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 adaptive steering control of an electric unicycle with a steering turning mechanism, in order to achieve self-balancing and speed tracking simultaneously. A state feedback control method using the linear quadratic regulator approach is first presented to simultaneously achieve self-balancing and speed tracking, and then an adaptive friction compensating term is proposed to overcome frictions caused by different terrain surfaces. The performance and merit of the proposed control method are well exemplified by conducting two simulations and five experiments on a laboratory-built electric unicycle.

Adaptive steering control of an electric unicycle

The paper presents a novel sliding-mode control method augmented with broad learning system (BLS), or abbreviated as BLS-SMC, for trajectory tracking and station keeping of an uncertain Inverse-Atlas ball-riding robot (IASBRR) driven by three omnidirectional wheels. After brief description of the dynamic model of the robot with frictions and gravity, a BLS-SMC controller is proposed to accomplish robust self-balancing and trajectory tracking of the IASBRR in the presence of unknown frictions, mass variations and model uncertainties. The proposed BLS-SMC controller is proven asymptotically stable using Lyapunov stability theory and Barbalta’s lemma. Three comparative simulations and two experiments are conducted to show the effectiveness and merits of the proposed control method. The comparative results also indicate that the proposed controller is superior more efficient by comparing to an existing method.

Sliding-Mode Control Augmented with Broad Learning System for Self-Balancing Inverse-Atlas Ball-Riding Robots with Uncertainties

This paper presents a more efficient control algorithm for selecting suitable firing nodes and removing unimportant input variables automatically to improve the computational efficiency, reduce the number of firing rules and achieve good performance for the nonlinear control systems. A novel function-link fuzzy cerebellar model articulation controller (FLFC) is designed for uncertain nonlinear systems based on a multiple attribute decision-marking method known as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The proposed control system is comprised a TOPSIS FLFC (TFLFC) and a robust compensator. The parameters of the proposed TFLFC are tuned online using the adaptation laws that are derived from a Lyapunov stability theorem, so the system's stability is guaranteed. Finally, the proposed control system is used to control an inverted pendulum system and a master-slave Duffing-Holmes chaotic system to illustrate its favorable control performance.

A TOPSIS Multi-Criteria Decision Method-Based Function-Link Fuzzy CMAC Control System Design for Uncertain Nonlinear Systems

Analysis and measurement of lateral elliptic motion effect for an asymmetric disc-type ultrasonic motor

This paper presents methodologies and techniques for human face detection, identification and tracking used for a human-robot interactive system. A fuzzy skin color adjuster together with standard image processing algorithm is proposed to detect human faces, and then identify them using the nonlinear support vector machine (SVM) and the Euclidean distance measure. A fuzzy Kalman filtering scheme is presented to track the identified human faces. Experimental results are conducted to verify the effectiveness and merit of the three proposed methods.

Ching-Chih Tsai

Papers

Adaptive steering control of an electric unicycle

Sliding-Mode Control Augmented with Broad Learning System for Self-Balancing Inverse-Atlas Ball-Riding Robots with Uncertainties

A TOPSIS Multi-Criteria Decision Method-Based Function-Link Fuzzy CMAC Control System Design for Uncertain Nonlinear Systems

Analysis and measurement of lateral elliptic motion effect for an asymmetric disc-type ultrasonic motor

Face detection, identification and tracking using support vector machine and fuzzy Kalman filter