar by engaging in physical exercise. In this research work, EBMM and proposed finite time robust controllers are used, including the sliding mode controller (SMC), backstepping SMC (BSMC) and supertwisting SMC (second‐order SMC or SOSMC) for automatic stabilisation of BGC in type 1 diabetic patients. The proposed SOSMC diminishes the chattering phenomenon which appears in the conventional SMC. The proposed BSMC is a recursive technique which becomes robust by the addition of the SMC. Lyapunov theory has been used to prove the asymptotic stability of the proposed controllers. Simulations have been carried out in MATLAB/Simulink for the comparative study of the proposed controllers under varying data of six different type 1 diabetic patients available in the literature.     

Parameter estimation of a meal glucose–insulin model for TIDM patients from therapy historical data

The effect of meal on blood glucose concentration is a key issue in diabetes mellitus because its estimation could be very useful in therapy decisions. In the case of type 1 diabetes mellitus (T1DM), the therapy based on automatic insulin delivery requires a closed‐loop control system to maintain euglycaemia even in the postprandial state. Thus, the mathematical modelling of glucose metabolism is relevant to predict the metabolic state of a patient. Moreover, the eating habits are characteristic of each person, so it is of interest that the mathematical models of meal intake allow to personalise the glycaemic state of the patient using therapy historical data, that is, daily measurements of glucose and records of carbohydrate intake and insulin supply. Thus, here, a model of glucose metabolism that includes the effects of meal is analysed in order to establish criteria for data‐based personalisation. The analysis includes the sensitivity and identifiability of the parameters, and the parameter estimation problem was resolved via two algorithms: particle swarm optimisation and evonorm. The results show that the mathematical model can be a useful tool to estimate the glycaemic status of a patient and personalise it according to her/his historical data.Inspec keywords: medical control systems, closed loop systems, particle swarm optimisation, parameter estimation, biochemistry, diseases, patient monitoring, patient diagnosis, blood, sugar, patient treatment, medical computingOther keywords: meal intake, metabolic state, mathematical modelling, postprandial state, closed‐loop control system, automatic insulin delivery, T1DM, type 1 diabetes mellitus, therapy decisions, blood glucose concentration, TIDM patients, meal glucose–insulin model, mathematical model, parameter estimation problem, data‐based personalisation, glucose metabolism, insulin supply, carbohydrate intake, glucose records, therapy historical data, glycaemic state     

Hypnosis regulation in propofol anaesthesia employing super‐twisting sliding mode control to compensate variability dynamics

Regulation of hypnosis level on bi‐spectral index monitor (BIS) during a surgical procedure in propofol anaesthesia administration is a challenging task for an anaesthesiologist in multi‐tasking environment of the operation theater. Automation in anaesthesia has the potential to solve issues arising from manual administration. Automation in anaesthesia is based on developing the three‐compartmental model including pharmacokinetics and pharmacodynamic of the silico patients. This study focuses on regulation of the hypnosis level in the presence of surgical stimulus including skin incision, surgical diathermy and laryngoscopy as well as inter‐patient variability by designing super‐twisting sliding mode control (STSMC). The depth of the hypnosis level is maintained to 50 on the BIS level in the maintenance phase after improving the induction phase to 60 s using the conventional sliding mode control and 30 s with STSMC. The proposed scheme also compensates the inter‐patient variability dynamics including height, age and weight of the different silico patients. Moreover, the surgical stimuli direct the hypnosis level towards the state of consciousness and stimulate the controller to provide continuous drug infusion during the interval 80–90 s. Simulation results witness that the oscillatory behaviour is observed in drug infusion to ensure the moderate level of hypnosis (40–60) for general surgery.Inspec keywords: surgery, patient treatment, patient monitoring, drugs, drug delivery systems, variable structure systems, medical control systems, perturbation techniquesOther keywords: hypnosis regulation, hypnosis level, bi‐spectral index monitor, surgical procedure, propofol anaesthesia administration, multitasking environment, manual administration, three‐compartmental model, surgical diathermy, laryngoscopy, BIS level, silico patients, surgical stimuli direct, moderate level, pharmacokinetics, interpatient variability dynamics, surgical stimulus, skin incision, time 60.0 s, time 80.0 s to 90.0 s, time 30.0 s     

Estimation of parameters for plasma glucose regulation in type‐2 diabetics in presence of meal

In this study, the authors propose a methodology for the estimation of glucose masses in stomach (both in solid and liquid forms), intestine, plasma and tissue; insulin masses in portal vein, liver, plasma and interstitial fluid using only plasma glucose measurement. The proposed methodology fuses glucose–insulin homoeostasis model (in the presence of meal intake) and plasma glucose measurement with a Bayesian non‐linear filter. Uncertainty of the model over individual variations has been incorporated by adding process noise to the homoeostasis model. The estimation is carried out over 24 h for the healthy people as well as a type II diabetes mellitus patients. In simulation, the estimator follows the truth accurately for both the cases. Moreover, the performances of two non‐linear filters, namely the unscented Kalman filter (KF) and cubature quadrature KF are compared in terms of root mean square error. The proposed methodology will be helpful in future to: (i) observe a patient''s insulin–glucose profile, (ii) calculate drug dose for any hyperglycaemic patients and (iii) develop a closed‐loop controller for automated insulin delivery system.Inspec keywords: blood, diseases, biochemistry, parameter estimation, biological tissues, liver, Bayes methods, nonlinear filters, Kalman filters, drugs, drug delivery systems, medical signal processingOther keywords: automated insulin delivery system, closed‐loop controller, hyperglycaemic patients, drug dose, root mean square error, cubature quadrature KF, Kalman filter, type II diabetes mellitus, process noise, Bayesian nonlinear filter, glucose‐insulin homoeostasis model, interstitial fluid, liver, portal vein, insulin mass, biological tissues, intestine, stomach, glucose mass, meal intake, type‐2 diabetics, plasma glucose regulation, parameter estimation     

Optimal sliding mode control of drug delivery in cancerous tumour chemotherapy considering the obesity effects

Different control strategies have been proposed for drug delivery in chemotherapy during recent years. These control algorithms are designed based on dynamic models of various orders. The order of the model depends on the number of effects considered in the model. In a recent model, the effect of obesity on the tumour progression and optimal control strategy in chemotherapy have been investigated in a fifth‐order state‐space model. However, the optimal controller is open loop and not robust to the common uncertainties of such biological system. Here, the sliding surface is obtained by the optimal trajectory and by considering uncertainties of some parameters, the robust‐sliding control law is formulated in a way to slid on the optimal surface. Then, a sliding mode controller is designed to determine the drug dose rate such that the system follows the optimal desired trajectory. The stability of the control system is proved and the simulation results indicate that three states track the trajectory and the remaining two states satisfy the constraints.Inspec keywords: drug delivery systems, drugs, tumours, cancer, optimal control, open loop systems, controllers, medical control systemsOther keywords: optimal sliding mode control, drug delivery, cancerous tumour chemotherapy, obesity effects, control algorithms, dynamic models, tumour progression, optimal control strategy, fifth‐order state‐space model, open loop, biological system, sliding surface, optimal trajectory, robust‐sliding control law, sliding mode controller, drug dose rate     

Robust control of HIV infection by antiretroviral therapy: a super‐twisting sliding mode control approach

Acquired immune deficiency syndrome is an epidemic infectious disease which is caused by the human immunodeficiency virus (HIV) and that has proliferated across worldwide. It has been a matter of concern for the scientific community to develop an antiretroviral therapy, which will prompt a rapid decline in viral abundance. With this motivation, this study proposes the design of a robust super twisting sliding mode controller based on output information for an uncertain HIV infection model. The control objective is to decrease the concentration of infected CD4+ T cells to a specified level by drug administration using only the output information of the uncertain HIV infection model which is total CD4+ T cell concentration. The robust output‐feedback controller has been developed in combination with a robust exact differentiator, functioning as an observer. The reported analysis demonstrates that the approach proposed here is capable of ensuring robust performance under several operating conditions, measurement and modelling error, parametric uncertainties and external disturbances and the simulation results prove the proficiency of the controller proposed.Inspec keywords: control system synthesis, observers, robust control, drugs, medical control systems, diseases, uncertain systems, variable structure systems, patient treatment, feedback, cellular biophysics, microorganismsOther keywords: robust control, antiretroviral therapy, sliding mode control approach, acquired immune deficiency syndrome, epidemic infectious disease, human immunodeficiency virus, scientific community, robust super, mode controller, output information, uncertain HIV infection model, control objective, infected CD4, total CD4, T cell concentration, robust output‐feedback controller, robust exact differentiator, robust performance     

Blood glucose concentration control for type 1 diabetic patients: a non‐linear suboptimal approach

In this study, a closed‐loop treatment strategy is proposed for the control of blood glucose levels in type 1 diabetic patients. Toward this end, a non‐linear technique for designing suboptimal tracking controllers, called the state‐dependent Riccati equation tracker, is used based on a mathematical model of the glucose–insulin regulatory system. Since two state variables of the utilised model are not available to the controller, a non‐linear filter is also designed to estimate these variables using the measured blood glucose concentration. Effects of unannounced meals and regular exercise are investigated for a nominal patient and nine diabetic patients with unknown parameters. Numerical simulations are given to show the effectiveness of the proposed treatment strategy even in the presence of parametric uncertainties and the observation noise.Inspec keywords: blood, biochemistry, diseases, patient treatment, Riccati equations, nonlinear filters, medical signal processingOther keywords: blood glucose concentration control, type 1 diabetic patients, nonlinear suboptimal approach, closed‐loop treatment strategy, suboptimal tracking controllers, state‐dependent Riccati equation tracker, glucose‐insulin regulatory system, nonlinear filter, unannounced meals, regular exercise, treatment strategy, parametric uncertainties, observation noise     

Controllability and observability analysis of basal ganglia model and feedback linearisation control

Deep brain stimulation (DBS) is a clinical remedy to control tremor in Parkinson''s disease. In DBS, one of the two main areas of basal ganglia (BG) is stimulated. This stimulation is produced with no feedback of the tremor and often causes a wide range of unpleasant side effects. Using a feedback signal from tremor, the stimulatory signal can be reduced or terminated to avoid extra stimulation and as a result decrease the side effects. To design a closed‐loop controller for the non‐linear BG model, a complete study of controllability and observability of this system is presented in this study. This study shows that the BG model is controllable and observable. The authors also propose the idea of stimulating the two BG areas simultaneously. A two‐part controller is then designed: a feedback linearisation controller for subthalamic nucleus stimulation and a partial state feedback controller for globus pallidus internal stimulation. The controllers are designed to decrease three indicators: the hand tremor, the level of delivered stimulation signal in disease condition, and the ratio of the level of delivered stimulation signal in health condition to disease condition. Considering these three indicators, the simulation results show satisfactory performance.Inspec keywords: feedback, brain, neurophysiology, diseases, medical control systems, closed loop systems, controllers, linearisation techniques, bioelectric phenomenaOther keywords: controllability analysis, observability analysis, basal ganglia model, feedback linearisation control, deep brain stimulation, clinical remedy, tremor control, Parkinson''s disease, feedback signal, closed‐loop controller, nonlinear BG model, feedback linearisation controller, two‐part controller, subthalamic nucleus stimulation, partial state feedback controller, globus pallidus internal stimulation, disease condition, delivered stimulation signal     

Sliding mode controller–observer pair for p53 pathway

A significant loss of p53 protein, an anti‐tumour agent, is observed in early cancerous cells. Induction of small molecules based drug is by far the most prominent technique to revive and maintain wild‐type p53 to the desired level. In this study, a sliding mode control (SMC) based robust non‐linear technique is presented for the drug design of a control‐oriented p53 model. The control input generated by conventional SMC is discontinuous; however, depending on the physical nature of the system, drug infusion needs to be continuous. Therefore, to obtain a smooth control signal, a dynamic SMC (DSMC) is designed. Moreover, the boundedness of the zero‐dynamics is also proved. To make the model‐based control design possible, the unknown states of the system are estimated using an equivalent control based, reduced‐order sliding mode observer. The robustness of the proposed technique is assessed by introducing input disturbance and parametric uncertainty in the system. The effectiveness of the proposed control scheme is witnessed by performing in‐silico trials, revealing that the sustained level of p53 can be achieved by controlled drug administration. Moreover, a comparative quantitative analysis shows that both controllers yield similar performance. However, DSMC consumes less control energy.Inspec keywords: control system synthesis, tumours, variable structure systems, observers, cancer, robust control, drugs, proteins, medical control systemsOther keywords: wild‐type p53, nonlinear technique, drug design, control‐oriented p53 model, control input, drug infusion, smooth control signal, dynamic SMC, zero‐dynamics, model‐based control design, input disturbance, controlled drug administration, sliding mode controller–observer pair, cancerous cells, antitumour agent, molecule based drug     

Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control‐based approach

Here, a direct adaptive control strategy with parametric compensation is adopted for an uncertain non‐linear model representing blood glucose regulation in type 1 diabetes mellitus patients. The uncertain parameters of the model are updated by appropriate design of adaptation laws using the Lyapunov method. The closed‐loop response of the plasma glucose concentration as well as external insulin infusion rate is analysed for a wide range of variation of the model parameters through extensive simulation studies. The result indicates that the proposed adaptive control scheme avoids severe hypoglycaemia and gives satisfactory performance under parametric uncertainty highlighting its ability to address the issue of inter‐patient variability.Inspec keywords: patient monitoring, adaptive control, diseases, Lyapunov methods, closed loop systems, medical control systems, patient treatment, medical computing, sugar, uncertain systems, blood, nonlinear control systems, physiological modelsOther keywords: blood glucose regulation, type 1 diabetic patients, adaptive parametric compensation control‐based approach, direct adaptive control strategy, nonlinear model, type 1 diabetes mellitus patients, uncertain parameters, appropriate design, adaptation laws, closed‐loop response, plasma glucose concentration, external insulin infusion rate, model parameters, adaptive control scheme, parametric uncertainty, inter‐patient variability