Position Control of a Flexible Manipulator Using a New Nonlinear Self-Tuning PID Controller

In this paper, a new nonlinear self-tuning PID controller(NSPIDC) is proposed to control the joint position and link deflection of a flexible-link manipulator(FLM) while it is subjected to carry different payloads. Since, payload is a critical parameter of the FLM whose variation greatly influences the controller performance. The proposed controller guarantees stability under change in payload by attenuating the non-modeled higher order dynamics using a new nonlinear autoregressive moving average with exogenous-input(NARMAX) model of the FLM. The parameters of the FLM are identified on-line using recursive least square(RLS) algorithm and using minimum variance control(MVC) laws the control parameters are updated in real-time. This proposed NSPID controller has been implemented in real-time on an experimental set-up. The joint tracking and link deflection performances of the proposed adaptive controller are compared with that of a popular direct adaptive controller(DAC). From the obtained results, it is confirmed that the proposed controller exhibits improved performance over the DAC both in terms of accurate position tracking and quick damping of link deflections when subjected to variable payloads.

Investigation of artifacts by mapping SAR in thermoacoustic imaging

Microwave-induced thermoacoustic imaging(MI-TAI)remains one of the focus of attention among biomedical imaging modalities over the last decade.However,the transmission and dis-tribution of microwave inside bio-tissues are complicated,thus result in severe artifacts.In this study,to reveal the underlying mechanisms of artifacts,we deeply investigate the distribution of specific absorption rate(SAR)inside tissue-mimicking phantoms with varied morphological features using both mathematical simulations and corresponding experiments.Our simulated results,which are confirmed by the associated experimental results,show that the SAR distri-bution highly depends on the geometries of the imaging targets and the polarizing features of the microwave.In addition,we propose the potential mechanisms including Mie-scattering,Fabry-Perot-feature,small curvature effect to interpret the diffraction effect in different scenarios,which may provide basic guidance to predict and distinguish the artifacts for TAI in both fundamental and clinical studies.

A NEW METHOD OF BAD POINTS ELIMINATION BASED ON HOUGH TRANSFORM

In experimental tests, besides data in range of allowable error, the experimenters usually get some unexpected wrong data called bad points. In usual experimental data processing, the method of bad points exclusion based on automatic programming is seldom taken into consideration by researchers. This paper presents a new method to reject bad points based on Hough transform, which is modified to save computational and memory consumptions. It is fit for linear data processing and can be extended to process data that is possible to be transformed into and from linear form; curved lines, which can be effectively detected by Hough transform. In this paper, the premise is the distribution of data, such as linear distribution and exponential distribution, is predetermined. Steps of the algorithm start from searching for an approximate curve line that minimizes the sum of parameters of data points. The data points, whose parameters are above a self-adapting threshold, will be deleted. Simulation experiments have manifested that the method proposed in this paper performs efficiently and robustly.

Impact of Reactive Power in Power Evacuation from Wind Turbines

Application of Distributed Generation (DG) to supply the demands of a diverse customer base plays a vital role in the renewable energy environment. Various DG technologies are being integrated into power systems to provide alterna-tives to energy sources and to improve reliability of the system. Power Evacuation from these remotely located DG’s remains a major concern for the power utilities these days. The main cause of concern regarding evacuation is con-sumption of reactive power for excitation by Induction Generators (IG) used in wind power production which affects the power system in variety of ways. This paper deals with the issues related to reactive power consumption by Induc-tion generators during power evacuation. Induction generator based wind turbine model using MATLAB/SIMULINK is simulated and its impact on the grid is observed. The simulated results are analyzed and validated with the real time results for the system considered. A wind farm is also modeled and simulations are carried out to study the various im-pacts it has on the grid &nearby wind turbines during Islanding and system event especially on 3-Phase to ground fault.

Design of a Robust Optimal Decentralized PI Controller Based on Nonlinear Constraint Optimization For Level Regulation: An Experimental Study

This paper presents the development of a new robust optimal decentralized PI controller based on nonlinear optimization for liquid level control in a coupled tank system. The proposed controller maximizes the closed-loop bandwidth for specified gain and phase margins, with constraints on the overshoot ratio to achieve both closed-loop performance and robustness. In the proposed work, a frequency response fitting model reduction technique is initially employed to obtain a first order plus dead time(FOPDT) model of each higher order subsystem. Furthermore, based on the reduced order model, a proposed controller is designed. The stability and performance of the proposed controller are verified by considering multiplicative input and output uncertainties. The performance of the proposed optimal robust decentralized control scheme has been compared with that of a decentralized PI controller. The proposed controller is implemented in real-time on a coupled tank system. From the obtained results,it is shown that the proposed optimal decentralized PI controller exhibits superior control performance to maintain the desired level, for both the nominal as well as the perturbed case as compared to a decentralized PI controller.

Realizations of Voltage Transfer Functions Using DVCCs

Maheshwari has proposed three differential-voltage current-conveyor configurations for realizing first order all-pass filters only. This paper has exploited these configurations for realizing more complex transfer function T(s)?which yield poles and zeros of 1 -?T(s) in one of the four admissible patterns. Bilinear and biquadratic functions are dealt in detail. It is shown that only bilinear functions can be realized with all the four passive elements grounded. First order all-pass function is a special case which needs only three elements (2R, 1C) or (1R, 2C). A biquadratic function requires (2R, 2C) elements and has all the capacitor grounded. Design of second order all-pass function is given.

Coherence Based Sufficient Condition for Support Recovery Using Generalized Orthogonal Matching Pursuit

In an underdetermined system,compressive sensing can be used to recover the support vector.Greedy algorithms will recover the support vector indices in an iterative manner.Generalized Orthogonal Matching Pursuit(GOMP)is the generalized form of the Orthogonal Matching Pursuit(OMP)algorithm where a number of indices selected per iteration will be greater than or equal to 1.To recover the support vector of unknown signal‘x’from the compressed measurements,the restricted isometric property should be satisfied as a sufficient condition.Finding the restricted isometric constant is a non-deterministic polynomial-time hardness problem due to that the coherence of the sensing matrix can be used to derive the sufficient condition for support recovery.In this paper a sufficient condition based on the coherence parameter to recover the support vector indices of an unknown sparse signal‘x’using GOMP has been derived.The derived sufficient condition will recover support vectors of P-sparse signal within‘P’iterations.The recovery guarantee for GOMP is less restrictive,and applies to OMP when the number of selection elements equals one.Simulation shows the superior performance of the GOMP algorithm compared with other greedy algorithms.

MIMO-DCSK communication scheme and its performance analysis over multipath fading channels

The differential chaotic shift keying （DCSK） communication in multiple input multiple output （MIMO） multipath fading chan- nels is considered. A simple MIMO-DCSK communication scheme based on orthogonal multi-codes （OMCs） and equal gain combination （EGC） is proposed, in which OMCs are used to spread the same information bit at each transmitting antenna and the infor- mation bit is detected by EGC at receiving antenna. The OMCs are constructed from one chaotic sequence by means of othogo- nal space-time block coding （OSTBC）. The output signal-to-noise ratio （SNR） after EGC is given based on central limit theory （CLT）, and it can effectively exploit the spatial diversity of the underlying MIMO system. Simulation results show that the full spatial diversity gain is achieved without channel estimation in the MIMO-DCSK communication scheme and it performs better than MC-EGC for a large number of transmitting antennas.

Thermally annealed gamma irradiated Ni/4H-SiC Schottky barrier diode characteristics

Thermal annealing effects on gamma irradiated Ni/4 H-SiC Schottky barrier diode(SBD) characteristics are analyzed over a wide range of temperatures(400–1100 °C). The annealing induced variations in the concentration of deep level traps in the SBDs are identified by thermally stimulated capacitance(TSCAP). A little decrease in the trap density at E_C – 0.63 eV and E_C –1.13 eV is observed up to the annealing temperature of 600 °C. Whereas, a gamma induced trap at E_C – 0.89 eV disappeared after annealing at 500 °C, revealing that its concentration(< 1013 cm-3) is reduced below the detection limit of the TSCAP technique.The electrical characteristics of irradiated SBDs are considerably changed at each annealing temperature. To understand the anomalous variations in the post-annealing characteristics, the interface state density distribution in the annealed SBDs is extracted.The electrical properties are improved at 400 °C due to the reduction in the interface trap density. However, from 500 °C, the electrical parameters are found to degrade with the annealing temperature because of the increase in the interface trap density.From the results, it is noted that the rectifying nature of the SBDs vanishes at or above 800 °C.

Biomedical microwave-induced thermoacoustic imaging

Microwave induced thermoacoustic imaging(MTAI)has emerged as a potential biomedical imaging modality with over 20-year growth.MTAI typically employs pulsed microwave as the pumping source,and detects the microwave-induced ultrasound wave via acoustic transducers.Therefore,it features high acoustic resolution,rich elect romagnetic contrast,and large imaging depth.Benefiting from these unique advantages,MTAI has been extensively applied to various fields including pathology,biology,material and medicine.Till now,MTAI has been deployed for a wide range of biomedical applications,including cancer diagnosis,joint evaluation,brain in-vestigation and endoscopy.This paper provides a comprehensive review on(1)essential physics(endogenous/exogenous contrast mechanisms,penetration depth and resolution),(2)hardware configurations and software implementations(excit ation source,antenna,ultrasound detector and image recovery algorithm),(3)animal studies and clinical applications,and(4)future directions.

A Delay-Dependent Anti-Windup Compensator for Wide-Area Power Systems With Time-Varying Delays and Actuator Saturation

In this paper, a delay-dependent anti-windup compensator is designed for wide-area power systems to enhance the damping of inter-area low-frequency oscillations in the presence of time-varying delays and actuator saturation using an indirect approach. In this approach, first, a conventional wide-area damping controller is designed by using output feedback with regional pole placement approach without considering time-varying delays and actuator saturation. Then to mitigate the effect of both time-varying delays and actuator saturation, an add-on delay-dependent anti-windup compensator is designed. Based on generalized sector conditions, less conservative delay-dependent sufficient conditions are derived in the form of a linear matrix inequality(LMI) to guarantee the asymptotic stability of the closedloop system in the presence of time-varying delays and actuator saturation by using Lyapunov-Krasovskii functional and Jensen integral inequality. Based on sufficient conditions, the LMI-based optimization problem is formulated and solved to obtain the compensator gain which maximizes the estimation of the region of attraction and minimizes the upper bound of-gain. Nonlinear simulations are performed first using MATLAB/Simulink on a two-area four-machine power system to evaluate the performance of the proposed controller for two operating conditions, e.g.,3-phase to ground fault and generator 1 terminal voltage variation. Then the proposed controller is implemented in real-time on an OPAL-RT digital simulator. From the results obtained it is verified that the proposed controller provides sufficient damping to the inter-area oscillations in the presence of time-varying delays and actuator saturation and maximizes the estimation of the region of attraction.

Nonparametric TOA estimators for low-resolution IR-UWB digital receiver

Nonparametric time-of-arrival（TOA） estimators for impulse radio ultra-wideband（IR-UWB） signals are proposed. Nonparametric detection is obviously useful in situations where detailed information about the statistics of the noise is unavailable or not accurate. Such TOA estimators are obtained based on conditional statistical tests with only a symmetry distribution assumption on the noise probability density function. The nonparametric estimators are attractive choices for low-resolution IR-UWB digital receivers which can be implemented by fast comparators or high sampling rate low resolution analog-to-digital converters（ADCs）,in place of high sampling rate high resolution ADCs which may not be available in practice. Simulation results demonstrate that nonparametric TOA estimators provide more effective and robust performance than typical energy detection（ED） based estimators.

Control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power systems.New analysis and control methods are needed for power systems to cope with the ongoing transformation.In the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power systems.Specifically,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

Substrate-induced stress in silicon nanocrystal/SiO_2 multilayer structures

A Raman frequency upshift in the nc-Si phonon mode is observed at room temperature, which is attributed to a strong compressive stress in the Si nanocrystals. The 10-period amorphous-Si（3 nm）/amorphous-SiO2 （3 nm） layers are deposited by high-vacuum radio-frequency magnetron sputtering on quartz and sapphire substrates at different temperatures. The samples are then annealed in N2 atmosphere at 1100 ℃ for 1 h for Si crystallization. It is demonstrated that the presence of a supporting substrate at the high growth temperature can induce different types of stresses in the Si nanocrystal layers. The strain is attributed to the difference in the thermal expansion coefficient between the substrate and the Si/SiO2 SL film. Such a substrate-indueed stress indicates a new method for tuning the optical and electronic properties of Si nanocrystals for strained engineering.

C-MEMS-derived glassy carbon electrochemical biosensors for rapid detection of SARS-CoV-2 spike protein

According to a World Health Organization(WHO)report,the world has experienced more than 766 million cases of positive SARS-CoV-2 infection and more than 6.9 million deaths due to COVID through May 2023.The WHO declared a pandemic due to the rapid spread of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)virus,and the fight against this pandemic is not over yet.Important reasons for virus spread include the lack of detection kits,appropriate detection techniques,delay in detection,asymptomatic cases and failure in mass screening.In the last 3 years,several researchers and medical companies have introduced successful test kits to detect the infection of symptomatic patients in real time,which was necessary to monitor the spread.However,it is also important to have information on asymptomatic cases,which can be obtained by antibody testing for the SARS-CoV-2 virus.In this work,we developed a simple,advantageous immobilization procedure for rapidly detecting the SARS-CoV-2 spike protein.Carbon-MEMS-derived glassy carbon(GC)is used as the sensor electrode,and the detection is based on covalently linking the SARS-CoV-2 antibody to the GC surface.Glutaraldehyde was used as a cross-linker between the antibody and glassy carbon electrode(GCE).The binding was investigated using Fourier transform infrared spectroscopy(FTIR)characterization and cyclic voltammetric(CV)analysis.Electrochemical impedance spectroscopy(EIS)was utilized to measure the change in total impedance before and after incubation of the SARS-CoV-2 antibody with various concentrations of SARS-CoV-2 spike protein.The developed sensor can sense 1 fg/ml to 1µg/ml SARS-CoV-2 spike protein.This detection is label-free,and the chances of false positives are minimal.The calculated LOD was~31 copies of viral RNA/mL.The coefficient of variation(CV)number is calculated from EIS data at 100 Hz,which is found to be 0.398%.The developed sensor may be used for mass screening because it is cost-effective.

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments.The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles(AUVs)because of its hostile and dynamic nature.The major constraints for path planning are limited data transmission capability,power and sensing technology available for underwater operations.The sea environment is subjected to a large set of challenging factors classified as atmospheric,coastal and gravitational.Based on whether the impact of these factors can be approximated or not,the underwater environment can be characterized as predictable and unpredictable respectively.The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner.But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted.Path planning is necessary for many applications involving AUVs.These are based upon planning safety routes with minimum energy cost and computation overheads.This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable.The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.

A Combined Reinforcement Learning and Sliding Mode Control Scheme for Grid Integration of a PV System

The paper presents development of a reinforcement learning(RL)and sliding mode control(SMC)algorithm for a 3-phase PV system integrated to a grid.The PV system is integrated to grid through a voltage source inverter(VSI),in which PVVSI combination supplies active power and compensates reactive power of the local non-linear load connected to the point of common coupling(PCC).For extraction of maximum power from the PV panel,we develop a RL based maximum power point tracking(MPPT)algorithm.The instantaneous power theory(IPT)is adopted for generation reference inverter current(RIC).An SMC algorithm has been developed for injecting current to the local non-linear load at a reference value.The RL-SMC scheme is implemented in both simulation using MATLAB/SIMULINK software and on a prototype PV experimental.The performance of the proposed RL-SMC scheme is compared with that of fuzzy logic-sliding mode control(FL-SMC)and incremental conductance-sliding mode control(IC-SMC)algorithms.From the obtained results,it is observed that the proposed RL-SMC scheme provides better maximum power extraction and active power control than the FL-SMC and IC-SMC schemes.

Identification of Protein-Coding Regions in DNA Sequences Using A Time-Frequency Filtering Approach

Accurate identification of protein-coding regions （exons） in DNA sequences has been a challenging task in bioinformatics. Particularly the coding regions have a 3-base periodicity, which forms the basis of all exon identifica- tion methods. Many signal processing tools and techniques have been applied successfully for the identification task but still improvement in this direction is needed. In this paper, we have introduced a new promising model-independent time-frequency filtering technique based on S-transform for accurate identification of the coding regions. The S-transform is a powerful linear time-frequency representation useful for filtering in time-frequency domain. The potential of the proposed technique has been assessed through simulation study and the results obtained have been compared with the existing methods using standard datasets. The comparative study demonstrates that the proposed method outperforms its counterparts in identifying the coding regions.

Impact of FACTS devices on exercising market power in deregulated electricity market

In power system studies, congestion in trans- mission lines and utilization of flexible alternating current transmission system （FACTS） devices are closely associated. These devices are very important due to their role in power delivery system enhancement. It is to be noted that the generation companies can exercise their market power which depends on the line flows, line constraints, generators＇ location and its share to the individual loads. This issue cannot be overlooked as it creates monopoliness which is against the deregulated market policy. The objective of this paper is to study the impact of market power when FACTS devices like thyristor controlled switching capacitor （TCSC） and thyristor controlled phase angle regulator （TCPAR） are used under steady state operation. The market power is determined using nodal must-run share （NMRS） index for the standard IEEE 14- bus system with and without the above FACTS devices and the results obtained are compared. All the above simula- tions are conducted in a MATLAB 7.9-R2009b environment.

An improved analytical model of 4H-SiC MESFET incorporating bulk and interface trapping effects

An improved analytical model for the current–voltage（I–V） characteristics of the 4H-SiC metal semiconductor field effect transistor（MESFET） on a high purity semi-insulating（HPSI） substrate with trapping and thermal effects is presented. The 4H-SiC MESFET structure includes a stack of HPSI substrates and a uniformly doped channel layer. The trapping effects include both the effect of multiple deep-level traps in the substrate and surface traps between the gate to source/drain. The self-heating effects are also incorporated to obtain the accurate and realistic nature of the analytical model. The importance of the proposed model is emphasised through the inclusion of the recent and exact nature of the traps in the 4H-SiC HPSI substrate responsible for substrate compensation.The analytical model is used to exhibit DC I–V characteristics of the device with and without trapping and thermal effects. From the results, the current degradation is observed due to the surface and substrate trapping effects and the negative conductance introduced by the self-heating effect at a high drain voltage. The calculated results are compared with reported experimental and two-dimensional simulations（Silvaco -TCAD）. The proposed model also illustrates the effectiveness of the gate–source distance scaling effect compared to the gate–drain scaling effect in optimizing 4H-SiC MESFET performance. Results demonstrate that the proposed I–V model of 4H-SiC MESFET is suitable for realizing SiC based monolithic circuits（MMICs） on HPSI substrates.