Traditional Proportional Integral Controller Research Articles

Improved LVRT Performance of PV Power Plant Using Recurrent Wavelet Fuzzy Neural Network Control for Weak Grid Conditions

An intelligent control method using recurrent wavelet fuzzy neural network (RWFNN) is proposed to improve the low-voltage ride through (LVRT) performance of a two-stage photovoltaic (PV) power plant under grid faults for the weak grid conditions. The PV power plant comprises an interleaved DC/DC converter and a three-level neutral-point clamped (NPC) smart inverter, in which the output active and reactive powers of the inverter can be predetermined in accordance with grid codes of the utilities. Moreover, for the purpose of improving the control performance of the PV power plant to handle the grid faults for the weak grid conditions, a new RWFNN with online training is proposed to replace the traditional proportional-integral (PI) controller for the active and reactive powers control of the smart inverter. Furthermore, the proposed controllers are implemented by two floating-point digital signal processors (DSPs). From the simulation and experimental results, excellent control performance for the tracking of active and reactive powers under grid faults for the weak grid conditions can be achieved by using the proposed intelligent control method.

Optimizing zinc electrowinning processes with current switching via Deep Deterministic Policy Gradient learning

This paper proposes a model-free Deep Deterministic Policy Gradient (DDPG) learning controller for zinc electrowinning processes (ZEP) to save energy consumption during the current switching periods. To overcome the problems such as inaccurate modeling and various time delays, the proposed DDPG controller utilizes various control periods and parameters for different working conditions. Strategies such as action boundary setting, reward function definition, state normalization are applied to ensure its learning performance. Simulations and experiments show that the DDPG learning controller can significantly decrease energy consumption during the ZEP current switching periods. The optimal control policy will be learnt for different working conditions with only one group hyperparameters. Furthermore, the smoother control actions of the DDPG controller will improve the stability and reduce more energy consumption by comparing with traditional proportional-integral (PI) controller, model predictive control (MPC) and artificial experiences. The artificial intelligence-based optimal control framework brings both energy saving and intelligence to zinc manufacturing plants.

DC Side Bus Voltage Control of Wind Power Grid-Connected Inverter Based on Second-Order Linear Active Disturbance Rejection Control

In order to improve the dynamic response speed and the steady-state performance of the DC side bus voltage of the wind power grid-connected inverter, a mathematical model of a typical three-phase voltage type PWM (Pulse Width Modulation, PWM) grid-connected inverter was established, and its traditional voltage-current double closed loop with proportional-integral control method was analyzed. Then a second-order linear active disturbance rejection controller that does not depend on system model information was designed to replace the traditional voltage outer loop proportional-integral controller, thus a new double closed-loop control structure was formed to control it. The frequency domain theory was used to analyze the convergence of the third-order linear extended state observer and the influence of the total disturbance on the performance of the third-order linear extended state observer. The parameter tuning scheme of the designed controller was given. Finally, the 1.5 MW direct-driven permanent magnet wind power generation system was built in the Matlab/Simulink software and the control effects of the two control modes under different working conditions are compared. The simulation results show that the control scheme designed in this paper is superior to the traditional proportional-integral controller which has good anti-interference characteristics and robustness. Especially it has a good stability effect on DC side bus voltage fluctuations.

HVDC Light Transmission System with Fuzzy Logic Based PI Controller

In the recent times there are many advancements in the sector of power electronic equipment. HVDC transmission system is further developed into HVDC light transmission system by replacing of thyristor valves with IGBT valves. There are a lot of advantages with HVDC light system compared to normal HVDC. When HVDC light transmission is confronted with fault, then the voltage and current vary, and they takes more time to come back to their steady state with PI controller. In this paper fuzzy logic based PI controller is proposed to reduce the time to reach their normal state, and improve the system steady state. The recommended controller is compared with traditional PI (proportional integral) controller for different control requirements, DC voltage, and reactive power under sudden disturbances such as three phase to ground fault. The performance of HVDC light system with traditional PI and fuzzy-PI shall be tested on under three-phase faults using MATLAB-Simulink software.

Simulating an induction motor multi-operating point speed control using PI controller with neural network

The Induction Motors (IM) speed widely influenced due to various motor loading conditions. When the load is applied the motor speed is reduced from the reference speed. This work presents a Matlab simulation of a Proportional Integral (PI) controller incorporating Neural Network for IM speed controls. The motor speed response profile under this control is improved and still constant at the point of load applied. Also, this controller stilled operates efficiently at a wide range of operating frequencies when compared with the traditional PI controller.

Seamless Dynamics for Wild-Frequency Active Rectifiers in More Electric Aircraft

In this article, a seamless dynamics controller for wild-frequency active rectifiers in more electric aircraft (MEA) is presented. The novelty of the proposed control scheme resides in its ability to seamlessly regulate the output dc-bus voltage and input reactive power in the presence of rapid frequency changes. These smooth dynamics are achieved through a multivariable direct model reference adaptive control (MRAC) formulation, which allows the gains of the controller to adjust themselves to the wild-frequency operation of the MEA power generation. The validity and performance effectiveness of the proposed seamless dynamics control scheme is verified experimentally through a laboratory-scaled three-phase 1.5-kW 270-V SiC two-level voltage-source-converter using a variable-frequency programmable grid emulator. Moreover, a traditional proportional-integral controller is implemented experimentally with the same converter as a benchmark to highlight the merits of the proposed MRAC.

Improved speed response of DC motor via intelligent techniques

<p>The classical Proportional- Integral (PI) control for Direct Current (DC) motor causes slow response of actual speed with high overshoot and undershoot which leads to sluggishness of the system. To minimize the problem of PI controller, intelligent technique based on hybrid neural network sliding mode control NN-SMC is suggested. The benefits of SMC are that it is simple, and tough to parameter deviations as compared with other controllers. In this paper, the neural network NN is used to minimize the error between reference speed and actual speed. In addition, the SMC aim is to control and optimize the voltage that is supplies the DC motor which guarantees the robust performance of the speed controller under disturbances. The proposed method for the speed control is first calculated and executed to DC motor by using MATLAB SIMULINK. The results of the suggested NN-SMC are compared with the traditional PI controller. The results obviously show the supremacy of NN-SMC over PI controller.</p>

Intelligent PV Power System With Unbalanced Current Compensation Using CFNN-AMF

A novel method is proposed to compensate the three-phase unbalanced currents of power grid under three-phase unbalanced load for a two-stage photovoltaic (PV) power system without the augmentation of active power filter. The PV power system is composed of an interleaved dc/dc converter and a three-level neutral-point clamped inverter. Moreover, the PV power system possesses the smart inverter function, in which the output active and reactive powers of the PV inverter are predetermined by a power factor according to grid codes of the utilities. In the proposed method, $dq0$ -axis compensation currents are obtained through low-pass filters to compensate the three-phase unbalanced currents of power grid. Furthermore, in order to improve the control performance of the dc bus voltage of the PV power system under unbalanced load variation condition, an online-trained compensatory neural fuzzy network with an asymmetric membership function (CFNN-AMF) is proposed to replace the traditional proportional-integral controller for the dc bus voltage control. In the proposed CFNN-AMF, the compensatory parameter to integrate pessimistic and optimistic operations of fuzzy systems is embedded in the CFNN. In addition, the dimensions of the Gaussian membership functions are directly extended to AMFs. Additionally, the proposed controllers of the PV power system are implemented by two control platforms using floating-point digital signal processor. Finally, excellent compensation performance for the three-phase currents of power grid under three-phase unbalanced load can be achieved from the experimental results.

Gain scheduling design based on active disturbance rejection control for thermal power plant under full operating conditions

To integrate more renewable energy into the power grid, thermal power plants have to accelerate the speed of power output and extend their operating ranges, and this can result in great challenges for their safe operations and even safety accidents. To this end, a gain scheduling design based on active disturbance rejection control (ADRC) is proposed for thermal power plants under full operating conditions. The urgency of the proposed control strategy is illustrated by analyzing the control difficulties of coordinated control systems. Then the scheduling parameter selection and the linear switching method for the proposed control strategy are analyzed. Moreover, the qualitative stability analysis based on the Kharitonov theorem and the quantitative calculation of stability regions are carried out to ensure the stability of the closed-loop system. Simulations of the power tracking under different load tracking rates and disturbance rejection under the coal quality variation are carried out. Simulation results show that the tracking and disturbance rejection performance in both power output and throttle pressure loops has been improved simultaneously compared with the regular ADRC and the traditional proportional-integral control strategies. Based on the verified superiority, the proposed gain scheduling design based on ADRC shows a promising potential in industrial applications.

Adaptive Backstepping Sliding Mode Control for the Vertical Launching Barrel-Cover of the Underwater Missile

The vertical launching barrel-cover device is a symmetry mechanism, so we can simplify this symmetry mechanism into an electro-hydraulic servo problem. The vertical launching barrel-cover of the underwater missile has parameter uncertainty, load time-varying and strong nonlinear of motion and coupling during the submarine movement. Therefore, it is important to study the nonlinear adaptive antidisturbances control method of the vertical launching barrel-cover. For the vertical launching cover system of the underwater missile, an adaptive backstepping sliding mode control system based on disturbance observer is proposed. The backstepping sliding mode controller is used to solve the problem of nonlinearity and chattering in the system; the adaptive method is used to dynamically follow the changes of the system characteristics, adjust the controller parameters. At the same time, the disturbance observer is added to the system to reduce the sensitivity of the system to disturbance By completing the process of switching cover, we have experimented with the designed adaptive backstepping sliding mode controller to verify the effectiveness of the controller. The controller improves the stability of the whole switch cover system. The experimental results show that compared with traditional proportional integral (PI) controller and sliding mode controller, the controller solves the problem of over-limit when the cover is in place, and has excellent tracking performance in the process of the switch cover.

Adaptive velocity-dependent proportional-integral controller for high-speed atomic force microscopy.

High-speed atomic force microscopy (AFM) has been rapidly developed in recent years. To reduce the oscillation of the scanner, a single-tone sinusoidal wave is widely used as a scanning wave rather than a triangular wave in high-speed AFM. However, the sinusoidal wave is nonlinear, resulting in a nonconstant relative linear velocity between the sample and the tip while scanning in the x-direction. If a traditional proportional-integral controller is still used as a feedback controller in the z-direction, the control errors will be enormous. Therefore, the paper proposes a new adaptive velocity-dependent proportional-integral controller. The relationship between the proportional-integral parameters and the linear velocity is achieved by fitting the experimental results. The adaptive and traditional controllers are compared against each other in some examples. The experiments demonstrate that the adaptive controller decreases the control errors in the z-direction to a half, which provides more precise AFM images. LAY DESCRIPTION: Typically, the scanner follows a triangular waveform in fast axis (x-axis), and follows a very slow ramp signal in the slow axis (y-axis) of conventional AFM. This scanning mode can be called raster scan. However, the triangular waveform contains high-order Fourier harmonics, vibrating the scanner and distorting the image easily. In high-speed AFM, the effect of the high-order Fourier harmonics will be more severe. The above problems can be solved by replacing triangular waves with single-tone sinusoidal waveform. Therefore, the sinusoidal-raster scan and nonraster scan based on the sinusoidal waveform are widely used in high-speed atomic force microscopy. However, the nonlinearly scan path will cause a variable relative linear velocity between the sample and the tip. If a standard proportional-integral controller is still used as a feedback controller in Z direction, the control errors will be large, and this difference will be evident at high-speed scanning. Thus, the paper proposes a new adaptive velocity-dependent proportional-integral controller to solve this problem. Experiments show that the control errors obtained by using the adaptive controller is about a half of that without using it. These illustrate that the proposed method can improve the image quality of the AFM at both low and high scan speeds.

Design of Backstepping Direct Power Control for Three-Phase PWM Rectifier

This study focuses on the backstepping control (BSC) design for the direct power control of a three-phase voltage-source pulsewidth-modulation rectifier. The power factor of this three-phase rectifier can be adjusted by controlling the instantaneous reactive power and the dc output voltage simultaneously. In the proposed BSC system with the consideration of system uncertainties, it can be divided into two independent backstepping controllers by introducing two decoupling control signals, and the corresponding controller parameters can be adjusted independently. As a result, both the stable dc-bus output voltage and the sinusoidal input current with a lower total-harmonic-distortion value can be obtained. Moreover, instantaneous active and reactive powers also can be indirectly controlled. In addition, the robustness against power grid fluctuation, step load change, and filter inductance variation can be achieved. The effectiveness of the proposed BSC system is verified by numerical simulations as well as realistic experiments, and its merits are indicated in comparisons with traditional proportional-integral control and proportional-resonant control.

Robustness Improvement of FCS-MPTC for Induction Machine Drives Using Disturbance Feedforward Compensation Technique

Finite control set-model predictive torque control (FCS-MPTC) has a fast dynamic response because this algorithm directly selects the optimal voltage vector by its cost function for induction machine drives fed by voltage source inverter (VSI). However, belonging to open-loop control paradigm, the FCS-MPTC has torque tracking error due to inevitable load disturbance and mismatched model parameters in reality. In traditional FCS-MPTC, the outer loop, i.e., speed loop, adopts a classic proportional integral (PI) controller, abbreviated as PI-MPTC. The lumped disturbance is only suppressed by a PI controller. However, pole placement of the PI controller is usually designed by cut-and-trial, which is difficult to simultaneously achieve optimal dynamic performance and optimal suppression of lumped disturbance. In this paper, the FCS-MPTC with mismatched parameters is first analyzed. Second, the deficiencies of the traditional PI controller are introduced. Third, disturbance feedforward compensation-based-model predictive torque control (DFCB-MPTC) of induction machine is proposed to compensate lumped disturbance and improve the performance of the system. Furthermore, a simplified stator flux observer is proposed, whose gain matrix is independent of rotor speed. Experimental results verify the feasibility of the proposed DFCB-MPTC. Compared with traditional PI-MPTC, the proposed DFCB-MPTC has better dynamic performance, steady performance, and stronger robustness.

Maximum Power Generation Control of a Hybrid Wind Turbine Transmission System Based on H∞ Loop-Shaping Approach

This paper presents the design, modeling, and optimal power generation control of a large hybrid wind turbine transmission system that seamlessly integrates planetary/parallel gear sets with a hydraulic transmission to improve the turbine's reliability and efficiency. The hybrid wind turbine has power splitting flows including both mechanical and hydraulic power transmissions. The turbine transmission ratio can be controlled to continuously vary for the maximum wind power extraction and grid integration. Dynamics of the hybrid wind turbine is modeled as an incremental disturbed state space model based on the dynamic equations of each mechanical/hydraulic element. To achieve good tracking and robustness performance, an optimal H∞ loop-shaping pressure controller is designed, which accurately tracks the optimal load pressure in the hydraulic transmission for maximizing wind power generations. The validations of the proposed hybrid wind turbine and the H∞ loop-shaping pressure controller are performed based on a detailed aero-hydro-servo-elastic hybrid type wind turbine simulation platform with both mechanical geared transmission and hydraulic transmission, which is adapted from the National Renewable Energy Laboratory 5 MW monopile wind turbine model within fatigue, aerodynamics, structures, and turbulence code. The validation results demonstrate that the hybrid wind turbine achieves better performance in both the maximum wind power extraction and power quality than the hydrostatic wind turbine. In addition, the proposed H∞ loop-shaping pressure controller has better tracking performance than the traditional proportional integral controller.

Real-Time Force Tracking Control of an Electro-Hydraulic System Using a Novel Robust Adaptive Sliding Mode Controller

This article focuses on a novel robust adaptive sliding mode control strategy of an electro-hydraulic force loading system with consideration of external disturbances and parameter uncertainties. To obtain the proposed controller, the nonlinear dynamic model of the electro-hydraulic force loading system is firstly provided, where external disturbances and system’s uncertain parameters are merged. Then, with consideration of external disturbances and parameter uncertainties, a robust adaptive sliding mode controller for the force control system is proposed and designed according to Lyapunov stability theory. The proposed controller has the merit of suppressing chattering phenomenon in traditional adaptive backstepping controllers when designing sign functions. In order to verify effectiveness and feasibility of the proposed controller, experimental studies are implemented on an electro-hydraulic force loading system by xPC rapid prototyping technology. Experimental results demonstrate that the proposed controller exhibits more excellent performance on force tracking control in comparison of a traditional proportional-integral controller and an adaptive backstepping controller.

Nonlinear Decoupling Control of Two-Terminal MMC-HVDC Based on Feedback Linearization

The traditional proportional-integral control for a modular multilevel converter (MMC) design based on a two-level voltage source converter does not consider the dynamics of arm circulating currents and sub-module capacitor voltages, which will lead to the incomplete decoupling between powers and circulating currents for an MMC. In view of this, a nonlinear decoupling control strategy, which applies for two scenarios, e.g., active/reactive power control for a power controlled station (PCS) and dc voltage/reactive power control for a dc-voltage controlled station (DVCS), is proposed for an MMC station based on feedback linearization. First, the nonlinear feedback laws for PCS and DVCS are derived based on the nonlinear equations of an MMC. Next, the complete nonlinear decoupling control strategies for PCS and DVCS are developed. Following that, the zero dynamics stabilities of the two control schemes for PCS and DVCS are investigated. In addition, the method to design parameters of the outer linear controller is also proposed to satisfy the requirement of dynamic performance. Taking a two-terminal MMC-HVDC for example, the simulation in Simulink validates the good transient performance of the proposed nonlinear control, and its robustness is also validated against the changing of system parameters.

A proton exchange membrane fuel cell with an airflow cooling system: Dynamics, validation and nonlinear control

This work synthesizes a reduced-order sliding mode observer-based sliding mode controller for a proton exchange membrane fuel cell system. This multivariable closed-loop system is dealt with two inputs (hydrogen fuel flow and cooling air flow rate) and two outputs (output voltage and stack temperature). For this, at first, we develop a nonlinear transient proton exchange membrane fuel cell model. This model is verified with the available experimental data. To maintain the fuel cell operating temperature, it is coupled with an airflow cooling fan. Then a nonlinear model-based control scheme is formulated that consists of sliding mode controller and reduced-order sliding mode observer. A special care is taken in control model against chattering response. Evaluating the sliding mode observer performance, it is integrated with sliding mode controller and the resulting hybrid control structure is compared with a traditional proportional integral controller. The nonlinear sliding mode observer-based controller shows its superiority over the proportional integral controller in rejecting the disturbance as well as tracking the set point.

Real-Time Performance Analyses and Optimal Gain-Scheduling Control of Offshore Wind Turbine Under Ice Creep Loads

At high latitudes, offshore wind turbines often face unfavorable loads by severe ice-induced vibrations during winter season, which may endanger facilities available on the platforms and degrade operating performance of wind turbine. Hence, it is vital to analyze the influences caused by ice loads. In this paper, based on a real-time simulation model, quantifiable analyses of performance losses due to ice creep loads are firstly studied deeply. Under ice creep loads, reliable pitch control is necessary to ensure safety and high-level power-tracking capability of modern offshore wind turbine. However, uncertain influences of ice creep loads are coupled with wind turbine operation and make it a challenge for wind turbine pitch control using traditional Proportional-Integral (PI) controller from the view of industry. As a result, improved pitch control using optimal gain-scheduling strategy is proposed to alleviate impacts of ice loads where the support vector regression algorithm is adopted to represent the strong nonlinear relationship among PI parameters under different operation conditions. For each operation point, PI parameters are optimally tuned by the particle swarm optimization algorithm. Finally, the presented nonlinear optimal gain-scheduling PI (OGS-PI) controller is applied on regulating generation power and reducing tower top displacement caused by ice creep loads based on software of Fatigue, Aerodynamics, Structures, and Turbulence, a high-fidelity wind turbine simulator. Simulation results show that unfavorable influence of ice creep loads to wind turbine operation can be significantly alleviated by the OGS-PI controller, which performs much better than the traditional PI controller.

Fuzzy Logic Control of the Ultracapacitor Interface for Enhanced Transient Response and Voltage Stability of a DC Microgrid

This paper proposes a novel fuzzy logic-based scheme to control the power flow from an ultracapacitor (UC) in a battery-UC hybrid energy storage system of a dc microgrid. The fuzzy logic controller determines the current reference for the UC converter to regulate the dc bus voltage tightly. Low-bandwidth controllers are designed for battery interfacing converter, which in combination with the proposed fuzzy controller, improve the quality of the current drawn from the battery. The fuzzy controller is simple to design and does not require the knowledge of the mathematical model of the system. It is a single input single output controller, which incurs low implementation complexity. It does not have “wind-up” issues as in the traditional proportional integral controller (PI)/PID controllers, which makes the controller relatively faster. In addition, the control strategy does not demand load current sensing. Low pass filter high pass filter (HPF) filters are also not used in this strategy, which eliminates the nonoptimal power-sharing problem associated with the frequency-based control strategies. The presented simulation results show the superiority of the proposed strategy over the conventional frequency-based control strategy. The hardware results validate the practical feasibility of the proposed scheme.

A hybrid control strategy for the optoelectronic stabilized platform of a seeker

In order to improve the rapidity and disturbance rejection rate of the optoelectronic stabilized platform of a seeker, a hybrid control strategy for stabilized loop of the optoelectronic stabilized platform is proposed in this paper. The hybrid control strategy consists of Butterworth low pass filter, disturbance observer (DOB), notch filter and incomplete derivative proportional integral derivative (IDPID) controller. Firstly, the controlling architecture and stabilized principle of the optoelectronic stabilized platform are analyzed. Secondly, the hybrid control strategy is analyzed. Finally, experiments of the seeker using the proposed hybrid control strategy and traditional proportional integral (PI) controller are carried out. In addition, the experimental set-up provides a comparison to the two controllers. Experimental results show that the requirements are totally met, the bandwidth of the stabilized loop with the proposed hybrid control strategy is 133.6 rad/s, and the disturbance rejection rate is 2.45%, which improve the performance of the seeker effectively.