PI Controller Research Articles

Optimized control strategy for a three-phase grid connected inverter using PI controller and DQ frame

This paper provides a proportional-integral (PI) controller and direct-quadrature (DQ) frame transformation-based optimum control method for a three-phase grid-connected inverter. In terms of grid synchronization, voltage regulation, and harmonic abatement, the proposed control technique attempts to improve the inverter's performance. By separating the control of active and reactive power, the control structure is made simpler and independent regulation of these parameters is possible. This improves the inverter's capacity to quickly react to grid disruptions and track reference values accurately. In order to lower carbon emissions and improve grid dependability, it has become vital to integrate renewable energy sources into the current power grid. Grid-connected inverters are essential in this situation because they transform DC electricity from renewable sources into grid-safe AC power. This abstract outline a proportional-integral (PI) controller and direct-quadrature (DQ) frame-based optimal control method for a three-phase grid-connected inverter using a MATLAB simulation.

Bio inspired technique for controlling angle of attack of aircraft

<p>This paper deals with the design of a proportional–integral (PI) controller for controlling the angle of attack of flight control system. For the first time teaching learning-based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed PI controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PI controller. The superiority of proposed approach is demonstrated by comparing the results with that of the conventional methods like genetic algorithm (GA) and particle swarm optimization (PSO). It is observed that TLBO optimized PI controller gives better dynamic performance in terms of settling time, overshoot, and undershoot as compared to GA and PSO based PI controllers. The various performance indices like mean square error (MSE), integral absolute error (IAE), and integral time absolute error (ITAE) are improved by using the TLBO soft computing techniques. Further, robustness of the system is studied by varying all the system parameters from −50% to +50% in step of 25%. Analysis also reveals that TLBO optimized PI controller gains are quite robust and need not be reset for wide variation in system parameters.</p>

Optimization of grid power quality using third order sliding mode controller in PV systems with multilevel inverter

Harmonic mitigation is essential in ensuring control over the level of current injected into the grid by a grid-connected inverter. This research proposes using a Third-Order Sliding Mode Control (TOSMC) to get the maximum power point tracking (MPPT) in a photovoltaic (PV) systemas well as to improve the performance and power quality of photovoltaic (PV) power systems connected to the grid. This study considers several quality concerns, reducing total harmonic distortion (THD) of the current, and integrating the energy supply from The photovoltaic system linking to the electrical network while thinking about non-linear demand. This enhancement is accomplished by integrating Two configurations: one oversees the boost DC-DC converter. At the same time, the other manages the DC-AC inverter it connects the PV system to the grid. The proposed strategy TOSMC utilizes a three-level neutral-point clamped (NPC) inverter with a phase-locked loop (PLL) technique for DC-AC conversion. This inverter employs modified pulse width modulation for direct current control. Additionally, the DC-DC converter is controlled by TOSMC to optimize power generation from the PV panel, regardless of its standard or unusual conditions. The photovoltaic (PV) system is connected to the alternating current (AC) grid, and a shunt active power filter (SAPF) supplies electricity to a non-linear load. The simulation results in this work, conducted using Matlab software are validated by comparing the TOSMC and the PI controller. According to performance monitoring, the findings show that the proposed TOSMC strategy is effective and well-regulated. The results indicate that the suggested TOSMC method mitigates steady-state error, overshoot, resilience, reduced power ripple, tracking efficiency, dynamic responsiveness, THD value, and feasibility in non-linear situations.

State Machine and Internal Model Control-based Hybrid Controller for Improved Transient Performance of Microgrids

The transient performance of microgrids is measured by their transient stability and transient response indices. The quality of these indices depends upon the design of the microgrid’s closed-loop control scheme, which is a cascaded combination of outer power controller and inner voltage-current (VA) controllers. Generally, the power controller is realized by droop control logic (fixed droop or adaptive droop), and VA controllers by conventional proportional-integral (PI) control. Control schemes with fixed droop coefficient logic and PI-based VA controllers suffer from stability and response issues. In this scheme, when these PI-based VA controllers are replaced with internal model control (IMC) based VA controllers, the response aspect is improved, while the stability aspect shows no improvement. Therefore, when fixed droop logic is replaced with adaptive droop control logic, stability is improved. However, adaptive droop coefficient schemes with PI-based VA controllers provide a limited improvement in stability. Moreover, conventional machine learning-based adaptive droop coefficient logic suffers from severe computational difficulties. It is verified in this work that IMC-based VA controllers which cannot improve stability with fixed droop logic, will contribute to stability enhancement when a suitable adaptive droop control logic is deployed. Therefore, to enhance both stability and response aspects with reduced computational effort, this paper proposes a hybrid control scheme made of a state machine-based droop controller (SMD) supported by IMC-based VA controllers. From the simulation results, while the conventional schemes could not withstand load power factors lesser than 0.707, the proposed hybrid controller scheme maintained stability at a power factor of 0.47 with a total harmonic distortion of less than 5%.

Low cost pulsed electric field generator using DC-DC boost converter and capacitor diode voltage multiplier

Traditional high-voltage pulse generators, like Marx generators often face challenges related to efficiency and complexity. In this paper, a solid-state multi-module high-voltage pulse generator that integrates capacitor-diode voltage multipliers (CDVM) with DC-DC boost converters and closed-loop voltage control is proposed to overcome these challenges. The system achieves high output voltage by coupling the pulsed output voltages of individual low-voltage DC sources in series across each module. The proposed design was modeled using MATLAB, and experimental testing was conducted on a single stage. Comparative analyses between timedomain parameters, proportional-integral (PI), and fractional order proportional integral derivative (FOPID) controllers were performed. Both MATLAB simulations and experimental validations demonstrate the effectiveness of this approach. The rise time, peak time, settling time, and steady-state error are all improved using an FOPID controller, decreasing from 0.32 to 0.31 seconds, 0.42 to 0.35 seconds, and 3.15 to 2.20 seconds, respectively. These findings indicate that a closed-loop FOPID controller enhances time-domain performance parameters more effectively than a PI controller for a two-stage DC-DC voltage multiplier.

Enhancing power quality in wireless DC power supplies through active power filtering: A computer simulation approach

This paper presents a computer simulation model for a high-power factor wireless DC power supply system, integrating an active power filter (APF) at the rectifier stage on the transmitter side using a rectifier boost technique. The APF, employing a MOSFET switch regulated by active pulse width modulation (APWM) within a current control loop, addresses pulsating and distorted AC supply currents caused by non-linear loads. A robust closed-loop control mechanism, including a subtractor circuit, proportional-integral (PI) controller, and comparator, ensures the generation of a continuous sinusoidal waveform synchronized with the supply voltage. The model utilizes a high-frequency inverter to convert DC to AC, which is then wirelessly transmitted via wireless power transfer (WPT) technology and converted back to DC by a high-frequency rectifier. MATLAB/Simulink simulation results show a significant reduction in total harmonic distortion (THD) of the AC supply current, complying with IEEE 519 standards. Selected results are presented to verify the proposed method's effectiveness in reducing harmonic distortions and enhancing power quality. This study highlights the advantages of WPT in scenarios where traditional wired connections are impractical and underscores the potential of this system for real-world applications, particularly in developing high-power factor wireless DC power supply systems.

Renewable Power Energy Management for Single and Three-phase Inverters Design

This study manages solar panels, wind turbines, and fuel cells to develop single- and three-phase Sinusoidal Pulse Width Modulation (SPWM) inverter circuits. The maximum power point tracking method in direct current (DC)-DC boost converters efficiently uses these renewable sources. Photovoltaic (PV), wind turbines, fuel cells, and bidirectional batteries are utilized in energy management. Efficiency, material cost reduction, and user convenience depend on energy management. The technology fully charges the standby battery when all sources are available. Other renewable sources will power the system if one fails. Before boost converter circuits, renewable energies generated 310V for PV, 60V for wind energy conversion, 215V for fuel cells, and 25.9V for bi-directional batteries. Proportional-integral (PI) controllers govern inverter switching to maintain high-quality sinusoidal outputs while decreasing total harmonic distribution (THD). Single-phase load voltage and current at resistive load have 0.65419% THD. Load voltage and current root main square (RMS) values are 217.3617 (V) and 3.1052 (A), respectively. When connected to an R load, the three-phase inverter circuit provides 1.5146% THD for load voltage and current. Load voltage and current RMS readings are 218.4261 (V) and 2.1843 (A). THD is 1.5969% for load voltage and 1.2905% for load current with an RL load. In this example, load voltage and current RMS values are 214.201 (V) and 2.0916 (A). Simulations demonstrate the successful integration of renewable sources to meet energy needs and maintain power supply. The above solutions use renewable energy efficiently and integrate with the grid.

Power quality improvement using PV fed series active power filter with enhanced Jaya optimized PI controller

Power quality improvement using PV fed series active power filter with enhanced Jaya optimized PI controller

Maximizing hydrogen production through photovoltaic generator by using improved incremental conductance algorithm with proportional integral PI controller

Effectively storing energy for prolonged periods poses a primary challenge for renewable and innovative energy sources. This research focuses on two key objectives: first, converting photovoltaic (PV) voltage to the necessary level for electrolysis through a buck converter, and second, utilizing a maximum power point tracking (MPPT) method to optimize the solar generator's efficiency. The simulation of the solar-driven buck converter for the electrolysis load was carried out using MATLAB/Simulink, integrating an Incremental Conductance (INC) MPPT algorithm with a PI controller for system optimization. The simulation results reveal the stabilization of both the generated power from the PV system and the load voltage. Significantly, the proposed system achieves an efficiency surpassing 90% under high irradiance levels.

Hardware implementation of a novel intelligent fuzzy fractional order proportional-integral (FFOPI) controller for a coupled tank liquid level control system

Hardware implementation of a novel intelligent fuzzy fractional order proportional-integral (FFOPI) controller for a coupled tank liquid level control system

Brayton-Moser passivity based controller for constant power load with interleaved boost converter.

A DC microgrid with renewable energy sources can achieve reduced current ripple, higher efficiency, faster dynamics, high voltage gain, and less operational stress by interfacing with an interleaved boost converter (IBC). The stability of an IBC linked to a DC microgrid supplying a constant power load (CPL) can be imperceptibly guaranteed by a conventional controller. A tightly regulated CPL with nonlinear and negative incremental impedance characteristics will lead to stability issues. Uncertainties such as load and line variations will further affect the stability of the system. A nonlinear passivity-based control algorithm requires more attention than a traditional controller to achieve the stability of power converters. This article explains the Brayton-Moser (BM) passivity-based controller (PBC) for a 2-level interleaved boost converter (IBC) interfaced DC microgrid with CPL. The suggested controller can achieve high signal stability by injecting a series-connected virtual impedance. The stability of the proposed controller has been assessed using the Lyapunov stability approach. A BM passivity-based controller for a 2-level IBC with CPL has been derived and investigated under various operating modes using MATLAB and Simulink. It was also observed that the proposed system achieves at least improvement in efficiency and reduction in current ripple. To evaluate the performance of BM Passivity-based controller, a comparative analysis was performed between the suggested controller and the traditional PI controller, which is also included in this paper.

Closed-loop control strategy design for Caputo–Fabrizio definition-based fractional-order Boost converters considering parametric uncertainties

This paper proposes a dual closed-loop adaptive PI control system based on parameter identification for Caputo–Fabrizio (C-F) definition-based fractional-order boost converters. First, a C-F definition-based fractional-order model of the Boost converter is derived. Afterward, an online component parameter identification method is proposed to obtain the values and orders of capacitors and inductors in the proposed model. Based on these identified parameters, a dual closed-loop adaptive PI control system considering parametric uncertainties for the Boost converters is designed using the frequency domain analysis method. Finally, simulation validations are conducted. The online parameter identification method can accurately identify the values and orders of capacitors and inductors. The identification error is less than [Formula: see text] for the capacitance value and [Formula: see text] for the other parameters. Moreover, the proposed control system can automatically adjust the parameters with changes in the component parameters, effectively improving the robustness. Compared to traditional PI controllers, when the parameters of components change, the proposed control system can reduce voltage overshoot by [Formula: see text] in the case of sudden changes in the input voltage. These results confirm the efficacy of the proposed online parameter identification method and the dual closed-loop adaptive PI control system.

Improved Droop Control Strategy for Microgrids Based on Auto Disturbance Rejection Control and LSTM

This thesis proposes an improved droop control strategy design based on active disturbance rejection control and LSTM. This strategy uses the droop control method to coordinately control the distributed generation units (DGs) in a microgrid to achieve stable operation of the microgrid system. Linear-Auto Disturbance Rejection Control (LADRC) is introduced and an improved LADRC is designed based on the error principle. A disturbance compensation link is introduced on the basis of traditional LADRC to form ILADRC and a droop control strategy is used. Instead of improving the PD controller in LADRC, an improved droop control strategy is formed, which not only achieves natural decoupling between powers, but also improves the system’s immunity and transient operation capabilities. At the same time, in order to achieve adaptive parameter tuning in the improved droop control strategy, this article introduces long short-term memory (LSTM) to form an adaptive improved droop control strategy which further improves the system’s immunity and robustness. This article builds a simulation model through the MATLAB/Simulink simulation experiment platform and tests PI control and traditional droop control. The strategy and the improved droop control strategy designed in this thesis are experimentally compared and verified, and simulation analysis and verification are conducted on the two working conditions. The simulation results clearly demonstrate the superiority of the improved droop control strategy over PI control and traditional droop control, indicating that the correctness and reliability under various working conditions are verified.

Advanced hybrid control for induction motor combining ANN-PID speed controller with neural predictive current regulator based on particle swarm optimization

This paper presents a hybrid control strategy for an induction motor (IM) organized into two nested loops. In the outer loop, an adaptive artificial neural network-based proportional-integral-derivative (ANN-PID) controller is used for speed control. The ANN-PID is divided into two stages: the first stage includes an adaptive ANN speed estimator, and the second stage includes an adaptation algorithm that fine-tunes both the weights and biases of the ANN estimator and the parameters of the PID controller. In the internal loop, a predictive current controller is used to control IM currents using neural networks. Specifically, the neural predictive controller (NPC) approaches the control problem by presenting it as an optimization problem using a neural predictor for IM currents. The considered objective function includes two elements: the current tracking error and the electromagnetic torque ripple. This function is computed over a given time horizon informed by predictions of IM currents. The particle swarm optimization (PSO) algorithm is applied to determine the optimal solution for this optimization task. The effectiveness of the hybrid control scheme is demonstrated by simulation results obtained using Matlab/Simulink, highlighting its superiority over conventional control methods. The proposed hybrid control is characterized by a reduction in torque ripple and overshoot, while also showing robustness to variations in load, rotor resistance, and rotor inductance. Comparisons with an ANN controller and a fuzzy PI controller further demonstrate the superior performance of the hybrid controller in handling nonlinear dynamics and maintaining control accuracy under various operating scenarios.

Intelligent Control of an Experimental Small-Scale Wind Turbine

Nowadays, wind turbines are one of the most popular devices for producing clean and renewable electric energy. The rotor blades catch the wind’s kinetic energy to produce rotational energy from the turbine and electric energy from the generator. In small-scale wind turbines, there are several methods to operate the blades to obtain the desired speed of rotation and power outputs. These methods include passive stall, active stall, and pitch control. Pitch control sets the angular position of the blades to face the wind to achieve a predefined relationship between turbine speed or power and wind velocity. Typically, conventional Proportional Integral (PI) controllers are used to set the angular position of the rotor blades or pitch angle. Nevertheless, the quality of speed or power regulation may vary substantially. This study introduces a rotor speed controller for a pitch-controlled small-scale wind turbine prototype based on fuzzy logic concepts. The basics of fuzzy systems required to implement this kind of controller are presented in detail to counteract the lack of such material in the technical literature. The knowledge base of the fuzzy speed controller is composed of Takagi–Sugeno–Kang (TSK) fuzzy inference rules that implement a dedicated PI controller for any desired interval of wind velocities. Each wind velocity interval is defined with a fuzzy set. Simulation experiments show that the TSK fuzzy PI speed controller can outperform the conventional PI controller in the speed and accuracy of response, stability, and robustness over the whole range of operation of the wind turbine prototype.

The effect of different mission profiles and ambient temperature on the lifetime of boost converter IGBT with a robust controller in a hybrid electric vehicle

AbstractThe reliability of power electronic converters is one of the essential issues in designing of electric vehicles. This paper estimates the lifetime of the boost converter switch by Semikron and Coffin‐Manson models for two common failure mechanisms of Bond wire and Base plate solder, respectively. Four mission profiles based on the Artemis standard are applied to hybrid electrical vehicle model to determine unidirectional output power. Kharitonov's theory is used to design a robust controller to handle the uncertainty raised by different power cycles of the electric vehicle and the parameters of the converter during simulation. Stability of converter is achieved during simulation by identifying simple proportional integral controller coefficients with Kharitonov's theorem. A prototype 230 W boost converter is designed and utilized to validate average model and switch loss calculation relationships. The lifetime results indicate that the number of cycles, and the average and the maximum junction temperature have a more impact than the duration of the drive cycle on the lifetime of the converter. A mixed mission profile is considered to investigate the effect of sudden change in driving modes and speed on total consumed life and lifetime to enhance the study's applicability. Lifetime of switch is decreased significantly in mixed mode in comparison with other mission profiles in the same driving time. Furthermore, the motorway mission profile has 53%, 39.6%, and 160% less total consumed life in comparison with the urban, rural and mixed mission profiles, respectively. In addition, the effect of ambient temperature changes on IGBT lifetime has been investigated for four mission profiles. While motorway had the least total consumed life in 25°C, the urban had better performance in comparison with other mission profiles from 25 to 55°C.

Modeling and Control of Dual Active Bridge‐Modular Multilevel Converter‐Based Solid State Transformer for Grid Integration of SPV and Battery Energy Storage

ABSTRACTThis article deals with the modeling and control of a solid‐state transformer (SST) based on a dual active bridge (DAB) and modular multilevel converter (MMC) for integrating solar photovoltaic (SPV) and battery energy storage (BES) systems into the grid. SST uses DABs for bidirectional DC‐DC conversion and an MMC for DC‐AC conversion. A hybrid control method is developed in this study, which combines proportional‐integral (PI) controllers and model predictive control (MPC) to achieve the multiple objectives of the SST. The DABs' control system uses PI controllers for power extraction from the SPV system and to regulate the charging and discharging of the BES according to power generation and demand fluctuations. MPC is applied to control the active power injection, regulate the DC‐link and sub‐module capacitor voltages of the MMC. Moreover, the developed hybrid control method ensures reliable SST performance even under adverse conditions like grid voltage distortion, unbalance, and frequency variations. An energy management strategy is developed based on total power generation, reference active power injection, and the state of charge of the BES. This strategy ensures accurate reference power injection to the grid despite dynamic changes in operating conditions. The article also presents a detailed mathematical model of the DAB and MMC components, and the stability of the control algorithm is analyzed theoretically. The effectiveness of the SST and the proposed hybrid control scheme is demonstrated through MATLAB/Simulink simulations and hardware‐in‐the‐loop experimental results under various operating conditions.

Model-Free Filter-Based Trajectory Tracking Controller for Two-Wheeled Vehicles Through Pole-Zero Cancellation Technique

Considering the nonlinear dynamics, this paper devises an advanced position trajectory tracking controller with a model-free filter for two-wheeled vehicle (TWV) applications. The proposed technique preserves a simple structure in the form of the proportional–integral (PI) controller involving the model-free filter and nonlinearly structured feedback gains, which make the following contributions: (a) the proposed filter smooths the position and yaw angle measurements according to the first-order convergence rate without any model information; and (b) the PI control with the nonlinearly structured feedback gains robustly stabilizes the position and yaw angle errors along the desired first-order system to accomplish the trajectory tracking mission, which is obtained by the pole-zero cancellation (PZC) in the presence of modeling errors. MATLAB/Simulink was used to emulate the resulting feedback system and validate the effectiveness of the proposed technique.

Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

Abstract One of the main objectives of this research is to construct a high-fidelity aerothermal model for controlling the turboshaft engine power turbine rotational speed. Firstly, a high-fidelity aerothermal model of General Electric T700 is formed. The turboshaft engine aerothermal model is simulated and compared to engine design point data on MATLAB/Simulink environment. Thermodynamic equations and some algebraic equations are used. In predicting compressor mass flow rate, the adaptive neuro-fuzzy inference system method is preferred. A propeller model is also added to the turbo shaft engine aerothermal model and to keep the power turbine rotational speed at a constant value, a Proportional Integral Derivative controller is designed and applied. Open-loop and closed-loop simulations are conducted and successful outcomes are achieved. Results indicate that the differences between simulation and actual engine data are within acceptable limits. The suggested model can be readily updated and expanded to control additional parameters of the engine. PACS 2010 Classification: Control theory in mathematical physics, 02.30. Yy, Computer modeling and simulation, 07.05.Tp, 05.70.Ce Thermodynamic functions and equations of state.

Research on characteristic and DC voltage balancing control of a novel three‐phase line‐voltage cascaded unity power factor rectifier under unbalanced grid

AbstractAccording to the operating modes of three‐phase line‐voltage cascaded boost high power factor rectifier topology, the operating characteristics of the rectified output voltage of each module and the characteristics of the topology for automatically balancing the input current under the unbalanced grid are analyzed in this article. Based on the analysis to the unique feature, a simple dual‐loop PI control strategy in the rotating coordinate system is designed with no need to deal with the negative sequence component of grid voltage. In response to the issue of unbalanced DC‐link capacitor voltage of each module caused by unbalanced grid, injection of the zero‐sequence voltage component is adopted in the designed control system, which make the output power of each module be able to be independently regulated, so that the balancing control to the DC‐link capacitor voltage of each module is realized. At the same time, the three‐phase input currents always remain in balance automatically operating under unity power factor. Simulations and experiments have verified the superiority of the topology structure and the feasibility of the control strategy.