ENGENHARIA DE CONTROLE E AUTOMAÇÃO - HISTÓRICO E PERSPECTIVAS

Um histórico sobre os cursos de Engenharia de Controle e Automação no Brasil, que iniciou com a implantação pioneira dessa formação na Universidade Federal de Santa Catarina em 1990, e que hoje se apresenta consolidada e em expansão por todo o território naciona

Local Stabilization of Time-Delay Nonlinear Discrete-Time Systems Using Takagi-Sugeno Models and Convex Optimization

A convex condition in terms of linear matrix inequalities (LMIs) is developed for the synthesis of stabilizing fuzzy state feedback controllers for nonlinear discrete-time systems with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is used to represent exactly the nonlinear system in a restricted domain of the state space, called region of validity. The proposed stabilization condition is based on a Lyapunov-Krasovskii (L-K) function and it takes into account the region of validity to determine a set of initial conditions for which the actual closed-loop system trajectories are asymptotically stable and do not evolve outside the region of validity. This set of allowable initial conditions is determined from the level set associated to a fuzzy L-K function as a Cartesian product of two subsets: one characterizing the set of states at the initial instant and another for the delayed state sequence necessary to characterize the initial conditions. Finally, we propose a convex programming problem to design a fuzzy controller that maximizes the set of initial conditions taking into account the shape of the region of validity of the T-S fuzzy model. Numerical simulations are given to illustrate this proposal

A LINEAR PROGRAMMING APPROACH FOR REGIONAL POLE PLACEMENT UNDER POINTWISE CONSTRAINTS

Abstract This paper considers the problem of control of discrete-time linear systems under several complicating features frequently encountered in practice : uncertain parameters in the model, additive noise, linear symmetrical state and input constraints. The main control design objective, beyond local stabilization, is to locate the closed-loop poles in a "good" region of the unit disc of the complex plane. The originality of the proposed approach is to use Linear Programming as the basic design tool. It is shown that the matrix conditions derived from positive invariance relations and from design constraints can be formulated as linear matrix equalities and scalar inequalities. The control design problem can then be solved by Linear Programming, with an objective function describing the search for a trade-off between several design objectives

A unified framework for linear constrained regulation problems

Abstract This paper presents some results on the ability to control time-invariant linear systems by linear state feedback under some constraints on the state vector or on the control vector. The proposed unified framework provides solutions for continuous-time systems as well as discrete-time systems. This approach relies on the positive invariance properties of some domains of the state-space for stable closed-loop systems

H[infinit] and H[sub2] design techniques for a class of prefilters

The design of a dynamic prefilter from the point of view of robust performance under structured uncertainty is considered. Synthesis methods are presented for the cases of H8 or H2 performance, and linear time-invariant (LTI) or linear time varying (LTV) uncertainty, all of which result in convex optimization problems across frequency. Methods to obtain finite-dimensional approximations are discussed. In the case of H8 performance and LTV uncertainty, the synthesis problem is reduced exactly to a finite dimensional linear matrix inequality in state space