There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

System Identification I

This paper provides an overview of the recent developments in data-based techniques focused on modern industrial applications. As one of the hottest research topics for complicated processes, the data-based techniques have been rapidly developed over the past two decades and widely used in numerous industrial sectors nowadays. The core of data-based techniques is to take full advantage of the huge amounts of available process data, aiming to acquire the useful information within. Compared with the well-developed model-based approaches, data-based techniques provide efficient alternative solutions for different industrial issues under various operating conditions. The main objective of this paper is to review and summarize the recent achievements in data-based techniques, especially for complicated industrial applications, thus providing a referee for further study on the related topics both from academic and practical points of view. This paper begins with a brief evolutionary overview of data-based techniques in the last two decades. Then, the methodologies only based on process measurements and the model-data integrated techniques will be further introduced. The recent developments for modern industrial applications are, respectively, presented mainly from perspectives of monitoring and control. The new trends of data-based technique as well as potential application fields are finally discussed.

Data-Based Techniques Focused on Modern Industry: An Overview

In this paper, we present two novel algorithms to realize a finite dimensional, linear time-invariant state-space model from input-output data. The algorithms have a number of common features. They are classified as one of the subspace model identification schemes, in that a major part of the identification problem consists of calculating specially structured subspaces of spaces defined by the input-output data. This structure is then exploited in the calculation of a realization. Another common feature is their algorithmic organization: an RQ factorization followed by a singular value decomposition and the solution of an overdetermined set (or sets) of equations. The schemes assume that the underlying system has an output-error structure and that a measurable input sequence is available. The latter characteristic indicates that both schemes are versions of the MIMO Output-Error State Space model identification (MOESP) approach. The first algorithm is denoted in particular as the (elementary MOESP scheme)...

Subspace model identification-Part 1. The output-error state-space model identification class of algorithms

Faced with environmental issues caused by fossil fuel burning in the industrial and transportation sectors, innovations towards cleaner solutions to replace the ever diminishing fossil fuels have been the focus of not only researchers but governments all around the world. The hybrid electric vehicle (HEV) technology is the result of the desire to have vehicles with a better fuel economy and lower tailpipe emissions to meet the requirements of environmental policies as well as to absorb the impact of rising fuel prices. The objectives are met by combining a conventional internal combustion engine (ICE) with one or more electric motors powered by a battery pack that can be charged using an on-board generator and the regenerative braking technology to power the transmission. The challenge is to develop an efficient energy management strategy (EMS) to satisfy the objectives while not having a reduced vehicle performance. In this paper, EMSs that are proposed and developed in the recent years are revisited and reviewed. Additionally, the Plug-in HEV is discussed in a new perspective from the EMS point of view. The through-the-road (TtR) HEV with in-wheel motors (IWM) is a fairly new concept in the HEV design that features less complicated configuration with reduced hardware requirements and lower cost. Recent research findings are evaluated throughout this paper leading to a hypothetical TtR HEV materialization. A thorough discussion is made encompassing the advantages and disadvantages of the concept, its performance compared to conventional HEVs and the way forward.

A review on hybrid electric vehicles architecture and energy management strategies

In this paper, Self Tuning Fuzzy PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in a linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from experimental works. Fuzzy logic is used to tune each parameter of PID controller. Through simulation in Matlab by selecting appropriate fuzzy rules are designed to tune the parameters Kp, Ki, and Kd of the PID controller, the performance of the hydraulic system has improved significantly compare to conventional PID controller.

Application of self-tuning fuzzy pid controller on industrial hydraulic actuator using system identification approach

The objective of this paper is to compare the time specification performance between two conventional controllers for an inverted pendulum system. The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart’s position. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. Two controllers are presented such as Linear‐Quadratic‐Regulator (LQR) and Proportional‐Integral‐Derivatives (PID) controllers for controlling the linearized system of inverted pendulum model. Simulation study has been done in Matlab simulink environment shows that both controllers are capable to control multi output inverted pendulum system successfully. The result shows that LQR produced better response compared to PID control strategies and is presented in time domain.

Performance comparison between lqr and pid controllers for an inverted pendulum system

This paper presents results for a tomographic system using an array of electrodynamic sensors. Sensitivity maps are derived for the individual sensors and then used by a back-projection algorithm to calculate concentration profiles from measured sensor values. Limitations in linearity over the sensing area are reduced by applying a filter to the images. The filtered back-projection algorithm is tested both on uniformly and on artificially produced non-uniformly distributed solids' flows.

https://iopscience.iop.org/article/10.1088/0957-0233/8/2/014/pdf

Concentration profiles of dry powders in a gravity conveyor using an electrodynamic tomography system

This paper presents the performance of different control approaches that consist of conventional, modern and intelligent controller that employed in a cruise control system. The cruise control system is one of the most enduringly popular and important laboratory models for teaching control system engineering. The system is widely used because it is very simple to understand and yet the control techniques cover many important classical and modern design methods. In this paper, the mathematical modelling for linear and nonlinear dynamic model of the cruise control system is obtained. PID, state space and artificial intelligence controller (fuzzy logic) are designed for linear model. Meanwhile, PID with feedforward controller is proposed for nonlinear model with disturbance effect. Feedforward-type PD controller is proposed in this study in order to eliminate the gravitational and wind disturbance effect. Simulation will be carried out using. Finally, a comparative assessment of the impact of each controller on the basis of results acquired.

Mohd. Fua'ad Rahmat

Papers

A review on hybrid electric vehicles architecture and energy management strategies

Application of self-tuning fuzzy pid controller on industrial hydraulic actuator using system identification approach

Performance comparison between lqr and pid controllers for an inverted pendulum system

Concentration profiles of dry powders in a gravity conveyor using an electrodynamic tomography system

Modelling and controller design for a cruise control system