Showing papers on "PID controller published in 2018"
TL;DR: Rigorous analysis is provided to demonstrate that the fast terminal SMC law can offer a higher accuracy than the traditional linear SMClaw and show the advantages of the present discrete-time fast terminalSMC approach over some existing approaches, such as discrete- time linear sliding mode control approach and the PID control method.
Abstract: The main objective of this paper is to solve the position tracking control problem for the permanent magnet linear motor by using the discrete-time fast terminal sliding mode control (SMC) method. Specifically, based on Euler's discretization technique, the approximate discrete-time model is first obtained and analyzed. Then, by introducing a new type of discrete-time fast terminal sliding surface, an improved discrete-time fast SMC method is developed and an equivalent-control-based fast terminal SMC law is subsequently designed. Rigorous analysis is provided to demonstrate that the fast terminal SMC law can offer a higher accuracy than the traditional linear SMC law. Numerical simulations and experimental results are finally performed to demonstrate the effectiveness of the proposed approach and show the advantages of the present discrete-time fast terminal SMC approach over some existing approaches, such as discrete-time linear sliding mode control approach and the PID control method.
201 citations
TL;DR: It is validated that the proposed proposed robust virtual inertia controller successfully provides desired robust frequency support to a low-inertia islanded microgrid against high RESs penetration.
Abstract: This paper presents robust virtual inertia control of an islanded microgrid considering high penetration of renewable energy sources (RESs). In such microgrids, the lack of system inertia due to the replacement of traditional generating units with a large amount of RESs causes undesirable influence to microgrid frequency stability, leading to weakening of the microgrid. In order to handle this challenge, the $H_{\mathbf {\infty }}$ robust control method is implemented to the virtual inertial control loop, taking into account the high penetration of RESs, thus enhancing the robust performance and stability of the microgrid during contingencies. The controller’s robustness and performance are determined along with numerous disturbances and parametric uncertainties. The comparative study between $H_{\mathbf {\infty }}$ and optimal proportional-integral (PI)-based virtual inertia controller is also presented. The results show the superior robustness and control effect of the proposed $H_{\mathbf {\infty }}$ controller in terms of precise reference frequency tracking and disturbance attenuation over the optimal PI controller. It is validated that the proposed $H_{\mathbf {\infty }}$ -based virtual inertia controller successfully provides desired robust frequency support to a low-inertia islanded microgrid against high RESs penetration.
179 citations
TL;DR: In this paper, the authors presented a power system model, which includes both conventional generating units and renewable energy sources (RES) for studying the AGC problem of such systems, and the control strategy was based on the proportional-integral-derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA).
Abstract: Till this moment, the model of interconnected power systems in the automatic generation control (AGC) loops relies only on the synchronous generating units. In today's world, a high level of penetration of renewable energy sources (RES) is integrated to the power grids. This paper presents a novel power system model, which includes both conventional generating units and RES for studying the AGC problem of such systems. The control strategy in the AGC loops is based on the proportional-integral-derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA). It represents a great challenge to this controller to deal with the RES uncertainties. The effectiveness of the WOA-based PID controller is compared with other computation evolutionary algorithms-based PID controller. The system performance is evaluated under different operating conditions. For achieving a realistic study, 1) real wind speed data that extracted from Zafarana location in Egypt are used, 2) solar irradiation and temperature data that extracted from a field test are implemented, and 3) an irregular wave energy condition is applied. The validity of the control strategy is verified using the simulation results, which are carried out using MATLAB environment.
171 citations
TL;DR: Simulation results show that the proposed FA-based controllers present better performance over GA in terms of settling times and different indices.
Abstract: In this paper, firefly algorithm (FA) for optimal tuning of PI controllers for load frequency control of hybrid system composing of photovoltaic (PV) system and thermal generator is introduced. Also, maximum power point tracking of PV is considered in the design process. The block diagram of the hybrid system is performed. To robustly tune the parameters of controllers, a time-domain-based objective function is established which is solved by the FA. Simulation results are presented to show the improved performance of the suggested FA-based controllers compared with genetic algorithm (GA). These results show that the proposed controllers present better performance over GA in terms of settling times and different indices.
163 citations
Proceedings Article•
01 Jan 2018TL;DR: Adopting a data-driven, model-based approach, it is demonstrated that an RL agent with little prior knowledge is able to effectively and safely regulate conditions on a server floor after just a few hours of exploration, while improving operational efficiency relative to existing PID controllers.
Abstract: Despite impressive recent advances in reinforcement learning (RL), its deployment in real-world physical systems is often complicated by unexpected events, limited data, and the potential for expensive failures In this paper, we describe an application of RL “in the wild” to the task of regulating temperatures and airflow inside a large-scale data center (DC) Adopting a data-driven, model-based approach, we demonstrate that an RL agent with little prior knowledge is able to effectively and safely regulate conditions on a server floor after just a few hours of exploration, while improving operational efficiency relative to existing PID controllers
160 citations
TL;DR: The stability and the convergence of the whole system are proved based on the Lyapunov stability theory and simulation experiments are followed through on a four-area interconnected power system to demonstrate the effectiveness of the proposed control scheme.
Abstract: This paper concentrates on the problem of control of a hybrid energy storage system (HESS) for an improved and optimized operation of load-frequency control applications. The HESS consists of a supercapacitor serving as the main power source and a fuel cell serving as the auxiliary power source. First, a Hammerstein-type neural network is proposed to identify the HESS, which formulates the Hammerstein model with a nonlinear static gain in cascade with a linear dynamic block. It provides the model information for the controller to achieve the adaptive performance. Second, a feedforward neural network based on a back-propagation training algorithm is designed to formulate the proportional-integral-derivative (PID)-type neural network, which is used for the adaptive control of the HESS. Meanwhile, a dynamic antiwindup signal is designed to solve the operational constraint of the HESS. Then, an appropriate power reference signal for the HESS can be generated. Third, the stability and the convergence of the whole system are proved based on the Lyapunov stability theory. Finally, simulation experiments are followed through on a four-area interconnected power system to demonstrate the effectiveness of the proposed control scheme.
136 citations
TL;DR: This paper proposes an algebraic substitution method and its structure, which can convert a noncascaded integral system of PID control into a cascaded integral form, and shows that the converted system can achieve a better control effect under the ADRC than that of a PID.
Abstract: The Active Disturbance Rejection Control (ADRC) prefers the cascaded integral system for a convenient design or better control effect and takes it as a typical form. However, the state variables of practical system do not necessarily have a cascaded integral relationship. Therefore, this paper proposes an algebraic substitution method and its structure, which can convert a noncascaded integral system of PID control into a cascaded integral form. The adjusting parameters of the ADRC controller are also demonstrated. Meanwhile, a numerical example and the oscillation control of a flexible arm are demonstrated to show the conversion, controller design, and control effect. The converted system is proved to be more suitable for a direct ADRC control. In addition, for the numerical example, its control effect for the converted system is compared with a PID controller under different disturbances. The result shows that the converted system can achieve a better control effect under the ADRC than that of a PID. The theory is a guide before practice. This converting method not only solves the ADRC control problem of some noncascaded integral systems in theory and simulation but also expands the application scope of the ADRC method.
133 citations
TL;DR: A maiden attempt is made to propose a fuzzy aided integer order proportional integral derivative with filter-fractional order integral (FPIDN-FOI) controller for AGC of multi-area power systems that is robust and executes adequately under variations in system parameters, random load disturbance patterns and nonlinearities.
Abstract: Automatic generation control (AGC) executes a vital role to supply quality power in an interconnected power system. To cultivate good quality of power supply via preserving area frequency and tie-line power oscillations following consumer's load demand disturbances, the controller designed for AGC of power system should display excellent disturbance rejection expertise. Hence, in this paper, a maiden attempt is made to propose a fuzzy aided integer order proportional integral derivative with filter-fractional order integral (FPIDN-FOI) controller for AGC of multi-area power systems. A more recent intelligent optimization technique termed as imperialist competitive algorithm (ICA) is fruitfully employed for concurrent tuning of various parameters of the proposed controller. It is observed from the simulation results that the proposed FPIDN-FOI controller outperforms the various existing control strategies and PID/PIDN/FPIDN controller designed in the study for five different power system models. Effect of variation in fractional order value of integral on the system performance is analyzed. A sensitivity analysis is conducted to test the robustness of the designed controller under variations in the system parameters, load demands and existence of the system nonlinearities. It is perceived that the proposed controller is robust and executes adequately under variations in system parameters, random load disturbance patterns and nonlinearities.
128 citations
TL;DR: A technique to discretize fractional differential equations with variable-order operators with resulting model and a particle swarm optimization algorithm are used to search for the optimal parameters of the VFPID controllers.
123 citations
TL;DR: Time domain simulation of transient responses indicates that the designed HSCOA based fuzzy PID controller operates satisfactorily to deal with the GDB nonlinearity and outperform other published techniques.
118 citations
TL;DR: A novel model to control the frequency of the wind farm connected to conventional units is presented and the defined frequency control parameters are optimized based on a multiobjective function using particle swarm optimization algorithm.
Abstract: In a high penetrated wind farm power system, wind farms can collaborate to control the power system frequency as like as conventional units. This paper presents a novel model to control the frequency of the wind farm connected to conventional units. Throughout the proposed frequency control, the integral controller, washout filter, and the PID controller could determine the active power variation value in different situations. In fact, a PID controller makes the wind farm aware of power variations. To improve the efficiency of the model, the defined frequency control parameters (i.e., PID coefficients) are optimized based on a multiobjective function using particle swarm optimization algorithm. This study has a unique perspective based on the wind farm collaboration through inertia control, primary frequency control, and supplementary frequency control of the system. A swift power reserve in a stable condition is needed in which wind farm can ameliorate the system frequency response. It is worth saying that the wind farm consists of variable speed turbines, such as a doubly fed induction generator, or a permanent magnet synchronous generator. To assess the performance of the proposed model, it is applied to a typical two-area system and the results are compared.
TL;DR: Simulation results show that a better control performance is achieved with the proposed new sliding-mode controller than the traditional control method when actuator or control input saturation exists in the autonomous 4WMV parking system.
Abstract: In this paper, a new model-free adaptive integral sliding-mode-constrained control scheme is presented for autonomous four-wheeled mobile vehicle (4WMV) parking systems. The proposed control strategy includes: 1) online identification for the object model based on a data-driven technique is presented for 4WMV and 2) an integral sliding-mode controller with control input constraints and stability analysis is provided. For online data-driven model identification, a compact-form dynamic linearization-based observer formulation is constructed for 4WMV. For integral sliding-mode controller design, a dynamic antiwindup compensator is introduced to solve integral saturation and actuator saturation problems in the autonomous 4WMV parking system. The designed control scheme only utilizes the body angle and steering angle of the vehicle under the condition that the precise mechanism model of the autonomous 4WMV parking system is not available to us. Finally, simulation comparisons between the model-free adaptive integral sliding-mode-constrained control scheme, PID control, and model-free adaptive control algorithms with coordinate compensation are given for two different vehicles. The simulation results show that a better control performance is achieved with the proposed new sliding-mode controller than the traditional control method when actuator or control input saturation exists in the autonomous 4WMV parking system.
TL;DR: An optimal control strategy is introduced with the purpose of enhancing the performance of PV systems based on the proportional-integral (PI) controller, which is designed by using the whale optimization algorithm (WOA).
TL;DR: This paper develops an enhanced robust fault tolerant control using a novel adaptive fuzzy proportional-integral-derivative-based nonsingular fast terminal sliding mode (AF-PID-NFTSM) control for a class of second-order uncertain nonlinear systems.
Abstract: This paper develops an enhanced robust fault tolerant control using a novel adaptive fuzzy proportional-integral-derivative-based nonsingular fast terminal sliding mode (AF-PID-NFTSM) control for a class of second-order uncertain nonlinear systems. In this approach, a new type of sliding surface, called proportional-integral-derivative (PID)-nonsingular fast terminal sliding mode (NFTSM) (PID-NFTSM) which combines the benefits of the PID and NFTSM sliding surfaces, is proposed to enhance the robustness and reduce the steady-state error, whilst preserving the great property of the conventional NFTSM controller. A fuzzy approximator is designed to approximate the uncertain system dynamics and an adaptive law is developed to estimate the bound of the approximation error so that the proposed robust controller does not require a need of the prior knowledge of the bound of the uncertainties and faults and the exact system dynamics. The proposed approach is then applied for attitude control of a spacecraft. The simulation results verify the superior performance of the proposed approaches over other existing advanced robust fault tolerant controllers.
TL;DR: Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation on MATLAB/Simulink and on real-time laboratory platform.
Abstract: This letter presents a novel model predictive control strategy without involving any proportional-integral-differential regulators for practical renewable energy based ac microgrids. The proposed method consists of a model predictive power control (MPPC) scheme and a model predictive voltage control (MPVC) scheme. By controlling the bidirectional buck-boost converters of the battery energy storage systems based on the MPPC algorithm, the fluctuating output from the renewable energy sources can be smoothed, while stable dc-bus voltages can be maintained as the inverters' inputs. Then, the parallel inverters are controlled by using a combination of the MPVC scheme and the droop method to ensure stable ac voltage output and proper power sharing. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation on MATLAB/Simulink and on real-time laboratory platform.
TL;DR: Extensive simulation results demonstrate that the CS based PID controller has better control performance in comparison with other PID controllers tuned by the PSO and ABC algorithms, and remarkably improves the PID tuning optimization technique.
Abstract: This article presents a novel tuning design of Proportional-Integral-Derivative (PID) controller in the Automatic Voltage Regulator (AVR) system by using Cuckoo Search (CS) algorithm with a new time domain performance criterion. This performance criterion was chosen to minimize the maximum overshoot, rise time, settling time and steady state error of the terminal voltage. In order to compare CS with other evolutionary algorithms, the proposed objective function was used in Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms for PID design of the AVR system. The performance of the proposed CS based PID controller was compared to the PID controllers tuned by the different evolutionary algorithms using various objective functions proposed in the literature. Dynamic response and a frequency response of the proposed CS based PID controller were examined in detail. Moreover, the disturbance rejection and robustness performance of the tuned controller against parametric uncertainties were obtained, separately. Energy consumptions of the proposed PID controller and the PID controllers tuned by the PSO and ABC algorithms were analyzed thoroughly. Extensive simulation results demonstrate that the CS based PID controller has better control performance in comparison with other PID controllers tuned by the PSO and ABC algorithms. Furthermore, the proposed objective function remarkably improves the PID tuning optimization technique.
TL;DR: This proposed hierarchical control system is tested in a hardware-in-the-loop system with four typical maneuvers, which are constant velocity, accelerating, decelerating, and low road adhesion coefficient situations to show different driver command.
Abstract: For four wheel independent motor-drive electric vehicle, the vehicle longitudinal and lateral motion can be controlled by distributing the driving and regenerative braking torques of four wheel motors. To meet the driving command of driver and keep the vehicle lateral stability, a hierarchical control system is proposed in this paper. In the upper layer, a nonlinear model predictive control is implemented to solve the nonlinear multiinput multioutput, over-actuated problem. The controller is based on a nonlinear three degree-of-freedom model with nonlinear tire model, considering wheel slips as virtual control input. In the lower layer, the wheel slips are manipulated by a PID controller for generating driving and regenerative braking torques of the independent motors. This proposed controller is tested in a hardware-in-the-loop system with four typical maneuvers, which are constant velocity, accelerating, decelerating, and low road adhesion coefficient situations to show different driver command. The results show that the driver command of longitudinal and lateral motion control are both satisfied.
TL;DR: The present paper attempts to address issues by reviewing recent literature in the field and by providing relevant analysis and recommendations on the benefit of using FOPID controllers.
TL;DR: A new control method to suppress current harmonics for permanent magnet synchronous linear motor (PMSLM) that is applied in the miniature microsecond laser cutting system and can reduce the overshoot and thrust ripple as well is presented.
Abstract: This paper presents a new control method to suppress current harmonics for permanent magnet synchronous linear motor (PMSLM) that is applied in the miniature microsecond laser cutting system. In the control method, the resonant–two-degree-of-freedom (R–2DOF) proportional–integral–derivative (PID) controller is proposed by combining a resonant controller and a two-degree-of-freedom (2DOF) PID controller. The current harmonic components are first analyzed. The resonant controller is subsequently added to the current loop in parallel to the traditional PI controller to suppress the current harmonic components. However, with the current harmonics suppression, the resonant controller can result in the overshoot in the current loop response. The 2DOF PID controller is adopted to reduce the overshoot. Thus, an R–2DOF PID controller is developed by combining the resonant controller and 2DOF PID controller. Meanwhile, the stability of the proposed controller is analyzed. Compared with the traditional PID controller and the Kalman filter, the proposed controller not only can suppress the current harmonics but can reduce the overshoot and thrust ripple as well. Finally, the simulation and experimental comparison results confirm the validity of the proposed control algorithm.
TL;DR: An output scaling factor (SF) based fuzzy classical controller to enrich AGC conduct of two-area electrical power systems and the superiority of the method is depicted by contrasting the results of GA/FA tuned PI controller.
Abstract: The interconnected large-scale power systems are liable to performance degradation under the presence of sudden small load demands, parameter ambiguity and structural changes. Due to this, to supply reliable electric power with good quality, robust and intelligent control strategies are extremely requisite in automatic generation control (AGC) of power systems. Hence, this paper presents an output scaling factor (SF) based fuzzy classical controller to enrich AGC conduct of two-area electrical power systems. An implementation of imperialist competitive algorithm (ICA) is made to optimize the output SF of fuzzy proportional integral (FPI) controller employing integral of squared error criterion. Initially the study is conducted on a well accepted two-area non-reheat thermal system with and without considering the appropriate generation rate constraint (GRC). The advantage of the proposed controller is illustrated by comparing the results with fuzzy controller and bacterial foraging optimization algorithm (BFOA)/genetic algorithm (GA)/particle swarm optimization (PSO)/hybrid BFOA-PSO algorithm/firefly algorithm (FA)/hybrid FA-pattern search (hFA-PS) optimized PI/PID controller prevalent in the literature. The proposed approach is further extended to a newly emerged two-area reheat thermal-PV system. The superiority of the method is depicted by contrasting the results of GA/FA tuned PI controller. The proposed control approach is also implemented on a multi-unit multi-source hydrothermal power system and its advantage is established by Correlating its results with GA/hFA-PS tuned PI, hFA-PS/grey wolf optimization (GWO) tuned PID and BFOA tuned FPI controllers. Finally, a sensitivity analysis is performed to demonstrate the robustness of the proposed method to broad changes in the system parameters and size and/or location of step load perturbation.
TL;DR: Experimental results are conducted in a wind tunnel to show the successful design and implementation of the gain scheduled control system for the fixed-wing UAV and the significant performance improvement over a linear control system without controller adaptation.
Abstract: Fixed-wing unmanned aerial vehicles (UAVs) have become increasingly important in military, civil, and scientific sectors. Because of the existing nonlinearities, effective control this type of UAV remains a challenge. This paper proposes a gain scheduled proportional-integral derivative (PID) control system for fixed-wing UAVs where a family of PID cascade control systems is designed for several operating conditions of airspeed. This is done using an automatic tuning algorithm, where the controllers are automatically selected by deploying an airspeed sensor positioned ahead of the aircraft. Furthermore, the actual gain scheduling is carried out by forming an interpolation between the family members of the linear closed-loop system, which ensures a smooth transition from one operating point to another. Experimental results are conducted in a wind tunnel to show the successful design and implementation of the gain scheduled control system for the fixed-wing UAV and the significant performance improvement over a linear control system without controller adaptation.
TL;DR: This paper addresses the problem of stabilization of port-Hamiltonian systems via the ubiquitous proportional-integral-derivative (PID) controller with a design based on passivity theory, and proves that this class of systems is strictly larger than the ones previously reported in the literature.
Abstract: In this note, we address the problem of stabilization of port-Hamiltonian systems via the ubiquitous proportional-integral-derivative (PID) controller. The design is based on passivity theory, hence the first step is to identify all passive outputs of the system, which is the first contribution of the paper. Adding a PID around this signal ensures that the closed-loop system is ${\mathcal L}_2$ -stable for all positive PID gains. Global stability (and/or global attractivity) of a desired constant equilibrium is also guaranteed for a new class of systems for which a Lyapunov function can be constructed. A second contribution is to prove that this class—that is identified via some easily verifiable integrability conditions—is strictly larger than the ones previously reported in the literature. Comparisons of the proposed PID controller with control-by-interconnection passivity-based control are also discussed.
TL;DR: It was demonstrated from the experimental work that the proposed IGA based PID controller improves the trajectory accuracy of the horizontal line and slope line trajectories by 23.98% and 23.64%, respectively in comparison to the SGA tuned PID controller.
TL;DR: The cascaded integration of Incremental Nonlinear Dynamic Inversion (INDI) for attitude control and INDI for position control of micro air vehicles and the effect of using a linearization to calculate thrust vector increments is investigated.
TL;DR: It is observed from different performance analysis that proposed I-SSO tuned type-II fuzzy controller exhibits superior performances for load frequency control in multi-area islanded AC microgrid system under different uncertainty conditions.
TL;DR: A novel proportional-integral-derivative (PID)-type motion controller for a quadrotor is introduced, and better tracking accuracy is obtained with the introduced nonlinear PID-type algorithm.
Abstract: A novel proportional-integral-derivative (PID)-type motion controller for a quadrotor is introduced in this paper A rigorous analysis of the closed-loop system trajectories is provided, and gain tuning guidelines are discussed Real-time experimental results consisting of the implementation of a PID-based scheme, a sliding-mode controller, and the new scheme are given Gains are selected so that the three tested controllers present the same energy consumption In order to assess the robustness of the controllers tested, experiments are carried out in the presence of disturbances in one of the actuators Specifically, the disturbance consists in attenuating the force delivered Better tracking accuracy is obtained with the introduced nonlinear PID-type algorithm
TL;DR: A model-free based neural network control with time-delay estimation (TDE-MFNNC) for lower extremity exoskeleton is presented and validated as more stable and effective than the traditional controllers.
TL;DR: In this paper, a predictive speed controller (PSC) based on finite control set model predictive control is developed for electric drives and a linear controller is incorporated in the control law of developed PSC offering improved system behavior.
Abstract: In this paper, a predictive speed controller (PSC) based on finite control set model predictive control is developed for electric drives. The large difference between the mechanical and electrical time constants necessitates long prediction horizons for a direct PSC (DPSC) strategy to be implemented. Therefore, the computation burden for online solving of the optimization problem critically increases even for low-complexity topologies, whereas the DPSC implementation becomes impossible for high-complexity inverters. Additionally, due to the absence of a PI controller in DPSC methods, stability issues arise; therefore, special care is mandated for eliminating steady-state errors. By using proper weighting of the speed errors, along with the current errors, in the cost function of the proposed PSC, the use of many prediction steps becomes unessential. For considering the current dynamics, a linear controller is incorporated in the control law of developed PSC offering improved system behavior, whereas the consideration of the speed errors allows achieving fast response characteristics. The proposed strategy is experimentally evaluated through examining reference and disturbance step changes of a PMSM drive with the three-level neutral-point clamped inverter. Finally, the proposed controller operation is experimentally compared with a predictive torque and speed control, by considering several performance indices.
TL;DR: A very simple modification to the original SIMC-rule is proposed, which is to add a derivative time τd = θ/3 (for the serial PID-form) that gives performance close to the IAE-optimal PID also for delay-dominant processes.