Performance investigations of APSO tuned linear and nonlinear PID controllers for a nonlinear dynamical system

Valluru, Sudarshan K.; Singh, Madhusudan

doi:10.1016/j.jesit.2018.02.001

Cited by 24 publications

(8 citation statements)

References 13 publications

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“…Many works have been reported using the evolutionary algorithms for tuning the controller owing to their enhanced performance in the time domain specification. The PID controller tuning for TRMS control using various evolutionary computation methods is studied in Reference 25. In most of the works, only simulation results are used for performance analysis of the TRMS system.…”

Section: Cgsa Based Computation Methods For Tuning the Controllermentioning

confidence: 99%

Performance evaluation of a non linear PID controller using chaotic gravitational search algorithm for a twin rotor system

Sivadasan,

Shiney

2023

Adv Control Appl

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A novel strategy using a chaotic gravitational search algorithm (CGSA) based nonlinear PID control scheme, which is validated through a laboratory helicopter model called the twin rotor system, is presented in this paper. In this work, CGSA is used as a stochastic based global optimization algorithm for controller design in the twin rotor system adopted. The fine chaotic search process used in CGSA obtains the optimal solution in the iterative process based on the current best solution. The goal of the controller design in this paper is to stabilize the twin rotor system with considerable cross couplings to reach the selected position and follow the desired trajectory effectively. The addition of nonlinear functions to the PID controller structure initiates better error tracking and facilitates smooth output under changing input conditions. The design objective is to implement a nonlinear PID control scheme for the angular displacements of the twin rotor system with minimization of the integral square error (ISE) as the fitness function in the algorithm. The statistical performance of the controller is analyzed by considering the best, worst, mean, and standard deviations of ISE. In this work, simultaneous control of pitch and yaw angles is considered to get rid of the coupling effect between the two rotors. From the simulation results it is observed that the proposed work shows better performance than the other evolutionary computation techniques. The results also indicate the advantage of the proposed CGSA based tuning for the two degree of freedom MIMO control with standard reference trajectories as per the TRMS330‐10 model.

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Section: Cgsa Based Computation Methods For Tuning the Controllermentioning

confidence: 99%

Performance evaluation of a non linear PID controller using chaotic gravitational search algorithm for a twin rotor system

Sivadasan,

Shiney

2023

Adv Control Appl

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“…The proportional-integral (PI) is one of the most commonly used algorithms for closedloop control design. PI controllers have been effectively applied in the design and control of several systems [8,9]. Proportional and integral gain parameters, which are functions of the error between the desired set point and the actual system output, make up a standard PI controller.…”

Section: Closed-loop Control Designmentioning

confidence: 99%

Genetic-Algorithm-Based Proportional Integral Controller (GAPI) for ROV Steering Control

Tanveer

Ahmad

2023

Interact 2023

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“…3 However, for nonlinear systems with parameter uncertainties such as CSTR, the traditional PID controller is difficult to meet the control requirements of the CSTR process. 4 In recent years, the control algorithm combining nonlinear control and PID control has been used in system control. 5,6 NPID combines PID control with nonlinear control strategy, which not only inherits the simple structure of linear PID algorithm, but also shows good control performance in nonlinear system control, making it one of the simplest and most effective control methods in many control algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…3 However, for nonlinear systems with parameter uncertainties such as CSTR, the traditional PID controller is difficult to meet the control requirements of the CSTR process. 4…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization of nonlinear PID controller using RBF neural network for continuous stirred tank reactor

Shi

Zhao

Zheng

2023

Measurement and Control

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The temperature system of the Continuous Stirred Tank Reactor (CSTR) has the characteristics of strong nonlinearity and uncertain parameters. The linear PID controller makes it difficult to meet CSTR’s control requirements. Nonlinear PID (NPID) can improve the control effect of nonlinear controlled objects, but due to the influence of nonlinear function selection and manual parameter setting, when parameters are uncertain or subject to external interference, the control performance of the system will decrease. To improve the adaptive capability of the NPID controller, the RBF-NPID control algorithm is proposed. The learning ability of RBF neural network is used to adjust NPID parameters online to improve the control performance of the system. In order to verify the effectiveness of the proposed algorithm, a CSTR model was established in MATLAB and algorithm comparison research was carried out. Simulation results show the effectiveness and superiority of the proposed algorithm.

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Performance investigations of APSO tuned linear and nonlinear PID controllers for a nonlinear dynamical system

Cited by 24 publications

References 13 publications

Performance evaluation of a non linear PID controller using chaotic gravitational search algorithm for a twin rotor system

Performance evaluation of a non linear PID controller using chaotic gravitational search algorithm for a twin rotor system

Genetic-Algorithm-Based Proportional Integral Controller (GAPI) for ROV Steering Control

Parameter optimization of nonlinear PID controller using RBF neural network for continuous stirred tank reactor

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