Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

2018 ◽  
Vol 36 (2) ◽  
pp. e12366 ◽  
Author(s):  
Thiagarajan Piraisoodi ◽  
Willjuice Iruthayarajan Maria Siluvairaj ◽  
Mohaideen Abdul Kadhar Kappuva
Keyword(s):  
Evolutionary Computation ◽  
Fractional Order ◽  
Controller Design ◽  
Hydraulic Turbine ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Computation Techniques ◽  
Proportional Integral ◽  
Multi Objective ◽  
Governing System

Adaptive fractional order fuzzy proportional–integral–derivative control of smart base-isolated structures equipped with magnetorheological dampers

2017 ◽  
Vol 29 (5) ◽  
pp. 830-844 ◽  
Author(s):  
Abbas-Ali Zamani ◽  
Saeed Tavakoli ◽  
Sadegh Etedali ◽  
Jafar Sadeghi
Keyword(s):  
Active Control ◽  
Fractional Order ◽  
Control Strategies ◽  
Near Field ◽  
Magnetorheological Damper ◽  
Proportional Integral Derivative ◽  
Isolation System ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Multi Objective

The current semi-active or even active control strategies have been developed to address a few drawbacks, such as unwanted large displacements created at the base level and system deficiency in adaptation to different types of seismic excitations, in the base isolation systems. In this article, two control strategies, multi-objective modified clipped optimal and adaptive fractional order fuzzy proportional–integral–derivative, are proposed for semi-active control of a smart base-isolated structure equipped with a magnetorheological damper. The main objective is to reduce the displacement of isolation system without allowing significant increase in the acceleration of superstructure for both far-field and near-field earthquake excitations. Using proper fitness functions, the weighting matrices of the multi-objective modified clipped optimal controller are tuned using multi-objective optimization. Then, the parameters of the fractional order fuzzy proportional–integral–derivative controller are obtained. Next, the fuzzy rule weights of the fractional order fuzzy proportional–integral–derivative controller are updated online based on the values of ground motion and structural responses using an adaptive strategy. For comparison, two control cases in which the magnetorheological damper is in passive mode, passive-off and passive-on, are considered. Numerical simulations show that the proposed adaptive fractional order fuzzy proportional–integral–derivative controller better mitigates the seismic responses of a base-isolated structure excited by a range of real-data earthquakes.

Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energy sources based on multi-objective grasshopper optimization algorithm

2021 ◽  
pp. 014233122110346
Author(s):  
Abdulsamed Tabak
Keyword(s):  
Fractional Order ◽  
Optimization Algorithm ◽  
Frequency Control ◽  
Frequency Deviation ◽  
Control Signal ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multi Objective ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

In recent years, fractional order proportional-integral-derivative (FOPID) controllers have been applied in different areas in the academy due to their superior performance over conventional proportional-integral-derivative (PID) controllers. When the literature is reviewed, it has been observed that lack of studies that use swarm-based and multi-objective optimization algorithms together with FOPID controllers in frequency control of micro-grid. The load frequency control (LFC) problem is considered as two objectives in order to eliminate the complications that occur when only the frequency deviation is minimized. In our study, a method called MOGOA-FOPID in which both the frequency deviation and the control signal are minimized together for the frequency control in the microgrid is proposed. By using the multi-objective grasshopper optimization algorithm (MOGOA), both the frequency deviation and the control signal are minimized together, and thus, it is aimed to limit the battery capacity, reduce the flywheel jerk and avoid high diesel fuel consumption as well as an effective frequency control. In order to obtain a more realistic system, not only the photovoltaic (PV) solar and wind power but also the load demand is taken in a stochastic structure. Then, the results of the proposed MOGOA-FOPID are compared with the results of multi-objective genetic algorithm (MOGA)-based PID/FOPID and MOGOA-PID and its superiority is demonstrated. Finally, robustness tests of the system are performed under the perturbed parameters and outperform of MOGOA-FOPID over other methods is seen.

Design of an integer order proportional–integral/proportional–integral–derivative controller based on model parameters of a certain class of fractional order systems

2018 ◽  
Vol 233 (3) ◽  
pp. 320-334 ◽  
Author(s):  
Erhan Yumuk ◽  
Müjde Güzelkaya ◽  
İbrahim Eksin
Keyword(s):  
Fractional Order ◽  
Design Parameter ◽  
Design Methodology ◽  
Model Parameters ◽  
Proportional Integral Derivative ◽  
Level Control ◽  
Proportional Integral Derivative Controller ◽  
Integer Order ◽  
Proportional Integral ◽  
Order Pole

In this study, we deal with systems that can be represented by single fractional order pole models and propose an integer order proportional–integral/proportional–integral–derivative controller design methodology for this class. The basic principle or backbone of the design methodology of the proposed controller relies on using the inverse of the fractional model and then approximating this fractional controller transfer function by a low integer order model using Oustaloup filter. The emerging integer order controller reveals itself either in pre-filtered proportional–integral or proportional–integral–derivative form by emphasizing on the dominancy concept of pole-zero configuration. Parameters of the proposed controllers depend on the parameters of the single fractional order pole model and the only free design parameter left is the overall controller gain. This free design parameter is determined via some approximating functions relying on an optimization procedure. Simulation results show that the proposed controller exhibits either satisfactory or better results with respect to some performance indices and time domain criteria when they are compared to classical integer order proportional–integral–derivative and fractional order proportional–integral–derivative controllers. Moreover, the proposed controller is applied to real-time liquid level control system. The application results show that the proposed controller outperforms the other controllers.

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