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

This paper presents a robust sliding mode controller for a class of unknown nonlinear discrete-time systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional theory into the sliding-mode technique is used and a neural-network based sliding mode control scheme is proposed. Because of the novality of Chebyshev Neural Networks (CNNs), that it requires much less computation time as compare to multi layer neural network (MLNN), is preferred to approximate the unknown system functions. By means of linear matrix inequalities, a sufficient condition is derived to ensure the asymptotic stability such that the sliding mode dynamics is restricted to the defined sliding surface. The proposed sliding mode control technique guarantees the system state trajectory to the designed sliding surface. Finally, simulation results illustrate the main characteristics and performance of the proposed approach.

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Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Control of flow rate in industrial plants is an essential and crucial task, which is usually achieved by pneumatic control valves in industries. Use of these valves often incorporates nonlinear and uncertain dynamics in the control loop on account of its input-output characteristics, which may result in degradation of control loop performance. To address this concern, a robust and improved fractional order parallel control structure (FOPCS) for flow control is proposed in this paper. The proposed FOPCS is an extension of parallel control structure (PCS) with the help of fractional order calculus, to enhance the robustness in the control loop without compromising with control performance. Also, a global optimization technique, backtracking search algorithm was further employed to critically tune the parameters of control structures. This was done in order to obtain an optimized and enhanced performance from the control loop. Extensive runtime studies on a laboratory scale plant, using advanced data acquisition facilities, were carried out to showcase the effectiveness of developed FOPCS. Proposed FOPCS is thoroughly assessed in terms of servo, regulatory and robustness performance. A quantitative comparison of FOPCS with PCS is also made on the basis of integral of absolute error, integral of absolute rate of controller output and their algebraic summation. All the conducted experimental studies suggested that proposed FOPCS was able to address the issues pertaining to uncertain and nonlinear behaviour of pneumatic control valve in the flow control loop.

A Robust Fractional Order Parallel Control Structure for Flow Control using a Pneumatic Control Valve with Nonlinear and Uncertain Dynamics

In one's day to day life; internet is growing and became an important part. Digital content can easily be downloaded, copied or edited. Digital content can be secured by various ways. Digital Watermarking is one of the methods for the protection of Digital Content. Digital Watermarking is a method by which data can be secured by hiding data in any image which can work as a carrier image. The carrier image is also known as cover image. Watermarking is an interactive method to protect and identify the digital data. It permits various types of watermarks to be hidden in digital data e.g. image, audio and video. In this work, watermarking has been done using LSB technique, DCT transform and DWT transform. These techniques are compared on the basis of peak signal to noise ratio (PSNR) and normalized correlation (NC). Parameters are compared for various noises like Gaussian noise, Poisson noise, Salt and Pepper noise and Speckle noise.

Comparative analysis of LSB, DCT and DWT for Digital Watermarking

Abstract This paper studies an improved fractional order parallel control structure (FOPCS) for enhancing the robustness in an industrial control loop having a first order process with dead time along with its tuning aspects. Since inclusion of fractional order calculus also increase the number of parameters to be determined for a particular control loops, tuning becomes an essential task. Four different tuning methods are considered to optimize the gains of parallel control structure (PCS) and FOPCS. Integral of time weighted absolute error for servo and regulatory problems along with overshoot value have been considered for performance evaluation. Extensive simulation studies including change in setpoint and mismatch in processmodel parameters have been carried out. On the basis of these studies, it was observed that FOPCS tuned by backtracking search algorithm, outperformed all other controllers in terms of considered performance measures.

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A fractional order parallel control structure tuned with meta-heuristic optimization algorithms for enhanced robustness

This paper presents a wideband low noise amplifier (LNA) which consist cascade of two stages. First stage, a complimentary common gate (CCG) stage is utilized to consume low power and low chip area while second stage is the mutually coupled common source (CS) stage used to generate high gain at high frequency. The concept of current reuse technique is used in CCG stage to save the dc power. While for the objective of low chip area, mutually coupled inductors are used, mathematically equivalent to a transformer. CCG stage provides high gain at low frequency. A frequency dependent load is generated by mutually coupled CS stage to transfer this gain at high frequency and then this load is transferred to the CCG stage using load transformation technique. This help a lot in achieving wide band input matching hence low noise figure (NF). Proposed LNA is verified mathematically and simulated in 90-nm CMOS process. The measured 3-dB bandwidth is 4.7–14.7 GHz with maximum voltage gain of 17.2 dB, minimum NF of 1.8 dB and S11 < − 10.3 dB. Maximum available power gain (GA) is 11.9 dB and maximum operating power gain is 11.4 dB at frequency of 13.2 GHz.

Vinay Kumar Deolia

Papers

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

A Robust Fractional Order Parallel Control Structure for Flow Control using a Pneumatic Control Valve with Nonlinear and Uncertain Dynamics

Comparative analysis of LSB, DCT and DWT for Digital Watermarking

A fractional order parallel control structure tuned with meta-heuristic optimization algorithms for enhanced robustness

A wideband design analysis of LNA utilizing complimentary common gate stage with mutually coupled common source stage