Robust pole location by parameter dependent state feedback control

Author(s):  
V.J.S. Leite ◽  
V.F. Montagner ◽  
P.L.D. Peres
2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
P. Bumroongsri

An offline model predictive control (MPC) algorithm for linear parameter varying (LPV) systems is presented. The main contribution is to develop an offline MPC algorithm for LPV systems that can deal with both time-varying scheduling parameter and persistent disturbance. The norm-bounding technique is used to derive an offline MPC algorithm based on the parameter-dependent state feedback control law and the parameter-dependent Lyapunov functions. The online computational time is reduced by solving offline the linear matrix inequality (LMI) optimization problems to find the sequences of explicit state feedback control laws. At each sampling instant, a parameter-dependent state feedback control law is computed by linear interpolation between the precomputed state feedback control laws. The algorithm is illustrated with two examples. The results show that robust stability can be ensured in the presence of both time-varying scheduling parameter and persistent disturbance.


Author(s):  
Emre Kemer ◽  
Hasan Başak ◽  
Emmanuel Prempain

This paper proposes two different [Formula: see text]-state-feedback controller synthesis algorithms for uncertain linear, time-varying, switched systems. The synthesis algorithms are based on a dwell-time approach, which makes use of time-varying parameter-dependent Lyapunov functions. The control laws consist of state-feedback controllers that are switched according to external signals. The proposed synthesis algorithms are then employed to design switched [Formula: see text]-state-feedback control laws for the longitudinal dynamics of the ADMIRE fighter benchmark model. The results obtained in simulation show the merits of the proposed approach.


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