Tree physiology optimization on SISO and MIMO PID control tuning

Halim, Abdul; Ismail, Idris

doi:10.1007/s00521-018-3588-9

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…Further, the method was effective in stabilizing unstable systems. Halim and Ismail 15 presented a PID controller tuning using tree physiology optimization, which was based on the tree growth concept whose simulation results showed better results compared to other tuning methods in Single Input Single Output (SISO) and MIMO problems. Rao et al ., 16 reported design of an observer using robust PID controller logic with H ∞ observer to obtain the stable output in TRMS with sensor and actuator failure.…”

Section: Introductionmentioning

confidence: 99%

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

et al. 2021

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Background: This paper presents a soft sensor design technique for the estimation of pitch and yaw angular positions of a Twin Rotor MIMO System (TRMS). The objective of the proposed work was to calculate the value of pitch and yaw angular positions using a stochastic estimation technique. Methods: Measurements from optical sensors were used to measure fan blade rotations per minute (RPM). The Kalman filter, which is a stochastic estimator, was used in the proposed system and its results were compared with those of the Luenberger observer and neural network. The Twin Rotor MIMO System is a nonlinear system with significant cross-coupling between its rotors. Results: The estimators were designed for the decoupled system and were applied in real life to the coupled TRMS. The convergence of estimation to the actual values was checked on a practical setup. The Kalman filter estimators were evaluated for various inputs and disturbances, and the results were corroborated in real-time. Conclusion: From the proposed work it was seen that the Kalman filter had at least Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE) as compared to the neural network and the Luenberger based observer.

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Section: Introductionmentioning

confidence: 99%

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

et al. 2021

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Event-triggered control optimal tuning through bio-inspired optimization in robotic manipulators

2022

View full text Add to dashboard Cite

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

et al. 2021

View full text Add to dashboard Cite

Background: This paper presents a soft sensor design technique for estimation of pitch and yaw angular positions of a Twin Rotor MIMO System (TRMS). The objective of the proposed work was to calculate the value of pitch and yaw angular positions using a stochastic estimation technique. Methods: Measurements from optical sensors were used to measure fan blade rotations per minute (RPM). The Kalman filter, which is a stochastic estimator, was used in the proposed system and its results were compared with those of the Luenberger observer and neural network. The Twin Rotor MIMO System is a nonlinear system with significant cross coupling between its rotors. Results: The estimators were designed for the decoupled system and were applied in real life to the coupled TRMS. The convergence of estimation to the actual values was checked on a practical setup. The Kalman filter estimators were evaluated for various inputs and disturbances, and the results were corroborated in real time. Conclusion: From the proposed work it was seen that the Kalman filter had at least Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE) as compared to the neural network and the Luenberger based observer.

show abstract

Tree physiology optimization on SISO and MIMO PID control tuning

Cited by 3 publications

References 33 publications

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

Event-triggered control optimal tuning through bio-inspired optimization in robotic manipulators

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

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