Explicit Nonlinear MPC for Fault Tolerance Using Interacting Multiple Models

Hill, Elyse; Gadsden, S. Andrew; Biglarbegian, Mohammad

doi:10.1109/taes.2021.3065089

Cited by 12 publications

(2 citation statements)

References 29 publications

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“…Many of these studies focus on FDD only and do not attempt to integrate controllers for task recovery. One of the few exceptions is the work of Hill et al. (2021) , where a non-linear Model Predictive Controller is applied to recover from reaction wheel failures that are identified through an UKF-based IMM for satellite maneuvering; an approach that is similar to our proposed strategy.…”

Section: Related Workmentioning

confidence: 99%

Cable failure tolerant control and planning in a planar reconfigurable cable driven parallel robot

et al. 2023

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The addition of geometric reconfigurability in a cable driven parallel robot (CDPR) introduces kinematic redundancies which can be exploited for manipulating structural and mechanical properties of the robot through redundancy resolution. In the event of a cable failure, a reconfigurable CDPR (rCDPR) can also realign its geometric arrangement to overcome the effects of cable failure and recover the original expected trajectory and complete the trajectory tracking task. In this paper we discuss a fault tolerant control (FTC) framework that relies on an Interactive Multiple Model (IMM) adaptive estimation filter for simultaneous fault detection and diagnosis (FDD) and task recovery. The redundancy resolution scheme for the kinematically redundant CDPR takes into account singularity avoidance, manipulability and wrench quality maximization during trajectory tracking. We further introduce a trajectory tracking methodology that enables the automatic task recovery algorithm to consistently return to the point of failure. This is particularly useful for applications where the planned trajectory is of greater importance than the goal positions, such as painting, welding or 3D printing applications. The proposed control framework is validated in simulation on a planar rCDPR with elastic cables and parameter uncertainties to introduce modeled and unmodeled dynamics in the system as it tracks a complete trajectory despite the occurrence of multiple cable failures. As cables fail one by one, the robot topology changes from an over-constrained to a fully constrained and then an under-constrained CDPR. The framework is applied with a constant-velocity kinematic feedforward controller which has the advantage of generating steady-state inputs despite dynamic oscillations during cable failures, as well as a Linear Quadratic Regulator (LQR) feedback controller to locally dampen these oscillations.

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Section: Related Workmentioning

confidence: 99%

Cable failure tolerant control and planning in a planar reconfigurable cable driven parallel robot

et al. 2023

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“…Though comprehensive, the methods used in [22] did not consider use of an SMC in the design, leaving room for investigation. Another work developed an explicit nonlinear model predictive control (eNMPC) based on an interacting multiple model (IMM) to tolerate actuator faults for a nonlinear spacecraft system [23].…”

Section: Introductionmentioning

confidence: 99%

Tube-Based Model Predictive Control Of Small Satellite Systems With Uncertainty Dynamics

Hill¹,

Biglarbegian²,

Gadsden³

2021

Progress in Canadian Mechanical Engineering. Volume 4

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In this paper, two tube-based model predictive control algorithms were developed using sliding mode control to regulate the attitude of a simulated CubeSat system. Incorporating sliding mode techniques increased the robustness of tube-based model predictive control by minimizing the uncertainty of the system in the presence of a disturbance. The proposed controllers' performances were evaluated against a traditional tube-based approach and measured in terms of root mean squared values on state errors and control efforts. Results indicate the effectiveness of the developed controllers over traditional tube-based methods for attitude control of small satellite systems, successfully extending this approach and opening an avenue for future development.Model predictive control; small satellites; uncertainty dynamics; mathematical modelling I.

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