Science Letters:Multi-frequency proportional-resonant (MFPR) current controller for PWM VSC under unbalanced supply conditions

This letter presents a multi-frequency proportional-resonant (MFPR) current controller developed for PWM voltage source converter (VSC) under the unbalanced supply voltage conditions. The delta operator is used in place of the shift operator for the implementation of MFPR by using a low-cost fixed-point DSP. The experimental results with an alternative control strategy validated the feasibility of the proposed MFPR current controller for the PWM VSC during voltage unbalance.

RESEARCH ON THE PERFORMANCE OF NEW TYPE OF PROPORTIONAL PESSURE AND FLOW CONTROL VALVE

A new closed loop flow controlling principle through correcting the valve'sopening area while load pressure is changing is carried out. Further more a principle using only oneproportional valve to compound control pressure and flow is suggested. By using very simpleproportional throttle valve in structure, the functions that five kinds of proportional valves orany two of them combined possess can be complimented. After analyzing, comparing, and testing thedynamic and static characteristics of valve with different controlling principles and main valvestructure styles, the optimized structure styles and control methods are achieved.

Water-Assisted Injection Molding System Based on Water Hydraulic Proportional Control Technique

Water-assisted injection molding（WAIM）, an innovative process to mold plastic parts with hollow sections, is characterized with intermittent, periodic process and large pressure and flow rate variation. Energy savings and injection pressure control can not be .attained based on conventional valve control system. Moreover, the injection water can not be supplied directly by water hydraulic proportional control system. Poor efficiency and control performance are presented by current trial systems, which pressurize injection water by compressed air. In this paper, a novel water hydraulic system is developed applying an accumulator for energy saving. And a new differential pressure control method is proposed by using pressure cylinder and water hydraulic proportional pressure relief valve for back pressure control. Aiming at design of linear controller for injection water pressure regulation, a linear load model is approximately built through computational fluid dynamics（CFD） simulation on two-phase flow cavity filling process with variable temperature and viscosity, and a linear model of pressure control system is built with the load model and linearization of water hydraulic components. According to the simulation, model based feedback is brought forward to compensate the pressure decrease during accumulator discharge and eliminate the derivative element of the system. Meanwhile, the steady-state error can be reduced and the capacity of resisting disturbance can be enhanced, by closed-loop control of load pressure with integral compensation. Through the developed experimental system in the State Key Lab of Fluid Power Transmission and Control, Zhejiang University, China, the static characteristic of the water hydraulic proportional relief valve was tested and output pressure control of the system in Acrylonitrile Butadiene Styrene（ABS） parts molding experiments was also studied. The experiment results show that the dead band and hysteresis of the water hydraulic proportional pressure relief valve are large, but the control precision and linearity can be improved with feed-forward compensation. With the experimental results of injection water pressure control, the applicability of this WAIM system and the effect of its linear controller are verified. The novel proposed process of WAIM pressure control and study on characteristics of control system contribute to the application of water hydraulic proportional control and WAIM technology.

Flow Control for a Two-Stage Proportional Valve with Hydraulic Position Feedback

The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor valve.Essentially,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load pressure.The flow fluctuation severely restricts the application of the Valvistor valve.In this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow valve.The mathematical model of this valve is established and linearized.Fuzzy proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control system.The feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main orifice.The results show that inference with BPNN can obtain the flow data fast and accurately.With the flow control method,the flow can keep at the set point when the pressure differential across the main orifice changes.The flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow valve.For the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes abruptly.The performances of hysteresis,linearity and bandwidth are in a high range.The linear mathematical model can be verified and the assumptions in the system modeling is reasonable.

A low-noise X-band microwave source with digital automatic frequency control for electron paramagnetic resonance spectroscopy

We report a new design of microwave source for X-band electron paramagnetic resonance spectrometer.The microwave source is equipped with a digital automatic frequency control circuit.The parameters of the digital automatic frequency control circuit can be flexibly configured for different experimental conditions,such as the input powers or the quality factors of the resonator.The configurability makes the microwave source universally compatible and greatly extends its application.To demonstrate the ability of adapting to various experimental conditions,the microwave source is tested by varying the input powers and the quality factors of the resonator.A satisfactory phase noise as low as-135 d Bc/Hz at 100-k Hz offset from the center frequency is achieved,due to the use of a phase-locked dielectric resonator oscillator and a direct digital synthesizer.Continuous-wave electron paramagnetic resonance experiments are conducted to examine the performance of the microwave source.The outstanding performance shows a prospect of wide applications of the microwave source in numerous fields of science.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

Simulation and Experiment Research on the Proportional Pressure Control of Water-assisted Injection Molding

Water-assisted injection molding（WAIM）,a newly developed fluid-assisted injection molding technology has drawn more and more attentions for the energy saving,short cooling circle time and high quality of products.Existing research for the process of WAIM has shown that the pressure control of the injecting water is mostly important for the WAIM.However,the proportional pressure control for the WAIM system is quite complex due to the existence of nonlinearities in the water hydraulic system.In order to achieve better pressure control performance of the injecting water to meet the requirements of the WAIM,the proportional pressure control of the WAIM system is investigated both numerically and experimentally.A newly designed water hydraulic system for WAIM is first modeled in AMEsim environment,the load characteristics and the nonlinearities of water hydraulic system are both considered,then the main factors affecting the injecting pressure and load flow rate are extensively studied.Meanwhile,an open-loop model-based compensation control strategy is employed to regulate the water injection pressure and a feedback proportional integrator controller is further adopted to achieve better control performance.In order to verify the AMEsim simulation results WAIM experiment for particular Acrylonitrile Butadiene Styrene（ABS） parts is implemented and the measured experimental data including injecting pressure and flow rate results are compared with the simulation.The good coincidence between experiment and simulation shows that the AMEsim model is accurate,and the tracking performance of the load pressure indicates that the proposed control strategy is effective for the proportional pressure control of the nonlinear WAIM system.The proposed proportional pressure control strategy and the conclusions drawn from simulation and experiment contribute to the application of water hydraulic proportional control and WAIM technology.

Improved control of intelligent excavator using proportional-integral-plus gain scheduling

Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to autonomously dig trenches without human intervention. One stumbling block is the achievement of adequate, accurate, quick and smooth movement under automatic control, which is difficult for traditional control algorithm, e.g. PI/PID. A gain scheduling design, based on the true digital proportional-integral-plus (PIP) control methodology, was utilized to regulate the nonlinear joint dynamics. Simulation and initial field tests both demonstrated the feasibility and robustness of proposed technique to the uncertainties of parameters, time delay and load disturbances, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner. The tracking error magnitudes for oblique straight line and horizontal straight line are less than 20 mm and 50 mm, respectively, while the velocity reaches 9 m/min.

Adaptive rotor current control for wind-turbine driven DFIG using resonant controllers in a rotor rotating reference frame

This paper proposes an adaptive rotor current controller for doubly-fed induction generator (DFIG), which consists of a proportional (P) controller and two harmonic resonant (R) controllers implemented in the rotor rotating reference frame. The two resonant controllers are tuned at slip frequencies ωslip+ and ωslip-, respectively. As a result, the positive- and negative-sequence components of the rotor current are fully regulated by the PR controller without involving the positive- and negative-sequence decomposition, which in effect improves the fault ride-through (FRT) capability of the DFIG-based wind power generation system during the period of large transient grid voltage unbalance. Correctness of the theoretical analysis and feasibility of the proposed unbalanced control scheme are validated by simulation on a 1.5-MW DFIG wind power generation system.

Research on Electro Hydraulic Proportional Control for Heavy Vehicle Blend Braking System

A blend braking system of heavy vehicle was proposed.The main control part of the system is the electro hydraulic proportional servo valve.A nonlinear model of brake cylinder controlled by the valve was deduced through the analysis of its control property and system feature.The transfer function of the system was also proposed,and the hydraulic inherent frequency and the PID closed-loop system feature were calculated.The simulated result is consistent with those tested in the bench and on the site with 50 t heavy vehicle.The experimental result shows that the control method has quick response and high precision.

A Novel Resonant Frequency Tracking Control for Linear Compressor Based on MRAS Method

To optimize the efficiency of the linear compressor,its operating frequency must be controlled equal to the system resonant frequency.The traditional resonant frequency tracking control algorithm relies on the steady state characteristics of the system,which suffers from slow convergence speed,low accuracy and slow system response.In order to solve these problems,a novel resonant frequency tracking control for linear compressor based on model reference adaptive system(MRAS)is proposed in this paper,and the parameter adaptive rate is derived by the Popov's hyperstability theory,so that the system resonant frequency can be directly calculated through the parameter adaptive rate.Furthermore,the traditional algorithm needs to calculate the piston stroke signal by integrating the back-EMF,which has the problem of integral drift.The algorithm proposed in this paper only needs the velocity signal,and the accuracy of the velocity calculation can be ensured by utilizing the self-adaptive band-pass filter(SABPF),thereby greatly improving the accuracy of the resonance frequency calculation.Simulation results verify the effectiveness of the proposed algorithm.

Performance enhancement of a viscoelastic bistable energy harvester using time-delayed feedback control

This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Hybrid internal model control and proportional control of chaotic dynamical systems

A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

Performance Analysis of PI and Fuzzy Control for Modified LCC Resonant Converter Incorporating Boost Converter

In this paper, the modified LCC type of series-parallel Resonant Converter (RC) was designed and state-space modeling analysis was implemented. In this proposed converter, one leg of full bridge diode rectifier is replaced with Synchronous Rectifier (SR) switches. The proposed LCC converter is controlled using frequency modulation in the nominal state. During hold-up time, the SRswitches control is changed from in-phase to phase-shifted gate signal to obtain high DC voltage conversion ratio. Furthermore, the closed loop PI and fuzzy provide control on the output side without decreasing the switching frequency. The parameter such as conduction loss on primary and secondary side, switching loss, core and copper also reduced. Simultaneously, the efficiency is increased about 94.79 is realized by this scheme. The proposed converter with an input of 40 V is built to produce an output of 235 V with the help of ZVS boost converter [1] even under line and load disturbances. As a comparison, the closed loop fuzzy controller performance is feasible and less sensitive than PI controller.

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model（NPM）. We propose that a proportional-derivative（PD） type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM.

Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.