Active self-healing mechanisms for discrete dynamic structures

Proceedings of the Institution of Mechanical Engineers, Part G:

2017

Reconfigurable systems are the safe dynamical systems wherein the health of the control input and/or sensor output variables are continuously monitored and then they are reconfigured, if necessary, in an event of an unexpected fault detected online. This idea is applied, in particular, at the reconfigurable system where the number of control variables is more than the state variables considered to define its motion. In this paper, an adaptive pole placing controller is developed for use in such reconfigurable systems. Adaptive pole placing controller, in theory, is adaptive to take a fault size and retain the closed loop poles it assigns at fixed locations in the open left half plane of the complex plane. As a result, when the controller is not adaptive, it means that the pole perturbations could lead to catastrophes. However, to design adaptive pole placing controller for a reconfigurable system, fault size is required. Hence, the primary objective of the paper is to present a simple procedure that determines the fault size for tuning in the adaptive pole placing controller. Both direct and full-order Luenberger observer based state feedback adaptive pole placing controllers are presented. In situations where the adaptive pole placing controller is not possible, the fault size for which the reconfigurable system with a non-adaptive pole placing controller would transit from a stable to unstable system (referred as fault tolerant margin with respect to the non-adaptive pole placing controller) is also presented. Some of these features of this paper are illustrated by using the reconfigurable aircraft model available in the literature.

Section: Fault Detection and Quantificationmentioning

confidence: 99%

“…If the parameters in ΔA=BGA and ΔB=BΔB in equation (7) are estimated using an extended Kalman filter algorithm, 18 there is always an estimated value different from true value until convergence takes place. Hence, the closed loop poles are perturbed and the controller eventually becomes a non-APPC.…”

Section: Reconfigurable Systemsmentioning

confidence: 99%

Adaptive fault tolerant control for reconfigurable systems

Proceedings of the Institution of Mechanical Engineers, Part G:

2017

“…When m=1 (single input systems), the pole placement design procedure is given by Sujitjorn and Wiboonjaroen. 18…”

Section: State-space Realization Of a Pid Controllermentioning

confidence: 99%

“…The infinite eigenvector options available in multiple input systems, in the present case the square systems, corresponding to the fixed stable eigenvalues, are used to reduce the tracking errors in a nonoptimal sense. In other techniques where pole placement is used by using a PID controller, such as Gundas and Chang, 16 Seraj, 17 and Sujitjorn and Wiboonjaroen, 18 the eigenvector options in a nonsquare system to modify transients as well as to change the steady-state errors may require further investigations. That is, with PID, gain tuning by eigenvector options as in the case of proportional controllers may be possible with further investigations.…”

Section: Introductionmentioning

confidence: 99%

Proportional–integral–derivative controller family for pole placement

Proceedings of the Institution of Mechanical Engineers, Part C:

Gruber

2016

In this paper, linear time-invariant square systems are considered. A procedure to design infinitely many proportional–integral–derivative controllers, all of them assigning closed-loop poles (or closed-loop eigenvalues), at desired locations fixed in the open left half plane of the complex plane is presented. The formulation accommodates partial pole placement features. The state-space realization of the linear system incorporated with a proportional–integral–derivative controller boils down to the generalized eigenvalue problem. The generalized eigenvalue-eigenvector constraint is transformed into a system of underdetermined linear homogenous set of equations whose unknowns include proportional–integral–derivative parameters. Hence, the proportional–integral–derivative solution sets are infinitely many for the chosen closed-loop eigenvalues in the eigenvalue-eigenvector constraint. The solution set is also useful to reduce the tracking errors and improve the performance. Three examples are illustrated.

“…A procedure to solve these equations is presented in Ashokkumar and Iyengar. [32][33][34] Hence, the infinite set of controllers each with a different modal matrix but with fixed desired set of eigenvalues is derived. This procedure also accommodates partial eigenvalue assignment, 32 The 15 digits after the decimal point are taken to simulate aircraft loss of control using l, which requires precision to isolate the eigenvalues on the imaginary axis.…”

Section: Linear Functional Controllersmentioning

confidence: 99%

Nonlinear trajectory transcriptions for aircraft loss of control recovery

Proceedings of the Institution of Mechanical Engineers, Part I:

Gruber

2016

Aircraft loss of control may occur when the interpolated gain set is such that it destabilizes the linear aircraft. That is, when linear aircraft is not asymptotically stable, the nonlinear aircraft loss of control occurs. Even in cases where interpolation stabilizes the linear aircraft, loss of control may also occur when the gains are not reconfigured within the stability region associated with the controller. Hence, understanding nonlinear aircraft navigation and control algorithms using such controllers that originate from various linear design methods becomes a challenging problem. It prompts to simulate the nonlinear aircraft trajectories within the distorted stability regions of the linear controllers interpolated when each one of them is designed to regulate an equilibrium (or trim) point. In this article, the gain interpolation parameter that would lead to loss of control is presented. Then, techniques to avert the loss of control using nonlinear trajectory transcriptions are presented. A 3-degree-of-freedom aircraft model of Langelaan is considered for illustrations.