Multivariable predictive PID control for quadruple tank

In this paper multivariable predictive PID controller has been implemented on a multi-inputs multi-outputs control problem i.e., quadruple tank system, in comparison with a simple multiloop PI controller. One of the salient feature of this system is an adjustable transmission zero which can be adjust to operate in both minimum and non-minimum phase configuration, through the flow distribution to upper and lower tanks in quadruple tank system. Stability and performance analysis has also been carried out for this highly interactive two input two output system, both in minimum and non-minimum phases. Simulations of control system revealed that better performance are obtained in predictive PID design

Advances in model identification using the block-oriented exact solution technique in a predictive modeling framework

Obtaining an accurate model has always been a challenging objective in implementation of Model Predictive Control, especially for nonlinear processes. Part of this work here proposed a model building methodology for a complex block-oriented process, namely a Hammerstein-Wiener system in order to meet such a demand. It is a general system of the more simple structures which are known as Hammerstein and Wiener. This methodology uses sequential step test training data determined from an optimal experimental design and simultaneously estimates all the model coefficients under nonlinear least squares objective function. It is evaluated using four process examples and is compared with a recently proposed method in three of them. Even with less frequent sampling, the proposed method is demonstrated to have advantages in simplicity, the ability to model non-invertible systems, the ability to model multiple input and non-minimum phase processes, and accuracy.;This class of modeling method is also being applied to model normal operation plant data. The common problem seen in this type of dataset including high multi-collinearities of the inputs and low signal to noise ratios for the outputs inhibit modelers to acquire cause and effect relationship. The second part of the work here is to introduced this modeling approach that is capable of developing accurate cause and effect models. It is a special application of the Wiener block-oriented system and the unique and powerful attributes of this approach over existing techniques are demonstrated in a mathematically simulated processes and real processes

Automatic Flight Control Systems

The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

Self-Aware Thermal Management for High-Performance Computing Processors

Editor's note: Thermal management in high-performance multicore platforms has become exceedingly complex due to variable workloads, thermal heterogeneity, and long, thermal transients. This article addresses these complexities by sophisticated analysis of noisy thermal sensor readings, dynamic learning to adapt to the peculiarities of the hardware and the applications, and a dynamic optimization strategy. - Axel Jantsch, TU Wien - Nikil Dutt, University of California at Irvine