Showing papers by "Gabriele Pannocchia published in 2005"

Offset‐free receding horizon control of constrained linear systems

Abstract: The design of a dynamic state feedback receding horizon controller is addressed, which guarantees robust constraint satisfaction, robust stability and offset-free control of constrained linear systems in the presence of time-varying setpoints and unmeasured disturbances. This objective is obtained by first designing a dynamic linear offset-free controller and computing an appropriate domain of attraction for this controller. The linear (unconstrained) controller is then modified by adding a perturbation term, which is computed by a (constrained) robust receding horizon controller. The receding horizon controller has the property that its domain of attraction contains that of the linear controller. In order to ensure robust constraint satisfaction, in addition to offset-free control, the transient, as well as the limiting behavior of the disturbance and setpoint need to be taken into account in the design of the receding horizon controller. The fundamental difference between the results and the existing literature on receding horizon control is that the transient effect of the disturbance and set point sequences on the so-called “target calculator” is explicitly incorporated in the formulation of the receding horizon controller. An example of the control of a continuous stirred-tank reactor is presented. © 2005 American Institute of Chemical Engineers AIChE J, 2005

A Candidate to Replace PID Control: SISO-Constrained LQ Control

Abstract: It is commonly believed that for single-input/single-output (SISO) systems, well-tuned proportional, integral, derivative (PID) controllers work as well as model-based controllers and that PID controllers are more robust to model errors. In this paper we present a novel offset-free constrained linear quadratic (LQ) controller for SISO systems, which is implemented in an efficient way so that the total controller execution time is similar to that of a PID. The proposed controller has three modules: a state and disturbance estimator, a target calculation, and a constrained dynamic optimization. It is shown that the proposed controller outperforms PID both in setpoint changes and disturbance rejection, it is robust to model errors, it is insensitive to measurement noise, and it handles constraints better than common anti-windup PID. Tuning the proposed controller is simple. In principle there are three tuning parameters to choose, but in all examples presented only one was actually varied, obtaining a clear and intuitive effect on the closed-loop performance. © 2005 American Institute of Chemical Engineers AIChE J, 51: 1178 –1189, 2005

SISO model predictive controller

Abstract: A method of predictive control for a single input, single output (SISO) system, including modeling the SISO system with model factors, detecting output from the SISO system, estimating a filtered disturbance from the output, determining a steady state target state from the filtered disturbance and a steady state target output, populating a dynamic optimization solution table using the model factors and a main tuning parameter, and determining an optimum input from the dynamic optimization solution table. Determining an optimum input includes determining a time varying parameter, determining a potential optimum input from the time varying parameter, and checking whether the potential optimum input is the optimum input.

How to Use Simplified Dynamics in Model Predictive Control of Superfractionators

Abstract: In this paper, issues associated with the application of model predictive control algorithms to the product quality control of superfractionator columns are addressed Full-order and reduced-order