Design and statistical robustness analysis of FOPID, IOPID and SIMC PID controllers for the control of an input-output linearized plant model

2015 ◽  
Author(s):  
J. Viola ◽  
L. Angel
Keyword(s):  
Robustness Analysis ◽  
Pid Controllers ◽  
Input Output ◽  
Plant Model ◽  
Statistical Robustness

scholarly journals Algorithm for Multiple Model Adaptive Control Based on Input-Output Plant Model

2012 ◽  
Vol 12 (1) ◽  
pp. 13-33 ◽  
Author(s):  
Tsonyo Slavov
Keyword(s):  
Adaptive Control ◽  
Covariance Matrix ◽  
Pid Controllers ◽  
Multiple Model ◽  
Input Output ◽  
Error Covariance Matrix ◽  
Error Covariance ◽  
Multiple Model Adaptive Control ◽  
Weighting Coefficients ◽  
General Error

Abstract An algorithm for multiple model adaptive control of a time-variant plant in the presence of measurement noise is proposed. This algorithm controls the plant using a bank of PID controllers designed on the base of time invariant input/output models. The control signal is formed as weighting sum of the control signals of local PID controllers. The main contribution of the paper is the objective function minimized to determine the weighting coefficients. The proposed algorithm minimizes the sum of the square general error between the model bank output and the plant output. An equation for on-line determination of the weighting coefficients is obtained. They are determined by the current value of the general error covariance matrix. The main advantage of the algorithm is that the derived general error covariance matrix equation is the same as this in the recursive least square algorithm. Thus, most of the well known RLS modifications for the tracking timevariant parameters can be directly implemented. The algorithm performance is tested by simulation. Results with both SISO and MIMO time variant plants are obtained.

Design and Control of a Shape Memory Alloy Actuated Robotic Catheter

2008 ◽  
Author(s):  
Arun S. Veeramani ◽  
John H. Crews ◽  
Gregory D. Buckner ◽  
Stephen B. Owen ◽  
Richard C. Cook ◽  
...  
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Imaging System ◽  
Open Loop ◽  
Pid Controllers ◽  
Input Output ◽  
Position Feedback ◽  
Catheter Tip ◽  
And Control ◽  
Reference Trajectories

This paper details the development of a Neural Network (NN) controller for a Shape Memory Alloy (SMA) actuated catheter, with potential application to tele-operated cardiac ablation procedures. The robotic catheter prototype consists of a central tubular structure actuated by four SMA tendons. A dual-camera imaging system provides position feedback of the catheter tip. Open loop bending responses are obtained and associated nonlinearities are identified. A NN controller is designed using time-shifted input-output maps generated from randomized open loop measurements. The tracking performance of this NN controller is compared with PI/PID controllers for various reference trajectories.

scholarly journals MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 36 ◽  
Author(s):  
Rafael Guardeño ◽  
Manuel J. López ◽  
Víctor M. Sánchez
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Low Cost ◽  
Robustness Analysis ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Estimation Errors ◽  
Plant Model ◽  
Bias Drift ◽  
Noise Characteristics

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors.

scholarly journals Robustness Analysis of the Estimators for the Nonlinear System Identification

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 834
Author(s):  
Wiktor Jakowluk ◽  
Karol Godlewski
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Adaptive Filtering ◽  
Nonlinear System Identification ◽  
Robustness Analysis ◽  
Estimation Methods ◽  
Function Evaluation ◽  
Model Parameters ◽  
Maximum Information ◽  
Plant Model

The main objective of the system identification is to deliver maximum information about the system dynamics, while still ensuring an acceptable cost of the identification experiment. The focus of such an idea is to design an appropriate experiment so that the departure from normal working conditions during the identification task is minimized. In this paper, the adaptive filtering (AF) scheme for plant model parameter estimation is proposed. The experimental results are obtained using the nonlinear interacting water tanks system. The adaptive filtering is expressed by minimizing the error between the system and the plant model outputs subject to the white noise signal affecting system output. This measurement error is quantified by the comparison of Minimum Error Entropy Renyi (MEER), Least Entropy Like (LEL), Least Squares (LS), and Least Absolute Deviation (LAD) estimators, respectively. The plant model parameters were obtained using sequential quadratic programming (SQP) algorithm. The robustness tests for the double-tank water system parameter estimators are performed using the ellipsoidal confidence regions. The effectiveness analysis for the above-mentioned estimators relies on the total number of iterations and the number of function evaluation comparisons. The main contribution of this paper is the evaluation of different estimation methods for the nonlinear system identification using various excitation signals. The proposed empirical study is illustrated by the numerical examples, and the simulation results are discussed.

Whether the opinion about superiority of fuzzy controllers is justified

2010 ◽  
Vol 58 (1) ◽  
pp. 59-65 ◽  
Author(s):  
R. Gessing
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Controller ◽  
Pid Controllers ◽  
Fuzzy Approach ◽  
Input Output ◽  
Fuzzy Controllers ◽  
Better Than

Whether the opinion about superiority of fuzzy controllers is justifiedIn the paper, using some MATLAB fuzzy logic toolbox Demos, in which the fuzzy controllers are compared with the classical PID ones, it is shown that the well tuned classical PID controllers are significantly better than those fuzzy presented in the Demos. It is shown, that using fuzzy approach, it is very difficult to shape the input-output nonlinearity, describing the so called fuzzy block of the fuzzy controller. It is also shown, that the linear fuzzy block (created to obtain comparable results with the classical PID controllers) is not justified at all, because it may be replaced by the usual summing junction, which is significantly simpler. The considerations of the paper do not support the idea of fuzzy controllers.

scholarly journals Input/output Linearization Control Technique for Anaerobic Digestion Reactor with Recirculation

2020 ◽  
Vol 141 ◽  
pp. 01007
Author(s):  
Sura Srisuddee ◽  
Malinee Sriariyanun ◽  
Chanin Panjapornpon ◽  
Atthasit Tawai
Keyword(s):  
Wastewater Treatment ◽  
Control System ◽  
Anaerobic Digestion ◽  
Control Technique ◽  
Pid Controllers ◽  
Input Output ◽  
Control Loops ◽  
Control Scheme ◽  
Continuously Stirred Tank Reactor ◽  
Regulatory Problems

Anaerobic digestion (AD) process has been generally applied in factories for wastewater treatment and energy recovery. For the AD processes, the continuously stirred tank reactor (CSTR) with recirculation are typically applied in industries for methane production from wastewater treatment. Since the recycle stream affects the inlet concentration of the reactor, the control performance of traditional PI and PID controllers used to manipulate control actuators may be limited. Additionally, the process control loops related to biochemical reactions are generally employed the operational experiences without process dynamic consideration. A control system based on input/output (I/O) linearization control technique for an anaerobic digestion (AD) process was developed in this work. The control system applied the concept of the I/O linearization technique, which followed dynamic behaviors of the reactor with a two-step (acidogenesis-methanogenesis) kinetic model. The volatile fatty acid (VFA) concentration was regulated by manipulation of the dilution rate to achieve the requested trajectories. Control performances of the closed-loop system were investigated by a simulation under servo and regulatory problems. The simulation results showed that the developed control scheme successfully forced the controlled output to achieve the desired set points and handled the introduced control problems.

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