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 an improved global localization method and an improved pose tracking approach for an indoor autonomous mobile robot (AMR) with ultrasonic and laser scanning measurements using a fuzzy extended information filtering scheme An ultrasonic self-localization system, consisting of two ultrasonic transmitters and three receivers, is presented to estimate both the unknown global position and orientation of the AMR in a world frame, and a fuzzy adaptive extended information filter (FAEIF) is proposed to improve estimation accuracy for the ultrasonic localization system With the odometric data from the driving wheels and the laser scanning measurements from the robot's surrounding, a FAEIF-based pose tracking algorithm is proposed to continuously keep track of the robot's poses at slow speeds less than 100 cm/sec The proposed algorithms were implemented using an industrial personal computer with a computation speed of 800MHz, and standard C++ programming techniques The system prototype together with experimental results has been used to confirm the merit of the proposed methods in comparison with the well-known EIF

Improved global localization and pose tracking of an autonomous mobile robot via fuzzy adaptive extended information filtering

This paper develops techniques for position recovery of a free-ranging automatic guided vehicle using a dead-reckoning device and a laser scanner. Extended information filtering (ElF) scheme is presented using a simple rectangular model and a 2-D laser scanner. By continuously updating the robot's pose and matching the laser data with the environmental model, we find that the outliers can be filtered out effectively by validation gate. Moreover, a range-weighted Hough transform (RWHT) is used to extract the modeled lines from the clutter data. Computer simulations and experimental results are performed to illustrate the feasibility and efficacy of the proposed position recovery methods.

Laser-based position recovery of a free-ranging automatic guided vehicle

This paper presents a direct adaptive motion controller using fuzzy wavelet neural networks (FWNN) for speed control of an electric two-wheeled robotic vehicle (ETWRV) with unknown parameters and uncertainties. With the decomposition of the overall system into two subsystems: yaw motion control and mobile inverted pendulum, two direct adaptive FWNN motion controllers are respectively proposed to achieve station keeping, speed following and yaw motion control. Asymptotic stabilities of the two controllers with their FWNN weighting updating rules are derived via the Lyapunov stability theory. Simulation results indicate that the proposed controllers are capable of providing satisfactory control actions to steer the vehicle.

Direct Adaptive Fuzzy-Wavelet-Neural-Network Control for Electric Two-Wheeled Robotic Vehicles

This paper presents a two degree-of-freedom control method for achieving bi-level positive airway pressure (Bi-PAP) of an obstructive sleep apnea (OSA) treatment system. After constructing a closed-loop DC brushless motor which is based on a microchip (dsPIC30F3010) drive together with a blower and an airway module, we develop a pressure control system for achieving Bi-PAP control. A mathematical model of the overall open-loop system is established based on the input-output data and its system parameters are sequentially determined using the recursive least-squares (RLS) approach. A two degree-of-freedom (DOF) controller, including a nonlinear feedforward controller and a feedback proportional-integral-derivative controller (PID controller) with gain scheduling, is proposed to maintain and follow the desired bi-level pressure setpoints. Through experimental results, the proposed control method is shown useful and effective in achieving bi-level airway pressure tracking.

Two Degree-of-freedom Control for Bi-level Positive Airway Pressure of an Obstructive Sleep Apnea Treatment System

This paper develops methodologies and techniques for design, analysis and implementation of a direct self-tuning model following predictive temperature controller for a variable-frequency oil-cooling machine, used for cooling high-speed machine tools. The oil- cooling process is modeled experimentally as a first-order system model with a time-delay and its system parameters are identified using the recursive least-squares method. Based on this model, a novel adaptive predictive controller is proposed for achieving set-point tracking and disturbance rejection. A real-time direct self-tuning model following predictive control algorithm is then presented and implemented utilizing a standalone digital signal processor (DSP) TMS320F243 from Texas Instruments. The experimental results show that the proposed control method is proven capable of giving satisfactory performance under set-point changes, fixed loads and load changes.

http://ieeexplore.ieee.org/iel5/8775/27789/01239085.pdf

Ching-Chih Tsai

Papers

Improved global localization and pose tracking of an autonomous mobile robot via fuzzy adaptive extended information filtering

Laser-based position recovery of a free-ranging automatic guided vehicle

Direct Adaptive Fuzzy-Wavelet-Neural-Network Control for Electric Two-Wheeled Robotic Vehicles

Two Degree-of-freedom Control for Bi-level Positive Airway Pressure of an Obstructive Sleep Apnea Treatment System

Direct self-tuning model following predictive control of a variable-frequency oil-cooling machine