By a switched system, we mean a hybrid dynamical system consisting of a family of continuous-time subsystems and a rule that orchestrates the switching between them. The article surveys developments in three basic problems regarding stability and design of switched systems. These problems are: stability for arbitrary switching sequences, stability for certain useful classes of switching sequences, and construction of stabilizing switching sequences. We also provide motivation for studying these problems by discussing how they arise in connection with various questions of interest in control theory and applications.

Basic problems in stability and design of switched systems

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

Formation and control of optimal trajectory in human multijoint arm movement : minimum torque-change model

The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs.

https://hal-centralesupelec.archives-ouvertes.fr/hal-01337007/document

FPGAs in Industrial Control Applications

This paper presents techniques for system design and interval type-2 (IT2) fuzzy gear-changing control of an electronic gear-changing control system in an intelligent bike. After detailed description of the system structure and key components of the electronic gear-changing control system, the dynamic relationship between the pedaling power and the motion of the bike is mentioned for simulation studies. An IT2 fuzzy logic controller (FLC) is proposed by using two sensors of bike speed and pedaling rate, in order to accomplish smooth gear-changing strategy. The effectiveness and merit of the proposed IT2 fuzzy gear-changing method are well exemplified by comparing with an existing conventional fuzzy gear-changing strategy.

Interval type-2 fuzzy gear-changing control for intelligent bikes

This paper presents a decentralized cooperative transportation control method with obstacle avoidance using fuzzy wavelet neural networks (FWNN) and consensus algorithm for a group of mobile Mecanum-wheeled omnidirectional robots (MWORs) with uncertainties, in order to get together to move a large payload. The dynamic behavior of each uncertain MWOR is modelled by a reduced three-input-three-output second-order system model and the uncertain multi-MWOR system is modeled by graph theory. By online learning the system uncertainties using FWNN and using the Lyapunov stability theory, an intelligent adaptive, cooperative consensus-based control approach is presented to carry out transportation control with uncertainties. An obstacle avoidance method is proposed to modify the generating trajectory of the virtual leader, in order to avoid any collisions between the robots and the environment. Two simulations are conducted to show the effectiveness of the proposed method.

Decentralized cooperative transportation with obstacle avoidance using fuzzy wavelet neural networks for uncertain networked omnidirectional multi-robots

For modern mobile phone displays, their driving integrated circuit (IC) solutions, often called total solutions, have included various functions, such as scanning, driving, power-level conversion, image storage memory, timing control, and standard interfacing; however, most of them lack of realtime image processing engine. In this paper, a novel real-time pixel-level image processing algorithm is presented to enlarge image color gamut and enhance image contrast without frame memory for mobile phone displays. This image processing algorithm simultaneously executes two parallel algorithms: rich color and contrast enhancement. The rich color algorithm obtains a wide color gamut image data showing more than 30% area enhancement in the CIE1931 color space without hue distortion. The contrast enhancement algorithm improves 20% contrast ratio improvement. Numerous simulation results are provided to illustrate the feasibility and efficacy of the proposed algorithms and image processing engine. Experimental results are conducted to show the performance and usefulness of the proposed composite algorithm for 2.2- inch mobile phone TFT LCDs.

Color Gamut and Contrast Enhancement for Mobile Phone Displays

The plastic extrusion process with water cooling is a variable structure system in nature. To implement discrete-time variable structure control, three important problems are considered: 1) choice of dynamic sliding surface for a system with relative degree greater than one; 2) computation of the discrete-time dynamic sliding surface variable (s/sub k/); 3) and self-tuning of the switching control magnitude to reduce chatterings. A simplified lumped parameter model is constructed to decouple the original multi-channel system into multiple single-channel subsystems. Experimental results show effectiveness of the proposed method.

Discrete-time VSS temperature control for a plastic extrusion process with water cooling systems

This article presents an adaptive H ∞ nonlinear velocity control for a linear DC brushless motor. A simplified model of this motor with friction is briefly recalled. The friction dynamics is described by the Lu Gre model and the online tuning radial basis function neural network (RBFNN) is used to parameterise the nonlinear friction function and un-modelled errors. An adaptive nonlinear H ∞ control method is then proposed to achieve velocity tracking, by assuming that the upper bounds of the ripple force, the changeable load and the nonlinear friction can be learned by the RBFNN. The closed-loop system is proven to be uniformly bounded using the Lyapunov stability theory. The feasibility and the efficacy of the proposed control are exemplified by conducting two velocity tracking experiments.

Ching-Chih Tsai

Papers

Interval type-2 fuzzy gear-changing control for intelligent bikes

Decentralized cooperative transportation with obstacle avoidance using fuzzy wavelet neural networks for uncertain networked omnidirectional multi-robots

Color Gamut and Contrast Enhancement for Mobile Phone Displays

Discrete-time VSS temperature control for a plastic extrusion process with water cooling systems

Adaptive H∞ nonlinear velocity tracking using RBFNN for linear DC brushless motor