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 MIMO predictive control using recurrent neural networks for a class of nonlinear discrete-time systems. The recurrent-neural-network-based predictive control law is developed from the optimization of a generalized predictive performance criterion. A real-time adaptive control algorithm, including a neural predictor and a neural predictive controller, is proposed; the learning rates for both the neural predictor and controller are determined based on Lyapunov stability theory. Simulation results reveals that the proposed control strategy gives satisfactory tracking and disturbance rejection performance for two illustrative nonlinear multivariable systems.

MIMO Predictive Controller Using Recurrent Neural Networks

This paper develops methodologies for suboptimal nonlinear filtering of a stochastic hybrid system whose switching behavior is governed by a continuous-time finite state Markov chain (FSMC) with known transition probabilities. A novel suboptimal filter approximation is presented for the system whose transition rates are very slow. An approximate filter for the system structure detection problem is then studied. Finally, numerical simulations are performed to investigate the behavior of the suboptimal filters.

A novel suboptimal nonlinear filtering scheme for stochastic hybrid systems

This paper presents an direct adaptive control for an uncertain electric seatless unicycle using wavelet fuzzy cerebella model articulation controller (WFCMAC). The WFCMAC is proposed to approximate the equivalent control part and uncertainties. A nonlinear backstepping sliding-mode controller with on-line adaptive laws is presented to accomplish adaptive robust self-balancing and speed control of the seatless electric unicycle based on the rider's body inclination and the speed of the unicycle. Simulations results indicate that the performance and merit of the proposed method are well illustrated by comparing to two existing controllers.

Nonlinear self-balancing and speed control using WFCMAC for seatless electric unicycles

The paper presents a cooperative fuzzy sparse extended information filtering (FSEIF) method for simultaneous localization and mapping SLAM) of multiple three-wheeled omnidirectional mobile multirobots in a given indoor environment. After brief description of our previous fuzzy SEIF SLAM (FSEIF SLAM) algorithm for a single mobile robot, a cooperative Fuzzy SEIF SLAM approach is presented for a group of omnidirectional mobile multirobots, where the optimal path searching method is devised by incorporating with K-means and Dijkstra algorithm under the assumption of known map and correspondence conditions. The effectiveness and merits of the proposed cooperative FSEIF SLAM in a large-scale environment are well illustrated by carrying out comparative simulations for multiple mobile robots.

Cooperative FSEIF SLAM of Omnidirectional Mobile Multirobots

This paper presents techniques to design a dynamic motion controller using Ant Colony Optimization (ACO) for simultaneous stabilization and tracking of nonholonomic mobile robots. A unified dynamic motion controller is first designed based on the Lyapunov stability theory and adaptive backstepping technique, and ACO is then applied to search for the best control parameters of the proposed dynamic controller. Simulations are conducted to illustrate the performance of the proposed controller.

http://ieeexplore.ieee.org/iel5/5876182/5899042/05899193.pdf

Ching-Chih Tsai

Papers

MIMO Predictive Controller Using Recurrent Neural Networks

A novel suboptimal nonlinear filtering scheme for stochastic hybrid systems

Nonlinear self-balancing and speed control using WFCMAC for seatless electric unicycles

Cooperative FSEIF SLAM of Omnidirectional Mobile Multirobots

Adaptive dynamic motion control using ant colony optimization for nonholonomic mobile robots