Adaptive Output Feedback Control of Nonlinear Systems

Adaptive output feedback control of classes of nonlinear systems and related problems are investigated. The classes of systems that are studied include Lipschitz nonlinear systems, large-scale interconnected nonlinear systems with quadratically bounded interconnections, nonlinear systems containing product terms of unmeasured states and unknown parameters, and mechanical systems with unknown time-varying parameters and disturbances. Solutions and their bounds of relevant algebraic and differential matrix equations in systems and control theory are also studied. For analysis and synthesis of controllers, methods from Lyapunov theory, Algebraic Riccati Equations (AREs), Linear Matrix Inequalities (LMIs), and local polynomial approximations are extensively used. Findings and Conclusions: A stable output feedback controller can be designed for Lipschitz nonlinear systems if sufficient conditions related to distances to uncontrollability and unobservability of pairs of system matrices are satisfied. Stable linear decentralized output feedback controllers can be designed for large-scale systems if certain sufficient conditions are satisfied; these conditions can be formulated either as existence of positive definite solutions to AREs or as a feasibility problem of an LMI. By casting the dynamics of a nonlinear system, which contains products of unmeasurable states and unknown parameters, into a modified form, a stable adaptive output feedback controller can be constructed using a parameter dependent Lyapunov function; the procedure for casting the system dynamics into a modified form is constructive and is always possible. A stable adaptive controller for mechanical systems with unknown time-varying parameters and disturbances can be designed using local polynomial approximation; the time-varying parameters and disturbances are estimated by a modified least-squares algorithm using a new resetting strategy, which is a consequence of keeping the estimates continuous at the beginning of each time interval of local polynomial approximation. For all the problems that are investigated, simulation and experimental results are given to verify and validate the proposed methods.Department of Biochemistry and Molecular Biolog

Adaptive Control of Mechanical Systems with Static and Dynamic Friction Compensation

Mechanical and Aerospace Engineerin

Semi-supervised MIMO Detection Using Cycle-consistent Generative Adversarial Network

In this paper, a new semi-supervised deep multiple-input multiple-output (MIMO) detection approach using a cycle-consistent generative adversarial network (CycleGAN) is proposed for communication systems without any prior knowledge of underlying channel distributions. Specifically, we propose the CycleGAN detector by constructing a bidirectional loop of two modified least squares generative adversarial networks (LS-GAN). The forward LS-GAN learns to model the transmission process, while the backward LS-GAN learns to detect the received signals. By optimizing the cycle-consistency of the transmitted and received signals through this loop, the proposed method is trained online and semi-supervisedly using both the pilots and the received payload data. As such, the demand on labelled training dataset is considerably controlled, and thus the overhead is effectively reduced. Numerical results show that the proposed CycleGAN detector achieves better performance in terms of both bit error-rate (BER) and achievable rate than existing semi-blind deep learning (DL) detection methods as well as conventional linear detectors, especially when considering signal distortion due to the nonlinearity of power amplifiers (PA) at the transmitter

IMECE2002-DSC-33421 ON THE ADAPTIVE CONTROL OF MECHANICAL SYSTEMS WITH TIME-VARYING PARAMETERS AND DISTURBANCES

ABSTRACT In this paper, we propose and investigate a new adaptive control algorithm for mechanical systems with time-varying parameters and/or time-varying disturbances. The proposed method does not assume any structure to the time-varying parameter or disturbance. The idea is based on the expansion of the timevarying parameter/disturbance using the Taylor series expansion; this facilitates expanding a time-varying function as a finite length polynomial and a bounded residue; the coefficients of the finite length polynomial are estimated in a time interval small enough so that they can be assumed to be constant within that interval. A novel experiment is designed using a two-link mechanical manipulator to investigate the proposed algorithm experimentally. Simulation and experimental results validate the proposed new adaptive control algorithm; we discuss these results and also give some future research directions

A novel low-temperature fabrication approach of composite phase change materials for high temperature thermal energy storage

Phase change materials (PCMs) are generally integrated into matrix materials to form shape-stabilized composite heat storage materials (HSMs) used for high temperature thermal energy storage applications. The conventional fabrication of composite HSMs is prevalently implemented at quite high temperatures, which is energy-intensive and narrows down the range of applicable PCMs because of thermal decomposition. Therefore, this paper establishes a novel fabrication approach to accomplish highly dense matrix to encapsulate PCMs at extremely low temperatures, based on the recently developed cold sintering process. The feasibility of the proposed approach was demonstrated by a case study of NaNO3/Ca(OH)2 composite HSMs. It was observed that the Ca(OH)2 matrix formed dense microstructure with obvious sintered boundaries and successfully encapsulated NaNO3 as PCM. The HSMs maintained stable macroscopic shape after hundreds of thermal cycles, and exhibited an energy storage efficiency of 59.48%, little leakage of PCM, and good thermal stability. Mechanical tests indicated that the HSMs possessed excellent mechanical properties when the sintering pressure is over 220 MPa. The discharging time of stored heat was presented through infrared thermography, and the heat storage capacity measured for the composite HSMs was over four times as high as those of typical solid storage materials of sensible heat, which demonstrated their excellent heat storage performances. The HSMs can be used in the form of packed bed or parallel channel with multi-layered heat storage, which is beneficial for efficiently utilizing solar heat and improving the performance of current energy storage system. This study therefore provides a novel route for energy-saving and low-carbon fabrication of shape-stabilized composite HSMs