A new multiobjective performance criterion used in PID tuning optimization algorithms

Sahib, Mouayad A.; Ahmed, Bestoun S.

doi:10.1016/j.jare.2015.03.004

Cited by 129 publications

(53 citation statements)

References 25 publications

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“…The significance of each term is defined by a weighting factor w i . For an optimum compromised response, the weighting factors in Eq (15) are selected to be; w 1 = 0.452, w 2 = 0.438, w 3 = 0.11, and w 4 = 100 [51]. …”

Section: Resultsmentioning

confidence: 99%

Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design

et al. 2016

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Combinatorial test design is a plan of test that aims to reduce the amount of test cases systematically by choosing a subset of the test cases based on the combination of input variables. The subset covers all possible combinations of a given strength and hence tries to match the effectiveness of the exhaustive set. This mechanism of reduction has been used successfully in software testing research with t-way testing (where t indicates the interaction strength of combinations). Potentially, other systems may exhibit many similarities with this approach. Hence, it could form an emerging application in different areas of research due to its usefulness. To this end, more recently it has been applied in a few research areas successfully. In this paper, we explore the applicability of combinatorial test design technique for Fractional Order (FO), Proportional-Integral-Derivative (PID) parameter design controller, named as FOPID, for an automatic voltage regulator (AVR) system. Throughout the paper, we justify this new application theoretically and practically through simulations. In addition, we report on first experiments indicating its practical use in this field. We design different algorithms and adapted other strategies to cover all the combinations with an optimum and effective test set. Our findings indicate that combinatorial test design can find the combinations that lead to optimum design. Besides this, we also found that by increasing the strength of combination, we can approach to the optimum design in a way that with only 4-way combinatorial set, we can get the effectiveness of an exhaustive test set. This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly.

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Section: Resultsmentioning

confidence: 99%

Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design

et al. 2016

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“…There are many objective functions can be used in the PSO algorithm to get the PID parameters values. The most widely used function isthe time domain integral error performance criteria which depends on calculating the error between the input signal and the system output signal [17]. The integral of time multiplied by absolute error (ITAE) objective function, which is shown in equation (7), has been optimized through PSO algorithm for finding the PID controller parameters values.…”

Section: Controller Designmentioning

confidence: 99%

PID Controller Design for Cruise Control System using Particle Swarm Optimization

Abdulnabi

2017

ijci

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This paper presents a design of a Proportional-Integral-Derivative (PID) controller for automobile cruise control system. The parameters of the PID controller, which are the proportional ( ), derivative ( ) , and integrator ( ), have been selected using Particle Swarm Optimization (PSO) algorithm. In this study, the overall system performance has been compared with other predesigned controllers (conventional PID, Fuzzy logic PID, state space, and Genetic algorithm based PID controller). The simulation result illustrates that PSO based PID controller gives the best response in terms of settling time, rise time, peak time, and maximum overshot. The robustness analysis shows that the system is robust despite the deviations in some of the system parameters.

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“…However, it has been stated [13] that it doesn't mean minimizing all the performance parameters of system response such as the percent of overshoot (P.O. ), settling time (Ts), rising time (Tr), or steady state (Ess) at the same time.…”

Section: Integral Of Square Time Multiplied By Square Error (Istse)mentioning

confidence: 99%

A hybrid control design of FOPID and FWA for inverted pendulum systems

2016

J. appl. phys. sci.

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Abstract-Nowadays, along with the dramatic development of industrial automatic, optimization problem has been playing an important role in designing controllers for nonlinear systems. This paper proposes a hybrid control design of Fast Output Sampling Discrete Sliding Mode Control (FOSDSMC) and fractional order PID controller (FOPID) based on ireworks algorithm (FWA) to optimize controller parameters. The hybrid controller is veri ied on a nonlinear inverted pendulum system. The simulation of controller optimization process is carried out using MATLAB/Simulink. The results are compared with two published controllers such as a hybrid control design of PID controller and fast output sampling discrete sliding mode control, and a hybrid control con iguration of PID and state feedback controller based on linear quadratic regulator method. The comparison results show the better performance of the proposed method.

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A new multiobjective performance criterion used in PID tuning optimization algorithms

Cited by 129 publications

References 25 publications

Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design

Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design

PID Controller Design for Cruise Control System using Particle Swarm Optimization

A hybrid control design of FOPID and FWA for inverted pendulum systems

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