Design of Self-Adaptive PID Controller Based on Least Square Method

Liu, Xiaoyu; Huang, Tinglai; Tang, Xiangjiao; Xin, Hongbo

doi:10.1109/wgec.2009.65

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…The method of least squares is a standard approach in system identification for identifying the parameters. Least squares mean that the overall solution minimizes the sum of the squares of the errors made in solving every single equation [12]. It can be mentioned that data fitting is an important least square applications.…”

Section: Gain Schedulingmentioning

confidence: 99%

Temperature Control of a Continuous Stirred Tank Reactor by Means of two Different Intelligent Strategies

Rahmat

Yazdani

Movahed

et al. 2011

International Journal on Smart Sensing and Intelligent Systems

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Section: Gain Schedulingmentioning

confidence: 99%

Temperature Control of a Continuous Stirred Tank Reactor by Means of two Different Intelligent Strategies

Rahmat

Yazdani

Movahed

et al. 2011

International Journal on Smart Sensing and Intelligent Systems

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“…In order to get the better results, the controller has to be adaptive so that it can adjust the controller gain to adapt to the position and attitude change of the quadrotor. Many people have tried to design this adaptive control such as Gaikwad [4] with auto-tuning PID Loop Shaping and Liu [5] who design self-adaptive PID based on the least-square method. Another approach is proposed to control a quadcopter using PD controller equipped with active force control to reject uncertainty disturbance by estimating disturbance torque value [6].…”

Section: Introductionmentioning

confidence: 99%

A Modified Gain Schedulling Controller by Considering the Sparseness Property of UAV Quadrotors

Abdurrohman

Inovan

Ataka

et al. 2015

J. Mechatron. Electr. Power Veh. Technol.

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This work presented the gain scheduling based LQR for Quadrotor systems. From the original nonlinear model, the system is always controllable and observable in various equilibrium points. Moreover, the linearized systems have a unique property that is known as sparse system. Hence, in order to implement the most efficient state feedback controller, post-filter and pre-filter were introduced to transform the state coordinate to decrease coupling between states. Finally, the gain scheduling systems using these facts was proposed. The system behavior was tested using the proposed controller. The numerical studies showed the effectiveness of the controller to achieve desired altitude, attitude, and its ability during the disturbance.

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“…An adaptive PID controller is presented in [10] using least square method which is an offline parameter estimation method. On the other hand, an optimal self-tuning PID controller is introduced in [5] using RLS to estimate the model from its dynamic data.…”

Section: Introductionmentioning

confidence: 99%

Adaptive PID Controller Using RLS for SISO Stable and Unstable Systems

Fahmy¹,

Badr

Rahman³

2014

Advances in Power Electronics

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The proportional-integral-derivative (PID) is still the most common controller and stabilizer used in industry due to its simplicity and ease of implementation. In most of the real applications, the controlled system has parameters which slowly vary or are uncertain. Thus, PID gains must be adapted to cope with such changes. In this paper, adaptive PID (APID) controller is proposed using the recursive least square (RLS) algorithm. RLS algorithm is used to update the PID gains in real time (as system operates) to force the actual system to behave like a desired reference model. Computer simulations are given to demonstrate the effectiveness of the proposed APID controller on SISO stable and unstable systems considering the presence of changes in the systems parameters.

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Design of Self-Adaptive PID Controller Based on Least Square Method

Cited by 4 publications

References 1 publication

Temperature Control of a Continuous Stirred Tank Reactor by Means of two Different Intelligent Strategies

Temperature Control of a Continuous Stirred Tank Reactor by Means of two Different Intelligent Strategies

A Modified Gain Schedulling Controller by Considering the Sparseness Property of UAV Quadrotors

Adaptive PID Controller Using RLS for SISO Stable and Unstable Systems

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