LMI Based Digital State Feedback Controller for a Wound Rotor Induction Drive with Guaranteed Closed Loop Stability

Author(s):  
D. Sivanandakumar ◽  
K. Ramakrishnan
2014 ◽  
Vol 898 ◽  
pp. 680-683
Author(s):  
Hai Yan Wang

The control theory has widely application in many fields such as industrial and agricultural. A class of see-saw system model will be studied in this paper. Using the theory of pole assignment, we will design the state feedback controller, such that the closed-loop system is asymptotically stable. At the same time, using the tool of MATLAB, the model of closed see-saw system will be simulated and analyzed. It reveals the state regularity of see-saw system.


2012 ◽  
Vol 546-547 ◽  
pp. 997-1002
Author(s):  
Hong Li ◽  
Shu Hui Shi ◽  
Ou Wu

This paper focuses on the problem of non-fragile robust passive control for a class of nonlinear singular systems which contain structure uncertainties and time delay. A memorial state feedback controller is considered, and the controller is constructed such that closed-loop systems are generalized quadratically stable and passive with dissipation. The algorithm is given for obtaining the maximum dissipation, at the same time, the maximum guaranteed dissipation controller is proposed. Numerical example is presented to show the validity and applicability of the proposed method.


2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Xiaoming Chen ◽  
Mou Chen ◽  
Jun Shen

The problem ofl1-induced state-feedback controller design is investigated for positive Takagi-Sugeno (T-S) fuzzy systems with the use of linear Lyapunov function. First, a novel performance characterization is established to guarantee the asymptotic stability of the closed-loop system withl1-induced performance. Then, the sufficient conditions are presented to design the required fuzzy controllers and iterative convex optimization approaches are developed to solve the conditions. Finally, one example is presented to show the effectiveness of the derived theoretical results.


2015 ◽  
Vol 9 (4) ◽  
pp. 413-425 ◽  
Author(s):  
Abrar Allag ◽  
Abdelhamid Benakcha ◽  
Meriem Allag ◽  
Ismail Zein ◽  
Mohamed Yacine Ayad

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Firas Turki ◽  
Hassène Gritli ◽  
Safya Belghith

This paper proposes a state-feedback controller using the linear matrix inequality (LMI) approach for the robust position control of a 1-DoF, periodically forced, impact mechanical oscillator subject to asymmetric two-sided rigid end-stops. The periodic forcing input is considered as a persistent external disturbance. The motion of the impacting oscillator is modeled by an impulsive hybrid dynamics. Thus, the control problem of the impact oscillator is recast as a problem of the robust control of such disturbed impulsive hybrid system. To synthesize stability conditions, we introduce the S-procedure and the Finsler lemmas by only considering the region within which the state evolves. We show that the stability conditions are first expressed in terms of bilinear matrix inequalities (BMIs). Using some technical lemmas, we convert these BMIs into LMIs. Finally, some numerical results and simulations are given. We show the effectiveness of the designed state-feedback controller in the robust stabilization of the position of the impact mechanical oscillator under the disturbance.


Author(s):  
Qinghui Du

The problem of adaptive state-feedback stabilization of stochastic nonholonomic systems with an unknown time-varying delay and perturbations is studied in this paper. Without imposing any assumptions on the time-varying delay, an adaptive state-feedback controller is skillfully designed by using the input-state scaling technique and an adaptive backstepping control approach. Then, by adopting the switching strategy to eliminate the phenomenon of uncontrollability, the proposed adaptive state-feedback controller can guarantee that the closed-loop system has an almost surely unique solution for any initial state, and the equilibrium of interest is globally asymptotically stable in probability. Finally, the simulation example shows the effectiveness of the proposed scheme.


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