Showing papers on "PID controller published in 2015"

A Repetitive Control Scheme for Harmonic Suppression of Circulating Current in Modular Multilevel Converters

Abstract: In a modular multilevel converter (MMC), the interaction between switching actions and fluctuating capacitor voltages of the submodules results in second- and other even-order harmonics in the circulating currents. These harmonic currents will introduce extra power loss, increase current stress of power devices, and even cause instability during transients. Traditional methods for circulating current harmonic suppression have problems such as limited harmonic rejection capability, limited application area, and complex implementation. This paper presents a plug-in repetitive control scheme to solve the problem. It combines the high dynamics of PI controller and good steady-state harmonic suppression of the repetitive controller, and minimizes the interference between the two controllers. It is suitable for multiple harmonic suppression, easy to implement, and applicable for both single-phase and three-phase MMCs. Simulation and experimental results on a single-phase MMC inverter proved the validity of the proposed control method.

Teaching-learning based optimization algorithm based fuzzy-PID controller for automatic generation control of multi-area power system

Abstract: Fuzzy-PID controller is proposed for AGC of multi-area power system.TLBO algorithm is applied to optimize the parameters of fuzzy-PID controller.The superiority of proposed approach over LCOA, GA, PS and SA based PID controller is shown.Robustness analysis is performed under wide changes in system parameters and disturbance. This paper deals with the design of a novel fuzzy proportional-integral-derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching-learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the fuzzy-PID controller. The superiority of proposed approach is demonstrated by comparing the results with some of the recently published approaches such as Lozi map based chaotic optimization algorithm (LCOA), genetic algorithm (GA), pattern search (PS) and simulated algorithm (SA) based PID controller for the same system under study employing the same objective function. It is observed that TLBO optimized fuzzy-PID controller gives better dynamic performance in terms of settling time, overshoot and undershoot in frequency and tie-line power deviation as compared to LCOA, GA, PS and SA based PID controllers. 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 fuzzy-PID controller gains are quite robust and need not be reset for wide variation in system parameters.

Adaptive PID Speed Control Design for Permanent Magnet Synchronous Motor Drives

Abstract: This paper proposes an adaptive proportional-integral-derivative (PID) speed control scheme for permanent magnet synchronous motor (PMSM) drives. The proposed controller consists of three control terms: a decoupling term, a PID term, and a supervisory term. The first control term is employed to compensate for the nonlinear factors, the second term is made to automatically adjust the control gains, and the third one is designed to guarantee the system stability. Different from the offline-tuning PID controllers, the proposed adaptive controller includes adaptive tuning laws to online adjust the control gains based on the gradient descent method. Thus, it can adaptively deal with any system parameter uncertainties in reality. The proposed scheme is not only simple and easy to implement, but also it guarantees an accurate and fast speed tracking. It is proven that the control system is asymptotically stable. To confirm the effectiveness of the proposed algorithm, the comparative experiments between the proposed adaptive PID controller and the conventional PID controller are performed on the PMSM drive. Finally, it is validated that the proposed design scheme accomplishes the superior control performance (faster transient response and smaller steady-state error) compared to the conventional PID method in the presence of parameter uncertainties.

Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller

Abstract: This paper presents a new modified Perturbation and Observation (PO however, P&O prone to failure especially when high changes in irradiance, oscillation around the MPP and the convergence speed. To face this challenge and in order to overcome the drawbacks of the classical P&O MPPT, a new method based on variable-step size of modified P&O MPPT method using PID controller tuned by genetic algorithm is presented. The efficiency of the proposed method has been studied successfully using a boost converter connected to a Solarex MSX-60 model. Analysis and comparison with the classical fixed step size P&O and that developed genetic variable step size are presented. The efficiency and improvements of the proposed algorithm in transient, steady-state and dynamic responses, especially under rapidly changing atmospheric conditions, related to ripple, overshoot and response time have been demonstrated. Algorithm robustness was verified using different schemes for temperature and insolation proving its ability to track the maximum power point in case of random and fast changing atmospheric conditions.

Active Disturbance Rejection Control for a Flywheel Energy Storage System

Abstract: This paper presents the application of the Active Disturbance Rejection Control Technique (ADRCT) to improve the performance of a Flywheel Energy Storage System (FESS). The FESS is designed for the DC MicroGrid (MG) application. It mainly consists of a flywheel with a coaxial BrushLess DC (BLDC) machine, a three-phase full-bridge circuit, and a bidirectional Buck–Boost converter. A model-independent controller based on the ADRCT, which can estimate and compensate model uncertainties and unknown disturbances in real time, is designed for the bidirectional Buck–Boost converter control in the FESS. Simulations and experiments are conducted in both charge and discharge mode to verify the performance of the proposed controller by comparison with a traditional double loop PI controller. Results show that the new controller is more robust and more adaptive. It has a better anti-disturbance capability and a higher dynamic performance than the PI controller. Moreover, to adapt to different applications and operating conditions, the charging process of the FESS is further improved. Strategies on maximum torque control and power limiting control are developed and realized on the experimental platform.

Modeling and control of autonomous underwater vehicle (AUV) in heading and depth attitude via self-adaptive fuzzy PID controller

Abstract: This paper focuses on design of a new self-adaptive fuzzy PID controller based on nonlinear MIMO structure for an AUV. Complexity and highly coupled dynamics, time-variance, and difficulty in hydrodynamic modeling and simulation, complicates the AUV modeling process and the design of proper and acceptable controller. In this work, the comprehensive nonlinear model of AUV is derived through kinematics and dynamic equations and then its treatment in open-loop is verified. In proposed controller, the PID parameters are adjusted by Mamdani fuzzy rules. Combined adaptive methods and dual PID controllers can improve solving of the uncertainty challenge in the PID parameters and AUV modeling uncertainty. The simulation results indicate that developed control system is stable, competent, and efficient enough to control the AUV in tracking the two channels of heading and depth with stabilized speed. Obtained results show that the proposed controller is not only robust, but also gives excellent dynamic, stunning steady-state characteristics and robust stability compared with a classically tuned PID controller.

Kriging Based Surrogate Modeling for Fractional Order Control of Microgrids

Abstract: This paper investigates the use of fractional order (FO) controllers for a microgrid. The microgrid employs various autonomous generation systems like wind turbine generator, solar photovoltaic, diesel energy generator, and fuel-cells. Other storage devices like the battery energy storage system and the flywheel energy storage system are also present in the power network. An FO control strategy is employed and the FO-proportional integral derivative (PID) controller parameters are tuned with a global optimization algorithm to meet system performance specifications. A kriging based surrogate modeling technique is employed to alleviate the issue of expensive objective function evaluation for the optimization based controller tuning. Numerical simulations are reported to prove the validity of the proposed methods. The results for both the FO and the integer order controllers are compared with standard evolutionary optimization techniques, and the relative merits and demerits of the kriging based surrogate modeling are discussed. This kind of optimization technique is not only limited to this specific case of microgrid control, but also can be ported to other computationally expensive power system optimization problems.

A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system

Abstract: Selection of objective function and controller structure is vital for controller design.An objective function using ITAE, damping ratio and settling times is proposed.The concept is applied to design an hGSA-PS-based PI/PID controller for LFC.Nonlinear interconnected power system model with GRC, GDB and time delay is considered. In this paper, a hybrid gravitational search algorithm (GSA) and pattern search (PS) technique is proposed for load frequency control (LFC) of multi-area power system. Initially, various conventional error criterions are considered, the PI controller parameters for a two-area power system are optimized employing GSA and the effect of objective function on system performance is analyzed. Then GSA control parameters are tuned by carrying out multiple runs of algorithm for each control parameter variation. After that PS is employed to fine tune the best solution provided by GSA. Further, modifications in the objective function and controller structure are introduced and the controller parameters are optimized employing the proposed hybrid GSA and PS (hGSA-PS) approach. The superiority of the proposed approach is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as firefly algorithm (FA), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), particle swarm optimization (PSO), hybrid BFOA-PSO, NSGA-II and genetic algorithm (GA) for the same interconnected power system. Additionally, sensitivity analysis is performed by varying the system parameters and operating load conditions from their nominal values. Also, the proposed approach is extended to two-area reheat thermal power system by considering the physical constraints such as reheat turbine, generation rate constraint (GRC) and governor dead band (GDB) nonlinearity. Finally, to demonstrate the ability of the proposed algorithm to cope with nonlinear and unequal interconnected areas with different controller coefficients, the study is extended to a nonlinear three unequal area power system and the controller parameters of each area are optimized using proposed hGSA-PS technique.

Robust Trajectory Tracking of a Delta Robot Through Adaptive Active Disturbance Rejection Control

Abstract: This paper describes the adaptive control design to solve the trajectory tracking problem of a Delta robot with uncertain dynamical model. This robot is a fully actuated, parallel closed-chain device. The output-based adaptive control was designed within the active disturbance rejection framework. An adaptive nonparametric representation for the uncertain section of the robot model was obtained using an adaptive least mean squares procedure. The adaptive algorithm was designed without considering the velocity measurements of the robot joints. Therefore, a simultaneous observer–identifier scheme was the core of the control design. A set of experimental tests were developed to prove the performance of the algorithm presented in this paper. Some reference trajectories were proposed which were successfully tracked by the robot. In all the experiments, the adaptive scheme showed a better performance than the regular proportional-integral-derivative (PID) controller with feed-forward actions as well as a nonadaptive active disturbance rejection controller. A set of numerical simulations was developed to show that even under five times faster reference trajectories, the adaptive controller showed better results than the PID controller.

Fractional-order load-frequency control of interconnected power systems using chaotic multi-objective optimization

Abstract: Multi-objective optimization-based fractional-order PID controller is designed.NSGA-II algorithm is augmented with chaotic Logistic and Henon map.Load disturbance rejection and controller effort are minimized as two conflicting objectives.FOPID controller outperforms the PID controller in suppressing frequency deviation.Better trade-off is obtained for load-frequency control of power systems with FOPID. Fractional-order proportional-integral-derivative (FOPID) controllers are designed for load-frequency control (LFC) of two interconnected power systems. Conflicting time-domain design objectives are considered in a multi-objective optimization (MOO)-based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore the effect of augmenting two different chaotic maps along with the uniform random number generator (RNG) in the popular MOO algorithm-the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Different measures of quality for MOO, e.g. hypervolume indicator, moment of inertia-based diversity metric, total Pareto spread, spacing metric, are adopted to select the best set of controller parameters from multiple runs of all the NSGA-II variants (i.e. nominal and chaotic versions). The chaotic versions of the NSGA-II algorithm are compared with the standard NSGA-II in terms of solution quality and computational time. In addition, the Pareto optimal fronts showing the trade-off between the two conflicting time domain design objectives are compared to show the advantage of using the FOPID controller over that with simple PID controller. The nature of fast/slow and high/low noise amplification effects of the FOPID structure or the four quadrant operation in the two inter-connected areas of the power system is also explored. A fuzzy logic-based method has been adopted next to select the best compromise solution from the best Pareto fronts corresponding to each MOO comparison criteria. The time-domain system responses are shown for the fuzzy best compromise solutions under nominal operating conditions. Comparative analysis on the merits and de-merits of each controller structure is reported then. A robustness analysis is also done for the PID and the FOPID controllers.

A new hybrid algorithm based on optimal fuzzy controller in multimachine power system

Abstract: In this article, a new methodology based on fuzzy proportional-integral-derivative PID controller is proposed to damp low frequency oscillation in multimachine power system where the parameters of proposed controller are optimized offline automatically by hybrid genetic algorithm GA and particle swarm optimization PSO techniques. This newly proposed method is more efficient because it cope with oscillations and different operating points. In this strategy, the controller is tuned online from the knowledge base and fuzzy interference. In the proposed method, for achieving the desired level of robust performance exact tuning of rule base and membership functions MF are very important. The motivation for using the GA and PSO as a hybrid method are to reduce fuzzy effort and take large parametric uncertainties in to account. This newly developed control strategy mixed the advantage of GA and PSO techniques to optimally tune the rule base and MF parameters of fuzzy controller that leads to a flexible controller with simple structure while is easy to implement. The proposed method is tested on three machine nine buses and 16 machine power systems with different operating conditions in present of disturbance and nonlinearity. The effectiveness of proposed controller is compared with robust PSS that tune using PSO and the fuzzy controller which is optimized rule base by GA through figure of demerit and integral of the time multiplied absolute value of the error performance indices. The results evaluation shows that the proposed method achieves good robust performance for a wide range of load change in the presents of disturbance and system nonlinearities and is superior to the other controllers. © 2014 Wiley Periodicals, Inc. Complexity 21: 78-93, 2015

Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload

Abstract: The robotic manipulators are multi-input multi-output (MIMO), coupled and highly nonlinear systems The presence of external disturbances and time-varying parameters adversely affects the performance of these systems Therefore, the controller designed for these systems should effectively deal with such complexities, and it is an intriguing task for control engineers This paper presents two-degree of freedom fractional order proportional-integral-derivative (2-DOF FOPID) controller scheme for a two-link planar rigid robotic manipulator with payload for trajectory tracking task The tuning of all controller parameters is done using cuckoo search algorithm (CSA) The performance of proposed 2-DOF FOPID controllers is compared with those of their integer order designs, ie, 2-DOF PID controllers, and with the traditional PID controllers In order to show effectiveness of proposed scheme, the robustness testing is carried out for model uncertainties, payload variations with time, external disturbance and random noise Numerical simulation results indicate that the 2-DOF FOPID controllers are superior to their integer order counterparts and the traditional PID controllers

Modeling, Identification, and Control of a Dielectric Electro-Active Polymer Positioning System

Abstract: This paper deals with a positioning system based on a dielectric electro-active polymer membrane. The motion is generated by the deformation of the membrane caused by the electrostatic compressive force between two compliant electrodes applied on the surface of the polymer. This paper proposes a detailed electro–mechanical nonlinear model of the system, which is subsequently used to develop (in both time and frequency domains) various model-based feedback control laws. Accurate modeling is useful to compensate the nonlinear behavior of the actuator (caused by the material characteristics and geometry) and obtain PID controllers providing precise tracking of steps or sinusoidal reference signals. The various design strategies are compared on various experimental tests.

An adaptive chattering-free PID sliding mode control based on dynamic sliding manifolds for a class of uncertain nonlinear systems

Abstract: This paper proposes a new dynamic PID sliding mode control technique for a class of uncertain nonlinear systems. The offered controller is formulated based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. Furthermore, this approach can eliminate the chattering phenomenon caused by the switching control action and can realize high-precision performance. Moreover, an adaptive parameter tuning method is proposed to estimate the unknown upper bounds of the disturbances. Simulation results for an inverted pendulum system demonstrate the efficiency and feasibility of the suggested technique.

Implementation of Evolutionary Fuzzy PID Speed Controller for PM Synchronous Motor

Abstract: We develop an evolutionary fuzzy proportional-integral-derivative (PID) controller for a permanent magnet synchronous motor (PMSM). We first consider a fuzzy PID control design problem based on the common control engineering knowledge that good transient performances can be obtained by increasing the P and I gains and decreasing the D gain when the transient error is big. Then we give an evolutionary algorithm (EA) to autotune the control parameters of the fuzzy PID controller. We implement the proposed EA-based fuzzy PID control controller in real time on a Texas Instruments TMS320F28335 floating-point DSP. We also give simulation and experimental results to show the effectiveness of the proposed intelligent digital control system under abrupt load torque variation using a prototype PMSM.