Control Algorithm Architectures: PID, MPC, and Hybrid Approaches

The selection of the control algorithm is the single most consequential engineering decision in any closed-loop insulin delivery system. The field has converged on three dominant paradigms — PID-based, MPC-based, and hybrid compound control — each with distinct trade-offs in computational complexity, adaptability, and clinical safety margins, as documented across more than 50 patent filings spanning 2006 to 2026.

PID and Risk-Space PID (rPID)

Traditional PID controllers are reactive, using proportional, integral, and derivative terms calculated from the error between the measured glucose level and a target setpoint. Medtrum Technologies has extensively patented a risk-transformed variant called rPID, in which asymmetric blood glucose values in the raw physical space are mapped into an approximately symmetric risk space before control computation. This rPID approach retains the simplicity and robustness of classical PID while adding the precision advantages of risk-space transformation. The same risk-space concept is extended to MPC in corresponding rMPC filings from the same assignee.

Model Predictive Control (MPC) and Zone MPC

MPC is the more computationally sophisticated approach and has attracted major interest across both industry and academia. MPC explicitly uses a forward-looking physiological model to predict future glucose trajectories and optimise the insulin infusion rate over a prediction horizon, subject to safety constraints. The University of California Regents implemented zone MPC with daily periodic target-zone modulation: the controller strives to maintain an 80–140 mg/dL glucose zone during the day and a 110–220 mg/dL zone at night, with a 2-hour smooth transition between them. Diabeloop’s MPC-based controller determines a maximum allowable insulin injection amount and generates a delivery control signal based on this limit and the current required quantity, as disclosed in a 2024 patent filing.

“Zone MPC with diurnal target modulation maintains tighter glycaemic control during the day (80–140 mg/dL) while permitting a relaxed range at night (110–220 mg/dL) to reduce nocturnal hypoglycaemia risk — a clinically validated asymmetry established by the University of California’s periodic zone MPC controller.”

Hybrid Compound Control (cPID/cMPC)

Hybrid compound control represents the current frontier. Medtrum Technologies has patented a family of hybrid artificial pancreas algorithms that deeply combine PID and MPC: in the cPID variant, the input to the PID stage is the intermediate output of MPC, while in the cMPC variant, the input to MPC is the output of the PID controller. A further compound artificial pancreas algorithm calculates two independent insulin infusion amounts — designated I1 and I2 — from independent algorithm stages and then optimises them to produce a final infusion amount I3.

The University of California also contributed individualised controller schemes combining IMC-PID and MPC with personalised insulin feedback (IFB), calibrated using a priori patient basal insulin data. The Trustees of Boston University implemented an adaptive MPC in which a linear empirical input-output patient model is recursively updated online based on glucose measurements, minimising both subcutaneous insulin accumulation and control aggressiveness in an augmented objective function.

Insulin-on-Board Tracking and Pharmacokinetic Modelling

Accurate tracking of Insulin-on-Board (IOB) — the amount of previously delivered insulin still actively affecting blood glucose — is the most technically demanding sub-problem in closed-loop insulin delivery. Over-delivery relative to actual IOB is the primary mechanism of algorithmic hypoglycaemia, making this a patient safety issue as much as an engineering one.

Subcutaneous Absorption Rate Limits

Insulet Corporation addresses the subcutaneous absorption saturation problem by calculating an aggregate IOB amount over a first time period, determining whether this exceeds a maximum depot formation threshold, and carrying a residual forward to increase the subsequent individual IOB estimate. This approach corrects for the physical limitation that subcutaneous insulin absorption cannot exceed a maximum rate, preventing under-counting of effective IOB when large depot amounts are present.

Relative IOB and Dynamic Profile Customisation

Bigfoot Biomedical has patented a relative IOB approach: a processor computes a reference IOB value representing what a standard open-loop regimen would have delivered, and an automated IOB value representing what the closed-loop system has automatically dispensed, with the difference (relative IOB) used to guide subsequent dosing decisions. Insulet Corporation has also developed dynamic on-board insulin profile customisation, adapting IOB decay curves based on individual recent glucose history rather than population-average static profiles.

The residual active insulin problem in the context of user-initiated boluses is addressed by LifeScan IP Holdings, where a multi-model controller calculates system-computed bolus amounts and then adjusts for user-initiated bolus amounts, checking whether the user has subsequently entered a blood glucose reading to recalibrate IOB estimates.

Patient Digital Twins and Adaptive PK/PD Models

Pharmacokinetic/pharmacodynamic (PK/PD) modelling is embedded directly into closed-loop control in the patient digital twin approach by Medtronic MiniMed. Sensor glucose and meal data from recent days are used to fit a user-specific PK/PD model, which then computes updated controller parameters — enabling the controller to adapt to individual patient physiology over time. According to FDA guidance on adaptive algorithms in medical devices, this class of continuously learning system introduces specific regulatory considerations around algorithm change protocols and post-market surveillance.

Boston University implemented an adaptive MPC in which a linear empirical input-output patient model is recursively updated online based on glucose measurements, minimising both subcutaneous insulin accumulation and control aggressiveness in an augmented objective function. This represents the academic frontier for combining IOB pharmacokinetics with real-time model adaptation, a direction also encouraged by published research from Nature on closed-loop glucose control systems.

Hardware Implementations and Integrated Device Architecture

Beyond algorithms, the physical architecture of the closed-loop device is a critical design dimension. Systems range from loosely coupled multi-device configurations to fully integrated wearable platforms combining sensing and infusion in a single unit — each with distinct implications for patient burden, infection risk, and regulatory pathway.

Single-Insertion Integrated Platforms

Single-insertion platforms represent the most compact form factor. Medtrum Technologies has developed intelligently controlled miniature fully closed-loop artificial pancreas systems in which the infusion cannula itself serves dual roles: as the drug delivery channel and as an electrode for blood glucose sensing. The cannula wall electrodes and conductive-area electrodes allow analyte detection and insulin infusion from a single subcutaneous insertion point. The corresponding EP-jurisdiction grant confirms active status for this integrated design as of 2026.

Mechanical Infusion Drive Mechanisms

Medtrum Technologies has patented both a unilaterally driven closed-loop artificial pancreas — using a single-direction linear actuator and reset unit to precisely advance a piston-screw mechanism — and a bilaterally driven variant in which a power unit applies forces in two directions, enabling finer-resolution delivery steps and higher dosing efficiency. Becton Dickinson established foundational closed-loop architecture patents including intradermal delivery integration, with time-delay reduction as a key design objective: intradermal delivery reduces pharmacokinetic lag relative to subcutaneous delivery, as described in a 2009 patent filing.

Embedded Firmware Optimisation and Motion Sensing

Insulet Corporation’s embedded firmware dose optimisation uses a stepwise coarse-to-fine search across a discrete drug delivery amount space: a coarse pass narrows the solution range, and a refined pass identifies the cost-minimising delivery quantity, where the cost function evaluates predicted glucose and insulin trajectories using a recursive glucose model. This embedded optimisation approach avoids the need for continuous real-time convex optimisation solvers, enabling deployment on resource-constrained wearable processors — a critical consideration given the power and compute budgets of subcutaneous devices. According to standards published by ISO for software in medical devices (IEC 62304), embedded firmware of this class requires rigorous software lifecycle documentation.

Motion and activity sensing is integrated into dosing algorithms by Medtrum Technologies, where an onboard motion sensor detects physical activity status and feeds it as a variable factor into the TDD and current infusion algorithms, allowing the system to automatically account for exercise-induced changes in insulin sensitivity.

Dual-Drug and Multi-Drug Systems

Fully closed-loop dual-drug systems capable of delivering both insulin (hypoglycaemic) and glucagon (anti-hypoglycaemic) have been patented by Medtrum Technologies. This architecture uses independent infusion modules for each drug class, both governed by a shared algorithm-driven program module that determines which drug to administer based on the current blood glucose trajectory. Dexcom has addressed the integration of a continuous glucose sensor with an insulin delivery device and controller module, supporting manual, semi-automated, and fully automated operation.

Safety Constraints, Dosing Limits, and Fault Management

Safety enforcement is a non-negotiable engineering requirement in closed-loop insulin delivery because over-delivery can cause life-threatening hypoglycaemia within minutes. The patent dataset reveals five distinct safety mechanism categories, each addressing a different failure mode in the control loop.

Maximum Infusion Rate Enforcement

Maximum infusion rate enforcement is the primary safety mechanism. Medtronic MiniMed has extensively patented methods for calculating user-specific insulin infusion upper limits based on fasting blood glucose values, total daily insulin, and insulin delivered during fasting periods. When the controller-computed infusion rate exceeds the patient-specific maximum, the system substitutes a rate capped at that limit. LifeScan IP Holdings similarly addresses maximum dosing from a bolus-rate computation standpoint, computing a maximum delivery rate from default basal, temporary basal, and extended bolus rate data.

Closed-Loop Entry Safeguards and Data Gap Detection

Closed-loop entry safeguards govern when a system transitions from open-loop to closed-loop operation. Medtronic MiniMed’s safeguarding techniques require analysis of CGM calibration factors and corresponding timestamp data before the system is permitted to enter closed-loop mode. If more than 60 minutes of CGM data packets are missing, the system reverts to open-loop delivery at a pre-programmed basal rate. The same patent family details a PID-IFB (Insulin Feedback) closed-loop algorithm with IOB compensation running as an additional safety overlay. Regulatory guidance from FDA on automated insulin delivery systems specifically addresses CGM data integrity requirements as a precondition for closed-loop operation.

“If more than 60 minutes of CGM data packets are missing, Medtronic MiniMed’s system automatically reverts to open-loop delivery at a pre-programmed basal rate — a hard safety constraint that illustrates the non-negotiable role of sensor data integrity in closed-loop insulin delivery.”

Multi-Module Redundancy and Failover

Multi-controller redundancy and automatic failover is addressed by Medtrum Technologies in its distributed control architecture, in which detection, infusion, and electronic modules each contain their own embedded control units. Different modules assume control priority based on operational conditions, preventing single-point failure from compromising insulin delivery. This multi-module approach aligns with IEC 60601-1 safety requirements for medical electrical equipment, as documented by ISO.

Risk-Based Delivery Transformation and Dynamic Target Setpoints

DexCom’s approach uses a model-match evaluator that quantifies the degree to which recent glucose measurements are inconsistent with recent insulin — a discrepancy indicator for potential sensor error or patient metabolic disturbance — and then adjusts insulin delivery rate based on quantified hyper- or hypoglycaemic risk, as described in a 2026 patent filing. Medtronic MiniMed addresses aggressive initial dosing during closed-loop startup with a dynamic final target glucose value that decreases gradually toward the setpoint during startup, preventing the large initial error from triggering an over-aggressive insulin bolus.

Patent Landscape: Key Players and Emerging Innovation Trends

The closed-loop automated insulin delivery patent landscape is dominated by a small number of highly active assignees, each with a differentiated technical focus area. Understanding the landscape is essential for freedom-to-operate analysis, white-space identification, and competitive benchmarking in R&D strategy.

Dominant Assignees by Technical Focus

• Medtrum Technologies Inc. is by far the most prolific in this dataset, with over 15 distinct patent filings covering rPID/rMPC algorithms, hybrid compound algorithms, integrated single-insertion AP hardware, bilateral/unilateral drive mechanisms, multi-drug dual infusion, personalised gain-coefficient systems, motion-sensor integration, and multi-module redundant architectures. Their filings span 2018 to 2026, with active status in EP and WO jurisdictions.
• Medtronic MiniMed contributes major innovations in closed-loop safeguarding techniques, maximum infusion rate enforcement, PID-IFB control algorithms, dynamic target setpoint management, and patient digital twin-based PK/PD parameter adaptation.
• Insulet Corporation focuses on IOB management (specifically subcutaneous absorption rate limits), embedded firmware dose optimisation using coarse-to-fine search, and dynamic personalised IOB profile customisation. Their Omnipod platform is the commercial backdrop for these filings.
• The Regents of the University of California pioneered zone MPC and time-varying daily target range modulation for AP applications, establishing the mathematical framework used by several commercial implementers.
• Becton Dickinson established foundational closed-loop architecture patents including intradermal delivery integration, emphasising time-delay reduction as a controller performance lever.
• Diabeloop contributes closed-loop blood glucose control systems built on MPC with maximal allowable insulin injection constraints.
• Bigfoot Biomedical and Eli Lilly contribute relative IOB computation methods and TDD tracking/filtering techniques respectively, addressing the long-standing challenge of insulin-on-board accuracy.
• Harvard University and Boston University represent the academic frontier, with iterative learning control using sparse measurements and adaptive recursive MPC with augmented objective functions.

Six Emerging Innovation Trends

Innovation trends visible across the patent dataset include: (1) increasing integration of sensing and infusion hardware to a single-insertion platform; (2) shift from static population-average pharmacokinetic parameters toward individually adaptive patient models; (3) risk-space transformation of glucose variables to improve asymmetric control; (4) dual-drug (insulin + glucagon) fully closed-loop systems; (5) embedded optimisation via coarse-to-fine search enabling MPC on wearable processors; and (6) digital twin personalisation of controller parameters using recent sensor and meal data. These trends are consistent with the broader direction of personalised medicine as documented by WHO in its global diabetes action plan.

The geographic distribution of filings — spanning WO, EP, US, CN, JP, KR, AU, RU, ES, TW, and CA jurisdictions — reflects the global commercial interest in artificial pancreas technology and signals that any freedom-to-operate analysis must account for multi-jurisdictional coverage. Patent databases maintained by WIPO provide the authoritative international filing record for cross-jurisdictional searches in this technology area.