Predictive Control of a helicopter model with tolerance to actuator faults

Abstract

Predictive Control formulations can be designed with nominal asymptotic stability guarantees, provided that the associated optimization problem is feasible at each sampling time. However, model-plant mismatches, external perturbations or faults may cause the optimization to become infeasible. Such a problem motivates the development of techniques aimed at recovering feasibility without violating hard physical constraints imposed by the nature of the plant. This paper investigates the possible advantages of employing a policy of setpoint management to circumvent infeasibility problems in a Predictive Control framework. The investigation is mainly concerned with robustness of the controller regarding actuator faults that can be modelled as a change in the allowed excursion of the control signal. The results obtained with the proposed setpoint management technique are compared to the default solution provided by the adopted computational toolbox in case of infeasibility. An application involving a nonlinear simulation model of a laboratory helicopter with three degrees of freedom is presented.

A Review on Fault Diagnosis and Fault Tolerant Control Methods for Single-rotor Aerial Vehicles

“…Afonso et al [5] investigated a predictive control method for actuator faults. The main target is to find a new setpoint x ref (k) at each time k in order to make the problem feasible and to progressively steer the system state towards the original setpoint x ref .…”

Fault diagnosis and fault tolerant control methods for manned and unmanned helicopters: A literature review

“…Based on a bank of pre-defined sensor and actuator fault signatures, Rago et al [48] proposed a specific Kalman filter able to simultaneously detect, isolate and accommodate fault according to the selection of pre-defined gains associated to appropriate pre-defined sensor and actuator fault signatures. Other methods include fault tree analysis [85], adaptive control [86], [87], predictive control [88], adaptive sliding mode backstepping technology [89], fuzzy logic [32], fuzzy feedforward and quantum control [90].…”

Integrated fault‐tolerant control for a 3‐DOF helicopter with actuator faults and saturation

“…Many FE/FTC designs for the Quanser 3-DOF helicopter model have also been published [18][19][20][21][22][23]. [18] proposes an adaptive sliding mode observer (SMO) for actuator fault estimation for a Lipschitz nonlinear helicopter model without uncertainty and external disturbance.…”

“…In their work the faults are estimated with ultimately bounded errors and FTC is out of its scope. [19] presents an improved robust model predictive FTC design considering a linear 3-DOF helicopter system with uncertainty, disturbance and an actuator fault. However, model predictive control involves online optimisation and their work does not include FE.…”

“…Moreover, the adaptive method is incorporated with the SMC to avoid the requirement of a priori knowledge of the perturbation bounds. Compared with model predictive FTC [19], adaptive FTCs [20][21][22], and backstepping sliding mode FTC [23], the proposed FTC is easier to design and implement without online optimisation and system decomposition, and the FE observer and FTC controller gains are obtained using a single-step LMI formulation.…”