Human Body Based Intelligent Cooperative Decoupling Controllers

Journal of Low Frequency Noise, Vibration and Active Control

et al. 2019

This paper proposes an improved neuroendocrine-proportional-integral-derivative controller for nonlinear multi-inputmulti-output crane systems using a sigmoid-based secretion rate of the hormone regulation. The main advantage of the sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative is that the hormone secretion rate of neuroendocrine-proportional-integral-derivative can be varied according to the change of error. As a result, it can provide high accuracy control performance, especially in nonlinear multi-input-multi-output crane systems. In particular, the hormone secretion rate is designed to adapt with the changes of error using a sigmoid function, thus contributing to enhanced control accuracy. The parameters of the sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative controller are tuned using the safe experimentation dynamics algorithm. The performance of the proposed sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative controller-based safe experimentation dynamics algorithm is evaluated by tracking the error and the control input. In addition, the performances of proportional-integral-derivative and neuroendocrine-proportional-integral-derivative controllers are compared with the proposed sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative performance. From the simulation work, it is discovered that the sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative design provides better control performances in terms of the objective function, the total norm of error and the total norm of input compared to proportional-integral-derivative and neuroendocrine-proportional-integral-derivative controllers. In particular, it is shown the proposed sigmoid-based secretion rate neuroendocrine-proportional-integral-derivative controller contributes 5.12% of control accuracy improvement by changing the fixed hormone secretion rate into a variable hormone secretion rate based on the change of error. Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www. creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).bouncing to avoid any cause of damage or accidents. Various controller methods have been proposed to achieve accurate movement. These include sliding mode control, 1 linear quadratic regulator (LQR) control, 2 feedback control, 3 H-infinity control, 4 proportional-integral-derivative (PID) with input shaping, 5 and fuzzy-sliding mode control. 6 Generally, most of the controller designs are model based, where the control is derived from mathematical model of the system, and this is very challenging and complicated in case of nonlinear dynamic systems. 7 Thus, model-based control methods potentially suffer from proble...

show abstract

mentioning

confidence: 91%

An improved neuroendocrine–proportional–integral–derivative controller with sigmoid-based secretion rate for nonlinear multi-input–multi-output crane systems

Journal of Low Frequency Noise, Vibration and Active Control

et al. 2019

show abstract

A Multiple-node Hormone Regulation of Neuroendocrine-PID (MnHR-NEPID) Control for Nonlinear MIMO Systems

IETE Journal of Research

2020

Data-Driven Neuroendocrine-PID Controller Design for Twin Rotor MIMO System

2020

J. Phys.: Conf. Ser.