Industrial information integration engineering (IIIE) is a set of foundational concepts and techniques that facilitate the industrial information integration process. In recent years, many applicat...

A Survey on Industrial Information Integration 2016–2019

The multimicrogrid system is a complicated nonlinear system, which brings performance degradation due to deficient damping under the unexpected fluctuation in power generation due to the presence of renewable sources, dynamically changing loading conditions, and parameter variations. Owing to this, to provide consistent electric power with superlative attribute, sturdy and intelligent control techniques are amazingly imperative in the automatic generation control of microgrid (MG). The application of imperialist competitive algorithm (ICA)-based fractional-order integral proportional derivative with filter (IPDF), i.e., integral tilt derivative with filter controller (ITDF) controller in frequency control in two areas interconnected MG (isolation mode) with renewable penetration, is a novel work. A maiden attempt of the ICA is proposed to optimize the gains of the ITDF controller utilizing the integral time absolute error criterion. To demonstrate the supremacy of ICA, its outcomes are contrasted with two existing optimization strategies, namely the genetic algorithm and the particle swarm optimization. The effectiveness of the proposed controller is revealed by contrasting the dynamic responses of multi microgrid (MMG) with proportional integral derivative with filter (PIDF) and tilt integral derivative with filter (TIDF) controllers. At last, a sensitivity investigation is performed to exhibit the power of the studied strategy to wide variations in the MG parameters, magnitude as well as the location of step/random load disturbance. The proposed MMG is simulated in MATLAB/Simulink environment.

An Integral Tilt Derivative Control Strategy for Frequency Control in Multimicrogrid System

PID controllers are still widely practiced in the industrial systems. In the literature, many publications can be found considering PID controller design for unstable processes. However, owing to the structural limitations of PID controllers, generally, good closed loop performance cannot be achieved with a PID for controlling unstable processes and usually a step response with a high overshoot and oscillation is obtained. On the other hand, PI-PD controllers are proved to give very satisfactory closed loop performances for unstable processes. The paper presents a simple design method to tune parameters of a PI-PD controller for the control of the unstable processes with time delay. The proposed method is based on plotting the stability boundary locus, which is a locus dependent on the parameters of the controller and frequency, in the parameter plane. The method uses a new concept named centroid of the convex stability region. Simulation examples and an experimental application are given to illustrate the superiority of the proposed method over some existing ones.

A new design method for PI-PD control of unstable processes with dead time.

A survey of single and multi-component Fractional-Order Elements (FOEs) and their applications

The primary aim of load frequency control (LFC) is to provide a good quality of electrical power to the consumers within a prescribed limit of frequency and scheduled tie-line power deviation. To achieve this objective, LFC needs highly efficient and intelligent control mechanism. Subsequently, here, a novel integral-tilt-derivative (I-TD) controller, fine-tuned by a powerful heuristic optimisation technique [called as water cycle algorithm (WCA)], is proposed for the LFC study of a two-area interconnected thermal-hydro-nuclear generating units. The studied system involves non-linearities like generation rate constraints, governor dead band, and boiler dynamics. To explore the effectiveness of the proposed controller, dynamic responses of the studied system, as obtained using I-TD controller, are compared to those yielded by other controllers such as tilt-integral-derivative and conventional proportional–integral–derivative controllers. The investigation demonstrates that the proposed I-TD controller delivers better performance in comparison to the other counterparts. Furthermore, sensitivity analysis is carried out to show robustness of the WCA tuned proposed I-TD controller by varying system parameters and loading condition. It is perceived that the proposed I-TD controller is robust and offers better transient response under varying operating conditions.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2018.0345

Novel application of integral-tilt-derivative controller for performance evaluation of load frequency control of interconnected power system

Fractional calculus has been a topic of great interest for the last few decades The applications of fractional calculus can be found in the area of viscoelastic and chaotic systems, whose dynamics is expressed in the form of fractional differential equations The ongoing research work is based on the design of 1-Degree of Freedom (1-DOF) and 2-Degrees of Freedom (2-DOF) Fractional Order PID (FOPID) controllers for a Magnetic levitation (Maglev) plant and the performance has been compared with that of 1-DOF and 2-DOF Integer Order PID (IOPID) controllers in both simulation and real time The Degree of Freedom (DOF) represents the number of feed-forward control loops in a closed loop system A 2-DOF controller configuration comprises of a serial compensator and a feed-forward compensator in a closed loop structure An FOPID controller has a structure similar to that of a conventional IOPID controller, except that its derivative and integral orders are fractional numbers The design of such a controller requires the determination of five parameters: Kp, Ki, Kd, α and β, where α and β are the derivative and integral orders of the FOPID controller The controller design problem has been framed as an optimization problem, in which the cost function is formulated from the characteristic equation of the closed loop system at dominant poles that are identified from the given performance specifications The closed loop response shows that the proposed2-DOF FOPID controller exhibits superior response and robustness with respect to its integer order counterpart

Real time implementation of fractional order PID controllers for a magnetic levitation plant

Summary This article is about the design of controllers for magnetic levitation (Maglev) system in both simulation and real time. Local linearization around the equilibrium point has been done for the nonlinear Maglev system to obtain a linearized model transfer function. In this study, the design of integral-tilted-derivative (I-TD) controller has been proposed for the Maglev system and its performance is compared with conventional tilted-integral-derivative (TID) controller. In this study, TID controller parameters have been optimized through genetic algorithm (GA) and those set of values have been employed for the design of I-TD controller. A performance comparison between TID and I-TD controller is then investigated. The analysis shows the superiority of I-TD controller over TID controller in terms of maximum overshoot, gain margin and phase margin. The settling time remains almost same in both the cases. In future, a detailed study of robustness in presence of model uncertainties will be incorporated as a scope of further research.

TID and I-TD controller design for magnetic levitation system using genetic algorithm

In this paper, the design of a Proportional-Integral-Derivative (PID) controller for the cruise control system has been proposed. The cruise control system, which is a highly nonlinear, has been linearized around the equilibrium point. The controller has been designed for the linearized model, by taking the dominant pole concept in the closed loop characteristic equation. The PID controller parameters, i.e. proportional, integral and derivative parameters have been tuned using Genetic Algorithm (GA). In this study, the performance of the controller has been compared with that of the conventional PID, state space and Fuzzy logic based controller. The simulation output reveals the superiority of the proposed controller in terms of maximum overshoot, peak time, rise time, settling time and steady state error. The sensitivity and complementary sensitivity analysis show the robust behaviour of the system with output disturbance and high-frequency noise rejection qualities. As a scope of further research, fractional order and 2-dof PID controller will be designed for this cruise control system and the performance will be compared with this design.

PID controller design for cruise control system using genetic algorithm

Though Center of Gravity (CoG) defuzzification is a well-known and long-standing method in the history of fuzzy systems, because of its computational complexity, its use in the field of modeling of fuzzy controllers is almost nil. From literature, it appears that modeling of fuzzy Proportional Integral Derivative (FPID) controllers is rarely attempted using CoG defuzzification. In fact, none of the FPID controller models are obtained using both two-dimensional input space and CoG defuzzification. The available mathematical models of fuzzy Proportional Integral (FPI) and fuzzy Proportional Derivative (FPD) controllers using two-dimensional input space and CoG defuzzification were due to Arun and Mohan (2017). In this paper, the authors make an attempt to model and design an FPID controller using two-dimensional input space and CoG defuzzification. The incremental control effort produced by the newly developed FPID controller is found by combining the individual control efforts produced by incremental FPI and incremental FPD controllers. The incremental FPI and incremental FPD controller structures are unveiled using two-dimensional input space, CoG defuzzification, Min t-norm, Max t-conorm, and Larsen Product (LP) inference. The applicability and usefulness of the newly obtained FPID controller are depicted with simulation and real-time experimentation.

Debdoot Sain

Papers

Real time implementation of fractional order PID controllers for a magnetic levitation plant

TID and I-TD controller design for magnetic levitation system using genetic algorithm

PID controller design for cruise control system using genetic algorithm

Modeling, simulation and experimental realization of a new nonlinear fuzzy PID controller using Center of Gravity defuzzification.

Real Time Implementation of Optimized I-PD Controller for the Magnetic Levitation System using Jaya Algorithm