The minimization of roundoff noise subject to l2-norm dynamic-range scaling constraints in two-dimensional (2-D) state-space digital filters is considered by using joint error feedback and coordinate transformation optimization. An iterative approach for minimizing the roundoff noise under l2-norm dynamic-range scaling constraints is developed by jointly optimizing a scalar error-feedback matri...

The feedback synthesis of linear systems satisfying certain exponential bounds on their transient behavior is studied. We present sufficient conditions ensuring that there exists a state feedback matrix such that the closed loop system satisfies a desired exponential growth bound. Special interest is directed to the case of generating contraction semigroups, which under certain conditions can b...

This paper introduces a new method of intelligent control to control the Buck converter using newly developed small signal model of the pulse width modulation (PWM) switch. The new method uses recurrent supervised neural network to estimate certain parameters of the transformed system matrix [ A ~ ]. Then, a numerical algorithm used in robust control called linear matrix inequality (LMI) optimi...

In this paper, a closed-loop subspace identification approach through an orthogonal projection and subsequent singular value decomposition is proposed. As a by-product of this development, it explains why some existing subspace methods may deliver a bias in the presence of the feedback control and suggests a remedy to eliminate the bias. Furthermore, as the proposed method is a projection based...

In this paper, we have presented a simple method in order to solve the pole placement problem of linear output feedback systems with state space models. Pole placement is a control method assigned to arbitrary closed loop poles by state or output feedback. In linear systems, poles have influence on stability, system response, transient response, and band width. Pole placement methods are used i...

The design of an observer-based state feedback (OBSF) controller with guaranteed passivity properties for port-Hamiltonian systems (PHS) is addressed using linear matrix inequalities (LMIs). observer gain freely chosen and the LMIs conditions such that equivalent to control by interconnection input strictly passive (ISP) and/or output (OSP) zero detectable (ZSD) are established. It shown propos...

This paper studies the Lagrange stabilization of a class of nonlinear systems whose linear part has a singular system matrix and which have multiple periodic (in state) nonlinearities. Both state and output feedback Lagrange stabilization problems are considered. The paper develops a pseudo H∞ control theory to solve these stabilization problems. In a similar fashion to the Strict Bounded Real ...

Model predictive control (MPC) is a favored method for handling constrained linear control problems. Normally, the MPC optimization problem is solved on-line, but in ‘explicit MPC’ an explicit precomputed feedback law is used for each region of active constraints (Bemporad et al., 2002). In this paper we make a link between this and the ‘self-optimizing control’ idea of finding simple policies ...

in this paper, an adaptive attitude control algorithm is developed based on neural network for a satellite using four reaction wheels in a tetrahedron configuration. then, an attitude control based on feedback linearization control has been designed and uncertainties in the moment of inertia matrix and disturbances torque have been considered. in order to eliminate the effect of these uncertain...