Robotics

FTC

ActivePublished: 4 May 2026Updated: 4 May 2026Published

Key innovation

Designing control systems that maintain required stability and performance properties in the presence of sensor, actuator, or plant component faults.

How it works

Active FTC: (1) the FDI module monitors input and output signals and compares them against a nominal model, (2) the generated residual exceeds a threshold → fault detection, (3) isolation identifies the faulty component, (4) the reconfiguration mechanism selects a new controller (from a controller bank or via online adaptation) and/or reallocates control to healthy actuators. Passive FTC: a robust controller (e.g. H∞, sliding mode, μ-synthesis) is designed offline for the worst case within a defined fault set and requires no FDI.

Problem solved

Classical control systems designed under the assumption of full component health lose stability or performance when an actuator, sensor, or plant fault occurs. FTC provides systematic methods for designing controllers that tolerate a defined set of faults without requiring immediate system shutdown.

Components

Fault Detection and Diagnosis (FDD)Fault detection and isolation (a necessary condition for Active FTC).

Module observing plant signals to detect, isolate, and identify a fault. Implemented via state observers, Kalman filters, parity equations, or data-driven classifiers.

Official

Reconfiguration MechanismAdapts the controller to new plant conditions following a fault.

Component that alters controller structure or parameters after a fault is detected. Can be controller switching from a bank (multiple model), online parameter adaptation, or control allocation reassignment.

Official

Control AllocationRedistribution of control among functional actuators.

Mapping of desired forces/torques from a high-level controller onto individual actuator commands, accounting for their current availability and constraints. Critical in actuator-redundant systems (drones, redundant manipulators).

Official

Robust Baseline ControllerTolerates minor faults without active reconfiguration.

Nominal controller designed with a robustness margin (H∞, μ-synthesis, sliding mode) tolerating a predefined small-fault set without reconfiguration. The sole component in Passive FTC.

Official

Implementation

Implementation pitfalls

False FDI AlarmsHigh

Overly aggressive thresholds in the FDI module trigger unnecessary reconfigurations from measurement noise or disturbances, degrading control performance.

Fix:Apply appropriate residual filtering, hypothesis-based statistical tests (CUSUM, GLR), threshold hysteresis, and disturbance models.

Detection Delay vs. StabilityCritical

A slow FDI can let the plant leave the new controller's region of attraction before reconfiguration, leading to instability.

Fix:Analysis of the Maximum Detection and Decision Time (MDDT), with baseline controller design incorporating additional robustness margin for the pre-reconfiguration period.

Actuator saturation after reallocationHigh

After actuator loss, the remaining actuators must take on larger control values and may persistently saturate, destabilizing the system.

Fix:Control allocation with explicit constraint handling (QP, weighted pseudoinverse), reference graceful degradation, anti-windup in the controller.

Loss of observability following sensor failureHigh

Sensor loss may render part of the state unobservable — observer-based controllers then stop working correctly.

Fix:Observability analysis across all fault scenarios, sensor redundancy, hybrid observers utilizing alternative measurements.

Evolution

1971

Beard – Failure Accommodation

Inflection point

R. V. Beard publishes the MIT thesis "Failure Accommodation in Linear Systems Through Self-Reorganization" — regarded as the first formal work on fault-tolerant control.

1985

SIFT and FTMP — fault-tolerant avionics systems

The SIFT (Software-Implemented Fault Tolerance) and FTMP (Fault-Tolerant Multiprocessor) architectures demonstrate fault tolerance in avionics — the foundation of later fly-by-wire systems.

1997

Patton – "Fault-Tolerant Control Systems: The 1997 Situation"

Inflection point

The IFAC SAFEPROCESS survey by Patton consolidates terminology (Active vs Passive FTC, FDI vs FDD) and becomes the canonical reference of the field.

2003

Blanke – "Diagnosis and Fault-Tolerant Control"

The monograph by Blanke, Kinnaert, Lunze, Staroswiecki becomes the standard academic textbook on FTC (subsequent editions 2006, 2016).

2008

Zhang & Jiang bibliographic review

Y. Zhang and J. Jiang publish "Bibliographical review on reconfigurable fault-tolerant control systems" in Annual Reviews in Control — the most-cited review of the field.

Bibliographical review on reconfigurable fault-tolerant control systems (paper)

2014

FTC for quadrotors after motor loss

Inflection point

M. W. Mueller and R. D'Andrea (ETH) demonstrate quadrotor flight after the loss of one, two, or three motors — a landmark experimental FTC work in aerial robotics.

Stability and control of a quadrocopter despite the complete loss of one, two, or three propellers (paper)

2020

Data-driven and learning-based FTC

Rise of machine-learning-based methods (deep learning, reinforcement learning, neural network observers) for fault detection and adaptive controller reconfiguration.