다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

In this paper, an adaptive fuzzy optimal control design is addressed for a class of unknown nonlinear discrete-time systems. The controlled systems are in a strict-feedback frame and contain unknown functions and nonsymmetric dead-zone. For this class of systems, the control objective is to design a controller, which not only guarantees the stability of the systems, but achieves the optimal control performance as well. This immediately brings about the difficulties in the controller design. To this end, the fuzzy logic systems are employed to approximate the unknown functions in the systems. Based on the utility functions and the critic designs, and by applying the backsteppping design technique, a reinforcement learning algorithm is used to develop an optimal control signal. The adaptation auxiliary signal for unknown dead-zone parameters is established to compensate for the effect of nonsymmetric dead-zone on the control performance, and the updating laws are obtained based on the gradient descent rule. The stability of the control systems can be proved based on the difference Lyapunov function method. The feasibility of the proposed control approach is further demonstrated via two simulation examples.

Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone

Reactive matching is extended to wide bandwidths using the impedance property of LC-ladder filters. In this paper, we present a systematic method to design wideband low-noise amplifiers. An SiGe amplifier with on-chip matching network spanning 3-10 GHz delivers 21-dB peak gain, 2.5-dB noise figure, and -1-dBm input IP3 at 5 GHz, with a 10-mA bias current.

A 3-10-Ghz low-noise amplifier with wideband LC-ladder matching network

In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n -step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.

Adaptive NN Tracking Control of Uncertain Nonlinear Discrete-Time Systems With Nonaffine Dead-Zone Input

In the framework of the networked control systems (NCSs), the components are connected with each other over a shared band-limited network. The merits of NCSs include easy extensibility, resource sh...

A survey on sliding mode control for networked control systems

Renewable energy sources and technologies are increasingly gaining popularity in developing countries as their increasing energy demand can be met by the unexplored potential of renewable energy With help of decentralized system the power can be directly used at local load centers which will ease centralized grid The Impedance Source Inverter (ZSI) has many unique advantages as compared to normal Voltage Source Inverter (VSI) and is suitable for both centralized and decentralized applications This paper elaborates the distinguishing feature of ZSI which makes it suitable for isolated and grid integrated applications for a source whose nature is highly intermittent Operating principle, steady state analysis, different carrier modulation techniques to control shoot-through (ST) states are described ZSI is able to maintain the constant load bus voltage when connected to a highly intermittent PV panel with help of suitable control technique Its superiority in decentralized photovoltaic (PV) application is verified with help of MATLAB/Simulink environment An insight of inter-dependency of semiconductor device voltage stress, boosting factor (B) and modulation index (M) for sinusoidal pulsewidh modulation (SVPWM) control techniques is also presented

Z source inverter application and control for decentralized photovoltaic system

This paper discusses about the stabilization of unknown nonlinear discrete-time fixed state delay systems. The unknown system nonlinearity is approximated by Chebyshev neural network (CNN), and weight update law is presented for approximating the system nonlinearity. Using appropriate Lyapunov-Krasovskii functional the stability of the nonlinear system is ensured by the solution of linear matrix inequalities. Finally, a relevant example is given to illustrate the effectiveness of the proposed control scheme.

/pdf/stabilization-of-unknown-nonlinear-discrete-time-delay-4y8h4fbqkc.pdf

Stabilization of Unknown Nonlinear Discrete-Time Delay Systems Based on Neural Network

Abstract Now-a-days Massive MIMO (mMIMO) become an attractive technology due to its spectral and energy efficiency by the means of simple signal processing. However, in overloaded scenario, wherein the number of users equipments (UEs) are larger than number of antennas, the spectral effciency (SE) suffers and hence error rate performance, it has been shown recently that use of code domain NOMA in mMIMO can improve the SE performance. Further, interleave division multiple access (IDMA) has been drawn much attention as a suitable code domain non-orthogonal multiple access (NOMA) for future communication standards. This paper proposes the work in two folds, first a massive multiple input and multiple output (MIMO) and IDMA communication system is jointly proposed in which antennas on the base station serves users simultaneously in the same frequency band. Both and are large in numbers. Secondly, the minimum mean square error (MMSE) based beamformer is suggested to combat the propagation loss and effect of multiple access interference (MAI), for massive MIMO-IDMA system under downlink communication constraints. With the help of simulation results, the performance of the proposed system with MMSE beamforming have been investigated in terms of BER vs SNR curve plot.

/pdf/mmse-based-beamformer-in-massive-mimo-idma-downlink-systems-2ipsxarj7f.pdf

MMSE based beamformer in massive MIMO-IDMA downlink systems

This paper investigates a Chebyshev Neural Network (CNN) sliding mode controller for stabilization of time-delayed version of system with uncertainty and nonlinearity The nonlinearity in the system is unknown but bounded and has been approximated with the help of CNN The input delay has been balanced and further converted into regular form and the original system is converted into a delayed free version with the help of Smith Predictor Now, the predicted states of the system and “Gao’s reaching law” are used to derive the robust control law Further, to prove the stability analysis Lyapunov–Krasovskii candidates has been chosen according to the proposed system A numerical example is provided to illustrate the stability of the system in the presence of uncertainty, time delay and nonlinearity

Sliding Mode Control of Uncertain Nonlinear Discrete Delayed Time System Using Chebyshev Neural Network

Impedance Source Inverter (ZSI) offers a solution to low output renewable energy sources, provides unconventional high boost. Interaction of Quasi-Z-Source Inverter (qZSI) and third order filter ra...

Vinay Kumar Deolia

Papers

Z source inverter application and control for decentralized photovoltaic system

Stabilization of Unknown Nonlinear Discrete-Time Delay Systems Based on Neural Network

MMSE based beamformer in massive MIMO-IDMA downlink systems

Sliding Mode Control of Uncertain Nonlinear Discrete Delayed Time System Using Chebyshev Neural Network

Exploring the resonant characteristic of third order passive filter based Quasi-Z-source inverter