Most industrial control systems consist of a significant number loops. Generally, large processes are divided into many interconnected subsystems affecting each other, thus creating multivariable known as multiple–input multiple–output (MIMO) process. Generalized Predictive Control (GPC) based algorithm is most suitable for MIMO systems. In this study, multivariate nonlinear (NL) GPC and discre...

Abstract This paper analyzes the feasibility of the generalized predictive control law under constraints on the input, output or other auxiliary signals that depend linearly on the system variables. These constraints are formulated as sets of linear equalities or inequalities; the control sequence is therefore elaborated based on a quadratic optimization problem. The feasibility issues are rela...

1. Abstract The objective of this paper is to report the results from the research being conducted in reconfigurable flight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft’s control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive ...

In this paper, based on the prediction control performances defined over one cycle or multiple cycles, two higher-order ILC schemes have been developed by extending the Generalized Predictive Control (GPC) method to the two-dimensional (2D) system. The dynamics of the ILC system along time and cycle is taken as a 2D system, and the proposed designs integrate optimally the design and the combina...

This paper presents an efficient optimization algorithm for mixed integer nonlinear programming (MINLP) problem resulting from multiple partially linearized (MPL) model based control of nonlinear hybrid dynamical system (NHDS). The algorithm uses structural information of the canonical MPL framework and derives comparatively easier quadratic programming (QP) primal problem as well as an MILP ma...

The process of VAC polymerization has the characteristics such as nonlinearity, time-varying, disturbance and time-delay, moreover, it can not be achieve continuous on-line detection of the vinyl acetate polymerization rate. The traditional control strategy can't acquire satisfactory result, so the implicit generalized predictive control (GPC) algorithm is applied in the control of polymerizati...

The handling of various input constraints in the self-tuning generalized predictive control (STGPC) problem of ARIMAX/ARMAX systems is considered. The methods based on the Lagrange multipliers and Lemke’s algorithm are used to solve the constrained optimization problem. A self-tuning controller is implemented in an indirect way, and the considered constraints imposed on the control input signal...

This manuscript contains technical results related to a particular approach for the design of Model Predictive Control (MPC) laws. The approach, named “generalized” terminal state constraint, induces the recursive feasibility of the underlying optimization problem and recursive satisfaction of state and input constraints, and it can be used for both tracking MPC (i.e. when the objective is to t...

This paper deals with the effect of small prediction horizon in Neural Generalized Predictive control. A different strategy is proposed to overcome the problem of estimation at each sampling instant. In this method the parameter are estimated at a large sampling interval and control increments are calculated at a smaller sampling interval. Simulation studies are presented to show the merits of ...

This paper presents an adaptive neural control design for a class of unknown nonlinear systems. Novel state variables and the corresponding transform are introduced, such that the statefeedback control of a pure-feedback system can be viewed as the output-feedback control of a canonical system. An adaptive predictor incorporated with a neural network observer is proposed to obtain the future sy...