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The purpose of this paper is to improve transient response and dynamic performance of automatic voltage regulator (AVR).

This paper proposes a novel fractional order proportional–integral–derivative plus derivative (PI^λD^µD^µ2) controller called FOPIDD for AVR system. The FOPIDD controller has seven optimization parameters and the equilibrium optimizer algorithm is used for tuning of controller parameters. The utilized objective function is widely preferred in AVR systems and consists of transient response characteristics.

In this study, results of AVR system controlled by FOPIDD is compared with results of proportional–integral–derivative (PID), proportional–integral–derivative acceleration, PID plus second order derivative and fractional order PID controllers. FOPIDD outperforms compared controllers in terms of transient response criteria such as settling time, rise time and overshoot. Then, the frequency domain analysis is performed for the AVR system with FOPIDD controller, and the results are found satisfactory. In addition, robustness test is realized for evaluating performance of FOPIDD controller in perturbed system parameters. In robustness test, FOPIDD controller shows superior control performance.

The FOPIDD controller is introduced for the first time to improve the control performance of the AVR system. The proposed FOPIDD controller has shown superior performance on AVR systems because of having seven optimization parameters and being fractional order based.

The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control.

For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system.

The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value.

Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

The purpose of this paper is to analyze the performance of LCLC resonant converter (RC) with proportional integral controller and fuzzy gain scheduled proportional integral controller.

The drawbacks of series RC and parallel resonant converter (PRC) are explained using relevant references in Section 1 of this paper. The necessity of RCs and the merits of zero voltage and zero current switching are given in the Section 2. In Section 3, the modeling of LCLC RC using state space technique is done. In Section 4, the open loop analysis and performance evaluation of proportional integral controller, fuzzy gain scheduled proportional controller using MATLAB Simulink is obtained. The hardware specification is given and experimental results are taken for LCLC RC. In Section 5, conclusion of study is given.

The LCLC RC overcomes the drawbacks of series and PRC. The fuzzy gain scheduled proportional integral controller is suitable for load variations in RC.

The output of the converter is not affected with the load variations since the controller suggested in the paper works for load changes and can be a solution for load parameter deviation applications. Also performance of the RC is improved by the fast response of the proposed controller.

In recent years, use of sensorless control methods for electrical motor-based variable speed drive systems has been increasing rapidly to compensate the increasing costs in industrial systems. Also, use of induction motors is popular for a long time to decrease the cost of these industrial systems. This study aims to design an effective controller to improve the sensorless speed control performance of induction motor. To achieve this, a conformable fractional order proportional integral (CFOPI) controller is designed.

The system is modeled based on small signal analysis by using the input–output data, experimentally. To do this, system identification toolbox of Matlab is used. The proposed controller is established on conformable fractional integral approach proposed by Khalil et al. (2014). CFOPI controller coefficients are optimized using particle swarm optimization method on the created small signal-based simulation model of the system to minimize the integral time absolute error. To prove the success of the proposed method, a traditional fractional order proportional integral (TFOPI) controller is tested under the same experimental system with the CFOPI controller.

TFOPI and CFOPI controllers are tested with the optimum parameters. Reference and actual speed trends are obtained for both methods. In induction motor start-up test, settling-times are measured as 8.73 and 8.44 s and steady-state oscillations are 2.66% and 0% (almost) for TFOPI and CFOPI controllers, respectively. In variable referenced speed tracking test, CFOPI performs well at all speed levels, while TFOPI fails to reach the reference speed at most speed levels.

Proposed CFOPI control method can be easily implemented in industrial systems, thanks to its simple algorithm. digital signal peripheral interface controller (dsPIC) based driver circuit with designed CFOPI controller used in this study can be applied directly to industrial systems such as elevators, conveyors, cranes and drills. Moreover, it can improve the performance of induction motor-based variable speed drive systems.

The proposed method provides robust performance for induction motor used in control systems. Additionally, it does this by using less complex algorithm written on the processors according to the traditional fractional order controllers.

The purpose of this paper is to propose a new framework based on linear control system theory and the use of proportional (P) controller and proportional integral (PI) controller to address identified stability issues and control the time properties in hybrid fire testing.

The paper approaches hybrid fire testing as a control problem. It establishes the state equation to give the general stability conditions. Then, it shows how P and PI controllers can be incorporated in the system to maintain stability. A virtual hybrid fire testing is performed on a 2D steel frame for validation and to compare the performance of the controllers.

Control system theory provides an efficient framework for hybrid fire testing and rigorously formulate the stability conditions of the system. The use of a P-controller stabilises the process, but this controller is not suitable for continuous change of stiffness of the substructures. In contrast, a PI-controller handle the stiffness changes. The results of a virtual hybrid fire testing of a 2D steel frame shows that the PI-controller succeeds in reproducing the global behaviour of the frame, even if the surrounding structure is non-linear and subjected to fire.

The paper provides a rigorous formulation of the general problem of hybrid fire testing and shows the interest of a PI controller to control the process under varying stiffness. This methodology is a step forward for hybrid fire testing because it allows capturing the global behaviour of a structure, including where the numerical substructure behaves nonlinearly and is subjected to fire.

This study aims to present a method for the conceptual design and simulation of an aircraft flight control system.

The design methodology is based on particle swarm optimization (PSO). PSO can be used to improve the performance of conventional controllers. The aim of the present study is threefold. First, it attempts to detect and isolate faults in an aircraft model. Second, it is to design a proportional (P) controller, a proportional derivative (PD) controller, a proportional-integral (PI) controller and a fuzzy controller for an aircraft model. Third, it is to design a PD controller for an aircraft using a PSO algorithm.

Conventional controllers, an intelligent controller and a PD controller-based PSO were investigated for flight control. It was seen that the P controller, the PI controller and the PD controller-based PSO caused overshoot. These overshoots were 18.5, 87.7 and 2.6 per cent, respectively. Overshoot was not seen using the PD controller or fuzzy controller. Steady state errors were almost zero for all controllers. The PD controller had the best settling time. The fuzzy controller was second best. The PD controller-based PSO was the third best, but the result was close to the others.

This study shows the implementation of the present algorithm for a specified space mission and also for study regarding variation of performance parameters. This study shows fault detection and isolation procedures and also controller gain choice for a flight control system. A comparison between conventional controllers and PD-based PSO controllers is presented. In this study, sensor fault detection and isolation are carried out, and, also, root locus, time domain analysis and Routh–Hurwitz methods are used to find the conventional controller gains which differ from other studies. A fuzzy controller is created by the trial and error method. Integral of squared time multiplied by squared error is used as a performance function type in PSO.

The purpose of this paper is to propose a novel self-adjusting proportional integral (SA-PI) controller, for controlling the active and reactive power of permanent magnet synchronous generator (PMSG) when subjected to variable wind speed and parameter variations.

The proportional and integral gains of the proposed SA-PI controller are based on tan-hyperbolic function and adjust themselves automatically within pre-fixed limits according to the error occurring during transient situations.

The proposed SA-PI controller is able to evade the problems usually encountered while using a constant gain PI controller, such as lack of robustness, adaptability and a wide range of operation. It also damps out system oscillations faster with reduced settling time and fewer overshoots.

Simulation results and comparative studies with conventional PI controller and the differential evolution–optimized PI (DE-PI) controller reveal the effectiveness of the proposed control scheme. MATLAB is used to perform the simulation studies.

This paper aims to design a modified fractional order proportional integral derivative (PID) (FO[PI]^λD^µ) controller based on the principle of fractional calculus and investigate its performance for a class of a second-order plant model under different operating conditions. The effectiveness of the proposed controller is compared with the classical controllers.

The fractional factor related to the integral term of the standard FO[PI]^λD^µ controller is applied as a common fractional factor term for the proportional plus integral coefficients in the proposed controller structure. The controller design is developed using the regular closed-loop system design specifications such as gain crossover frequency, phase margin, robustness to gain change and two more specifications, namely, noise reduction and disturbance elimination functions.

The study results of the designed controller using matrix laboratory software are analyzed and compared with an integer order PID and a classical FOPI^λD^µ controller, the proposed FO[PI]^λD^µ controller exhibit a high degree of performance in terms of settling time, fast response and no overshoot.

This paper proposes a methodology for the FO[PI]^λD^µ controller design for a second-order plant model using the closed-loop system design specifications. The effectiveness of the proposed control scheme is demonstrated under different operating conditions such as external load disturbances and input parameter change.

This paper aims to get the optimal controller parameters of fractional order proportional integral derivative (FOPID)/proportional integral derivative (PID) i.e. K_p, K_i, K_d, λ and µ for designing controller in automatic voltage regulator (AVR) system.

A novel method is proposed to get the optimal controller parameters for designing controller in AVR system using improved Jaya algorithm (IJA). The time domain objective and regular integral error objectives are used to design the controller to estimate the performance of the AVR system based on optimal tuning FOPID/PID controller.

The proposed method captures time domain objective of the FOPID/PID controller design and demonstrates effective transient response and better control action. The efficient tuning of FOPID controller results in high superiority of control efforts.

The simulations of IJA-based FOPID/PID controller design method are performed in MatLab tool and compared with several methods in the recent state of the art and the same are observed to be robust for the AVR system.

The developed optimal FOPID/PID controller tuning using IJA optimization method is totally a new approach for the AVR system in the literature.

The purpose of this paper is to develop, extend and propose an improved proportional integral derivative (PID) rate control of a quadrotor unmanned aerial vehicle based on a convexity-based surrogated firefly algorithm.

An improved PID controller structure is proposed for the rate dynamics of the quadrotor. Optimality of the controller is ensured by a recent, simple yet efficient firefly optimization method. The hybrid structure is further enhanced with a convexity-based surrogated model function.

Monte Carlo, transient response, error metrics and histogram distribution analyzes are conducted to show the performance of the proposed controller. The performance of the proposed method is evaluated under various convex combination values to further investigate the effect of the proposed surrogated model. According to the results, the proposed method is capable of controlling the rate quadrotor dynamics with the steady-state error of 0.0023 (rad/s) for P, −0.0024 (rad/s) for Q and 0 (rad/s) for the R state, respectively. Also, the least mean objective value is achieved at = 0 value of convexity in Monte Carlo trials.

The originality of this paper is to propose an improved PID rate controller with a convexity-based surrogated firefly algorithm.