Abstract— The pole placement is one of the most important methods for designing controller for linear systems. In this paper work a procedure for solving the pole-placement problem for a linear time-invariant single-input/single output (SISO) systems by state-derivative feedback is described. Pole placement design to place all closed-loop poles at desired locations. In this paper, we shall prov...

It is being proposed in this paper a computational algorithm for acquiring the output feedback gain matrix in linear systems stabilization problems by regional pole placement in LMI regions. The output feedback controller is obtained through the solution of the coupled Sylvester equations. It is shown the existence of output feedback matrix providing conditions in which this problem has a solut...

In this paper, the pole placement controller based on the Robust Internal-loop Compensator(RIC) structure, which has inherent structural equivalence to disturbance observer, is proposed to control a linear positioning system. This controller has the advantage to easily select controller gains by using pole placement without loss of that of original RIC structure. The principal is to construct t...

A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...

Starting from a continuous time linear time-invariant system, a linearly similar variant of the Nagy–Foias model of the main operator of the system is constructed. A pole placement result, expressed in terms of invertibility of a certain Toeplitz operator, is obtained by applying this model. A numerical example of pole placement is given. Copyright c ©2005 IFAC

The pole placement (PP) technique for design of a linear state feedback control system requires specification of all the closed-loop pole locations even though only a few poles dominate the system’s transient response characteristics. The linear quadratic regulator (LQR) method, on the other hand, optimizes the system transient response and does not directly impose the location of the dominant ...