In this paper an approach to design adaptive proportional-integral (PI) controllers, for SISO systems, based on sliding window principal components analysis (PCA) is presented. Closed-loop control can be formulated and implemented within the reduced space defined by a PCA model. This PCA controller, results in an integral controller, which can be used as an inferential controller for linear or nonlinear systems. The main contributions of the paper are: a) the proposed architecture and the adaptive mechanism based on online sliding window PCA; b) the incorporation of a proportional action and an integral anti-windup mechanism on the classical integral PCA controller. Some experimental results, obtained with a nonlinear system (three tank benchmark Amira DTS200) are presented, showing the controller performance.

 Using a supermarket refrigeration system as an illustrative example, the paper postulates that by appropriately utilising knowledge of plant operation, the plant wide performance can be optimised based on a small set of variables. Focusing on steady state operations, the total system performance is shown to predominantly be influenced by the suction pressure. Employing appropriate performance function leads to conclusions on the choice of set-point for the suction pressure that are contrary to the existing practice. Analysis of the resulting data leads to a simple method for finding optimal pressure set-point for given load situations.

 This paper deals with the tuning of the parameters of a particular type of event-based PI controller based on send- on-delta (deadband) sampling. In particular, by exploiting the stabilizing region of the parameters, a new tuning rule which aims at minimizing the step response settling time is presented. Results are compared with well-known tuning rules devised for standard (continuous-time) PI controllers. Simulation and experimental results show the effectiveness of the proposed tuning rule.

 The aim of this paper is to present a robust tuning method of two-degree-of-freedom (2DoF) proportional integral (PI) controllers for integrating controlled processes. This is based on the use of a model reference optimization procedure with servo and regulatory closed-loop transfer functions targets. The designer is allowed to deal with the performance/robustness trade-off of the closed-loop control system by specifying the desired robustness level through selecting a maximum sensitivity in the range from 1.4 to 2.0. In addition, a smooth servo/regulatory performance combination is obtained by forcing both closed-loop transfer functions to perform as closely as possible to non-oscillatory dynamic targets. Controller tuning equations that guarantee the design robustness level are provided for integrating second-order plus dead-time (ISOPDT) models with normalized dead-times from 0.1 to 2.0, and integrating plus dead-time (IPDT) models. The robustness of the control system is analyzed. Comparative examples show the effectiveness of the proposed tuning method.

 In this work, a model predictive control (MPC) synthesis is proposed to regulate, in the presence of naturally present state and input constraints, the thickness of falling film in the vertical tube, modelled by the Kuramoto-Sivashinsky (K-S) equation. The infinite-dimensional state space representation is developed and an exact transformation modifies the boundary control problem into the distributed control problem. The appropriate analysis of K-S spectral operator reveals dissipative structure of the linearized operator which benefits from the applicability of spectral decomposition for the control purpose. The model predictive control synthesis utilizes the finite dimensional representation of the K-S PDE state in the formulation of the optimization functional, while the infinite dimensional K-S PDE state constraints are appropriately defined and cast in a form of constrained quadratic optimization. The simulation study evaluates the performance of proposed methods which achieves both stabilization of the thin film thickness and obeys inputs and states constraints.

 This paper proposes a simple yet effective control algorithm for a platoon of car-like robots. The formation used is a line, leader-follower formation, i. e. each robot is a follower for the previous robot and a leader for the next robot. The formation is implemented using speed measurements from optical encoders and distance measurements from image processing, but there is no communication between robots. String stability analysis on the resulting formation is performed. The results of the proposed method are verified by both simulations in Matlab(R) as well as measured data from the actual mobile robots.