Several path following algorithms based on the combination of three smooth penalty functions, the quadratic penalty for equality constraints and the quadratic loss and log barrier for inequality constraints, their modern counterparts, augmented Lagrangian or multiplier methods, sequential quadratic programming, and predictorcorrector continuation are described. In the first phase of this method...

This paper is about distributed derivative-based algorithms for solving optimization problems with a separable (potentially nonconvex) objective function and coupled affine constraints. A parallelizable method is proposed that combines ideas from the fields of sequential quadratic programming and augmented Lagrangian algorithms. The method negotiates shared dual variables that may be interprete...

This paper presents an active-set algorithm for large-scale optimization that occupies the middle ground between sequential quadratic programming (SQP) and sequential linear-quadratic programming (SL-QP) methods. It consists of two phases. The algorithm first minimizes a piecewise linear approximation of the Lagrangian, subject to a linearization of the constraints, to determine a working set. ...

MPC or model predictive control is representative of control methods which are able to handle inequality constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global asymptotic stability can be obtained; until recently, use of infinite...

The control of fluidized-bed operations processes is still one of the major areas of research due to the complexity of the process and the inherent nonlinearity and varying dynamics involved in its operation. There are varieties of problems in chemical engineering that can be formulated as NonLinear Programming (NLPs). The quality of the developed solution significantly affects the performa...

In this paper the consideration of asymmetric bounded signals (disturbances, inputs) in a general procedure for tuning infinite horizon model predictive controllers (MPC) with constraints is presented. These measures are stated by means of an asymmetric objective functional, instead of the standard l1 norm. The MPC is implemented with a terminal penalty to guarantee stability for all tuning par...

A new method is proposed for solving optimization problems with equality constraints and bounds on the variables. In the spirit of Sequential Quadratic Programming and Sequential Linearly-Constrained Programming, the new method approximately solves, at each iteration, an equality-constrained optimization problem. The bound constraints are handled in outer iterations by means of an Augmented Lag...

An iteration of the stabilized sequential quadratic programming method consists in solving a certain quadratic program in the primal-dual space, regularized in the dual variables. The advantage with respect to the classical sequential quadratic programming is that no constraint qualifications are required for fast local convergence (i.e., the problem can be degenerate). In particular, for equal...

We consider the use of the sequential quadratic programming (SQP) technique for solving the inequality constrained minimization problem min x f(x) subject to: g i (x) 0; i = 1; : : :; m: SQP methods require the use of an auxiliary function, called a merit function or line-search function, for assessing the steps that are generated. We derive a merit function by adding slack variables to create ...

Three-tank (3T) system is the most representative didactical equipment used as a bench mark system for system modeling, identification and control. A real target representing 3T system has been used for generating data that is used for developing a linear model based on autoregressive exogenous (ARX) method, and neuro-fuzzy (NF) network technique. The developed models have been used as an inter...