Proposed Proportional-integral Controller Research Articles

Determination of Attacking Angle of Aircraft in Bio Inspired Optimized Technique

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 GA and 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) etc. 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.

Design brushless DC motor control by using proportional-integral strategy for a smart storage cabinet system

As well know, the use of high technology is more and more encouraged in many countries to decrease the costs, time, and human resources. This paper presents a speed control of brushless DC motor (BLDC), which was applied for the smart storage cabinets. BLDC motor is proposed due to its low costs, high torque, and high performance. The proportional-integral (PI) controller is constructed for the speed control of the movement of cabinet systems. First, the mathematical model and transfer function of the BLDC motor is rewritten to show the structure of the BLDC motor. Second, the proposed PI controller is designed based on the tuning Ziegler-Nichols method and the PI controller is also expressed by the discretized form for BLDC motor. Third, the working principle of BLDC motor is clearly represented and analyzed. Forth, the detail configuration of the experimental system is presented. The STM32 microcontroller unit (MCU) was used to execute. Finally, the experimental test was implemented to validate the power of the proposed controller in practical cases. The experimental results at no-load and load were shown that the power of proportional integral derivative (PID) controller is good at tracking the desired speed signals.

Design of optimal PI controller for torque ripple minimization of SVPWM-DTC of BLDC motor

Conventional direct torque control (CDTC) for brushless DC motor (BLDCM) using proportional integral (PI) controller suffers from torque ripple minimization and speed regulation issues. A novel method in fusion with space vector pulse width modulation (SVPWM) with DTC using optimal PI controller is developed to minimize these issues. In this method, SVPWM replaces switching table and hysteresis controllers in CDTC. To get better performance in steady state, conventional PI controllers are preferred in SVPWM-DTC for BLDCM. However, uncertainty arises due to PI controller tuning as well as load variations. In such a case, optimal PI controller tuned properly can minimize these uncertainties. Here, JAYA algorithm is used to tune controller gain parameters. Simulations of proposed PI controller of SVPWM-DTC for BLDCM are carried away in Simulink. To appreciate the performance of proposed optimal controller of SVPWM-DTC for BLDCM, the simulation results are compared with Conventional PI controller and particle swarm optimization (PSO) technique based tuned PI controller. This proposed technique reduces the toque ripple by 63.1% when compared to conventional PI and 58.5% when compared to PSO-PI controller. It also improves the settling time by 43.9% when compared to conventional PI and 46.79% when compared to PSO-PI controller.

Saturating PI Control of Stable Nonlinear Systems Using Singular Perturbations

This article presents an antiwindup propor- tional-integral (PI) controller, using a saturating integrator, for a single-input and single-output (SISO) stable nonlinear plant, whose steady-state input–output map is increasing. We prove that, under reasonable assumptions, there exists an upper bound on the controller gain such that for any constant reference input, the corresponding equilibrium point of the closed-loop system is exponentially stable, with a “large” region of attraction. When the state of the closed-loop system converges to this equilibrium point, then the tracking error tends to zero. The closed-loop stability analysis employs Lyapunov methods in the framework of the singular perturbations theory. Finally, we show that if the plant satisfies the asymptotic gain property, then the closed-loop system is globally asymptotically stable for any sufficiently small controller gain. The effectiveness of the proposed PI controller is proved by showing how it performs as part of the control algorithm of a synchronverter (a special type of dc to ac power converter).

An improved energy management strategy for fuel cell/battery/supercapacitor system using a novel hybrid jellyfish/particle swarm/BAT optimizers

In this paper, a fuel cell (FC) hybrid emergency system is presented. It contains fuel cells, batteries, and supercapacitors which are effective for different conveyance applications. Abbreviating the hydrogen consumption and incrementing the lifetime of power sources are the key factors of each energy management strategy (EMS). An incipient proposed EMS depending on an optimized proportional-integral (PI) controller is presented considering FC efficiency to ensure the operation of the FC stack within its maximum efficiency region and reduce the stress on it which in turn leads to reducing its hydrogen consumption. Regarding tunning the PI controller gains (Kp,Ki), a proposed hybrid metaheuristic optimization technique named JSPSOBAT has been presented which merges jellyfish (JS) optimizer, particle swarm optimizer (PSO) and BAT optimizer to achieve the balance between exploration and exploitation phases. To firstly validate the effectiveness of the JSPSOBAT technique, a comparative study with other single and hybrid metaheuristic optimization techniques is presented by testing on 50 complex benchmark functions. Then, the JSPSOBAT is used to select the controller gains of the proposed PI controller. A 30 min load profile of a More Electric Aircraft (MEA) is used. The performance of the proposed EMS using the proposed optimization technique is compared with other EMS such as state machine control strategy, classical PI control strategy, equivalent consumption minimization strategy, external energy maximization strategy, and the results show that the proposed technique produces the best performance.

Lean-burn air-fuel ratio control using genetic algorithm-based PI controller

Maximizing the fuel economy while lowering exhaust emissions highly depend on precise air-fuel ratio (AFR) control. The major challenge in the control of AFR is the time-varying delay, which is an inherent reason for performance degradation and instability. For analysis, the time delay is approximated by Padé approximation, leading to a non-minimum phase system that exhibits the difficulty of controlling due to its zeroes in the right half side of the s-plane. Moreover, dealing with uncertainties in fuel-path dynamics and minimizing the effect of external disturbances are key goals in the minimization of harmful emissions and maximization of fuel economy. This study puts forward an AFR control strategy in lean-burn spark-ignition (SI) engines by proposing a genetic algorithm (GA)-based proportional-integral (PI) control technique. The proposed PI controller aims at dealing with the aforementioned design challenges. The PI controller gains, namely, proportional (K_p), integral (K_i) gains are obtained with the proposed GA algorithm based on minimization of an objective function. The GA-based PI controller’s performance is analyzed with several methods in time-domain study. According to the obtained results, it has been revealed that the proposed GA-based PI controller improves the reference air-fuel ratio tracking performance in the existence of the time-varying delays in the closed-loop system, exhibiting good disturbance rejection properties, and is robust against system uncertainties. Thus, it can be effectively used for the accurate regulation of AFR under various operating conditions in SI engines.

Design and Control for Four-Variable Chaotic Nanoelectronic Circuits Based on DNA Reaction Networks

Control of chaotic nanoelectronic circuit is a typical nonlinear problem. In this paper, we present a four-variable chaotic oscillatory nanoelectronic circuit by the cascade of multiplication, adjustment and elimination DNA chemical reaction modules. Furthermore, a proportional integral (PI) controller of four-variable nonlinear chaotic nanoelectronic circuit is realized based on catalysis and annihilation DNA chemical reaction modules. These DNA modules are realized by a series of DNA strand displacement (DSD) reactions and simulated by Visual DSD. Oscillatory time domain waveforms of four-variable chaotic oscillatory nanoelectronic circuit could be generated by the designed chaotic oscillatory chemical reaction modules. The proposed PI controller could be added for chaotic nanoelectronic circuits to stabilize oscillatory signals and it has robustness to the initial value changes of chaotic nanoelectronic circuit.

PI Control Loop–Based Frequency Smoothing of a Doubly-Fed Induction Generator

This paper proposes a frequency-smoothing scheme of a doubly-fed induction generator (DFIG) that can significantly eliminate the frequency fluctuations caused by continuously fluctuating wind speeds. To achieve this, a proportional-integral (PI) control loop depending on the frequency deviation instead of a proportional control loop used in conventional schemes is added to the maximum power point tracking loop. The P control loop in the proposed frequency-smoothing scheme eliminates the alternating component in the frequency deviation, whereas the I control loop eliminates the slowly-varying component. The gains for the P control loop and I control loop are suggested for effectively using the rotating masses of a DFIG while avoiding over-deceleration of the rotor speed. The simulation results evidently demonstrate that the proposed scheme nearly removes the frequency deviation under various wind conditions, by using the proposed PI control loop, especially in high penetration levels of wind.

Performance evaluation of PI controller for positive output Luo converter

The aim of this work is to design and analyze a Proportional Integral (PI) controller for Positive Output Luo Converter applications. Positive Output Luo Converter is a developed DC-DC converter. It is respected as a right choice for most industrial application where the rate of the output load voltage must be varying between the low and high values of the input value of voltage, output voltage rise and fall is smaller. This converter involve Power electronics switches (Diodes and MOSFET) since these elements are non-linear. The detailed model includes high-frequency switching that is introducing discontinuities into the model. PI controller coefficients (kp, ki) are calculated by particle swarm optimization (PSO) to provide optimal PI as hybrid PI by PSO controller with simple design procedure .Transient and steady state responses requirement of the system are considered in designing the proposed PI controller. The consequences show that the time of performing characteristics of PSO-PI controller established on integral squared error (ISE) performance index has the best time performing characteristics, line disturbance, load disturbance and set point variation.

Temperature Control for a Proton-Exchange Membrane Fuel Cell System with Unknown Dynamic Compensations

Numerous control strategies of temperature regulation have been carried out for proton-exchange membrane fuel cell systems including a cooling fan in order to ensure operation at the desired condition and extend the lifetime of the fuel cell stack. However, most existing control strategies are developed without considering the efficiency limitation of the cooling system such that the cooling fan may be unable to eliminate the additional heat. Moreover, there are unknown modelling errors, external disturbance and noise during modelling and experiment processes for fuel cells. Due to those unknown dynamics, the conventional control strategies may fail to achieve the expectant results. To address this issue, an alternative control strategy is proposed in this paper, which consists of a composite proportional-integral (PI) controller with an unknown system dynamics estimator. First, the control strategy is developed by reducing the temperature of input air through the humidifier and simultaneously increasing the mass flow of air in order to eliminate the excess heat that a cooling fan cannot remove. Moreover, an unknown system dynamics estimator is proposed in order to compensate the effect of the unknown dynamics. The construction of the estimator is designed through finding an invariant manifold which implies the relation between known variables and the unknown manifold. The invariant manifold is derived by applying a simple low-pass filter to the system which is beneficial to avoid the requirement of the unmeasurable state derivative. Furthermore, the proposed estimator is easily merged into the proposed PI control strategy and ensures the exponential convergence of estimated errors. Besides, the estimator is further modified such that the derivative of the desired temperature is not required in the controller. Finally, numerical simulations of the PEMFC system are provided and the results illustrate the efficacy of the proposed control strategy.

Optimal design of an Autonomous Emergency Braking (AEB) system for a passenger vehicle

This paper models the performance of a passenger vehicle equipped with Autonomous Emergency Braking (AEB) using a feedback control system in MATLAB Simulink. Two types of AEB control systems are simulated and compared; proportional-integral (PI) control and fuzzy logic control (FLC). Performance of both control systems simulated are compared using AEB City collision scenario defined in Euro New Car Assessment Protocol (NCAP). Results show that the proposed PI control system is able to meet Euro NCAP AEB City set requirements.

Voltage tracking of bridgeless PFC cuk converter using PI controller

This paper proposes a Proportional-Integral (PI) control voltage tracking of Bridgeless Power Factor Correction (BPFC) Cuk converter. In order to investigate the behaviour of different output voltages during overshoot, steady state and step response, P.I controller is designed to set the -42 V, -48 V, -54 V output voltages. The simulation results show that the proposed PI controller able to control the output voltage and achieve fast steady state and step response of BPFC Cuk converter. When the value of output voltage increase, the overshoot voltage will become higher but the steady state respond will be faster. Furthermore, BPFC Cuk converter with P.I controller have low output voltage ripples.

Multivariable sliding‐mode extremum seeking PI tuning for current control of a PMSM

High-performance current control is critical for obtaining smooth output torque in permanent-magnet synchronous motors (PMSMs). To this end, a new proportional–integral (PI) tuning method based on multivariable sliding-mode extremum seeking is proposed in this study and applied for current control of a PMSM. In the proposed method, a sliding-mode extremum seeking optimiser varies the PI gains by minimising a cost function based on the feedback error term. The resulting PI controller can achieve fast and accurate tracking response, high disturbance rejection, and low sensitivity to PMSM parameter variations. The stability of the proposed control strategy is investigated through a Lyapunov analysis and its performance is evaluated through experimental studies. The results indicate that the proposed controller can offer improved performance in terms of accuracy, parametric variations, and load torque disturbances when compared with a conventional PI and a recently proposed PI controller using the gradient-based extremum seeking tuning method.

PV Based Grid System for Power Quality Enhancement using Instantaneous P-Q Theory

The SPV interfaced grid system with battery storage unit, bidirectional VSI interconnected shunt active filter, an adaptive Proportional Integral (PI) controller is employed for improve current and voltage profile enhancement. The p-q theory is the common employed technique to extract the basic fundamental current harmonic components from affected or polluted power supply by means of diode rectifier or non linear load. The basic concepts of reactive power (IRP) theory includes it’s a time domain model and it can be applicable for both 3P3W and 3P4W. Initially, the control technique called instantaneous real and reactive power theory or p-q theory has been developed for three phase three wire system and then later it was extend to three phase four wire system. This system is valid under steady state as well as dynamic state. The bidirectional VSI based shunt APF is controlled by the PI based instantaneous reactive power theory. The proposed PI Controller interfaced shunt Active Power Filter is used to maintain DC-Link voltage.SPV system is interfaced with incremental conductance MPPT algorithm. This SAPF control scheme has to provide the following benefits like current harmonic mitigation as well as reactive power compensation

Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm

Voltage and frequency regulation is one of the greatest challenges for proper operation subsequent to the isolated microgrid. To validate the satisfactory electric power quality supply to customers, the proposed manuscript tries to enhance the quality of energy provided by DG (Distributed generation) units connected to the subsequent isolated grid. Microgrid and simulation-based control structure including voltage and current control feedback loops is proposed for microgrid inverters to recover voltage and frequency of the system subsequently for any fluctuations in load change. The proportional-integral (PI) controller connected to the voltage controller is an end goal to obtain smooth response in most of the consistent frameworks. The present controller creates the space vector pulse width modulation signals which are given to the three-leg inverter. The objective elements of the multiobjective optimization issue are voltage overshoot and undershoot, rise time, settling time, and integral time absolute error (ITAE). The hybrid Multiobjective Symbiotic Organism Search (MOSOS) calculation is associated for self-tuning of control parameters keeping in mind the end goal to deal with the voltage and frequency. The proposed PI controller, along with the hybrid Multiobjective Symbiotic Organism Search algorithm, provides the solution for the greatest challenge of voltage and frequency regulation in an isolated-microgrid operation.

Optimal Design of Proportional–Integral Controllers for Grid-Connected Solid Oxide Fuel Cell Power Plant Employing Differential Evolution Algorithm

This paper proposes the application of differential evolution (DE) algorithm for the optimal tuning of proportional–integral controller designed to improve the small signal dynamic response of a grid-connected solid oxide fuel cell (SOFC) system. The small signal model of the study system is derived and considered for the controller design as the target here is to track small variations in SOFC load current. The proposed proportional–integral (PI) controllers are incorporated in the feedback loops of hydrogen and oxygen partial pressures, grid current d–q components and dc voltage with an aim to improve the small signal dynamic responses. The controller design problem is formulated as the minimization of an eigenvalue-based objective function where the target is to find out the optimal gains of the PI controllers in such a way that the discrepancy between the obtained and desired eigenvalues is minimized. Eigenvalue and time domain simulations are presented for both open-loop and closed-loop systems. To test the efficacy of DE over other optimization tools, the results obtained with DE are compared with those obtained by particle swarm optimization (PSO) algorithm and invasive weed optimization (IWO) algorithm. Three different types of load disturbances are considered for the time domain-based results to investigate the performances of different optimizers under different sorts of load variations. Moreover, nonparametric statistical analyses, namely one-sample Kolmogorov–Smirnov (KS) test and paired sample t test, are used to identify the statistical advantage of DE algorithm over the other two. The presented results suggest the supremacy of DE over PSO and IWO in finding the optimal solution.

Parameter Tuning of PI Control for Speed Regulation of a PMSM Using Bio-Inspired Algorithms

This article focuses on the optimal gain selection for Proportional Integral (PI) controllers comprising a speed control scheme for the Permanent Magnet Synchronous Motor (PMSM). The gains calculation is performed by means of different algorithms inspired by nature, which allows improvement of the system performance in speed regulation tasks. For the tuning of the control parameters, five optimization algorithms are chosen: Bat Algorithm (BA), Biogeography-Based Optimization (BBO), Cuckoo Search Algorithm (CSA), Flower Pollination Algorithm (FPA) and Sine-Cosine Algorithm (SCA). Finally, for purposes of efficiency assessment, two reference speed profiles are introduced, where an acceptable PMSM performance is attained by using the proposed PI controllers tuned by nature inspired algorithms.

Experimental Validation of a Novel PI Speed Controller for AC Motor Drives With Improved Transient Performances

A proportional–integral (PI) controller is the most frequently used control technique for adjustable speed-motor drives. The main advantage of a PI controller is its ability to ensure zero steady-state error under low-frequency disturbances and model uncertainties as long as the closed-loop system is stable. However, the transient performances, under a PI regulator, are highly dependent on the machine parameters, the external disturbances, and the input constraints. This brief proposes the design process of a novel PI speed controller that is capable of preserving almost the nominal transient performance under the parameter variation and external disturbances such as the load torque. The controller also suppresses the effect of input saturation that may occur because of the armature current limitation. Simulation and experimental tests are carried out to verify the validity of the proposed design process. The results revealed that the proposed PI controller is effective regarding nominal performance recovery and input constraints handling.

Design and Implementation of a Discrete-Time Proportional Integral (PI) Controller for the Temperature Control of a Heating Pad.

Contact heat evoked potentials (CHEPs) are recorded from the brain by giving thermal stimulations through heating pads kept on the surface of the skin. CHEP signals have crucial diagnostic implications in human pain activation studies. This work proposes a novel design of a digital proportional integral (PI) controller based on Arduino microcontroller with a view to explore the suitability of an electric heating pad for use as a thermode in a custom-made, cost-effective CHEP stimulator. The purpose of PI controller is to set, regulate, and deliver desired temperatures on the surface of the heating pad in a user-defined pattern. The transfer function of the heating system has been deduced using the parametric system identification method, and the design parameters of the controller have been identified using the root locus technique. The efficiency of the proposed PI controller in circumventing the well-known integrator windup problem (error in the integral term builds excessively, leading to large transients in the controller output) in tracking the reference input and the controller effort (CE) in rejecting output disturbances to maintain the set temperature of the heating pad have been found to be superior compared with the conventional PI controller and two of the existing anti-windup models.

High-Efficiency mosfet-Based MMC Design for LVDC Distribution Systems

Low-voltage dc (LVdc) distribution networks have the potential to release larger capacity without having to upgrade the existing cables. One of the main challenges of LVdc networks is the extra customer-end dc–ac conversion stage. This paper proposes and evaluates a five-level Si mosfet -based modular multilevel converter (MMC) as a promising alternative to the conventional two-level insulated gate bipolar transistor-based converter. This is due to the comparatively higher efficiency, power quality and reliability, and reduced electromagnetic (EM) emissions. A comprehensive analysis of a Si mosfet five-level MMC converter design is performed to investigate the suitability of the topology for LVdc applications. Detailed theoretical analysis of the five-level MMC is presented, with simulated and experimental results to demonstrate circuit performance. To suppress the ac circulating current, especially the dominant second harmonics, this paper presents a double line-frequency proportional integral (PI) with orthogonal imaginary axis control method. Comparison of simulation and experimental results with those for double line-frequency proportional resonant control shows that the proposed PI controller has a better performance. In addition, it is simpler to implement and more immune to sampling/discretization errors.