Designing of IMC-PID Controller for Higher-order Process Based on Model Reduction Method and Fractional Coefficient Filter with Real-time Verification

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Ujjwal Manikya Nath ◽  
Chanchal Dey ◽  
Rajani K. Mudi
Keyword(s):  
Model Reduction ◽  
Real Time ◽  
Pid Controller ◽  
Performance Enhancement ◽  
Higher Order ◽  
Process Models ◽  
Reduction Scheme ◽  
Level Control ◽  
First Order ◽  
Improved Model

AbstractAn improved model reduction scheme is proposed here for higher-order processes and subsequently an enhanced IMC-PID controller is designed based on the obtained reduced model. In the proposed scheme, higher-order processes are estimated as first-order-plus-dead-time (FOPDT) model. Designed IMC controller includes a filter having two separate time constants with fractional order coefficients. Efficacy of the proposed model reduction scheme is verified in terms of closed loop performance evaluation for higher-order minimum and non-minimum phase process models in comparison with improved SIMC (iSIMC) controller (Grimholt. Optimal PI and PID control of first-order plus delay processes and evaluation of the original and improved SIMC rules. J Process Control. 2018;70:36–46). Overall performance enhancement for the proposed method is demonstrated through simulation study as well as real-time experimentation on a level control loop.

scholarly journals Real Time Level Control of Conical Tank and Comparison of Fuzzy and Classical Pid Controller

2015 ◽  
Vol 8 (S2) ◽  
pp. 40 ◽  
Author(s):  
C. Dinesh ◽  
V. V. Manikanta ◽  
H. S. Rohini ◽  
K. R. Prabhu
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Level Control ◽  
Time Level

scholarly journals Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
V. Rajinikanth ◽  
K. Latha
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Nonlinear Process ◽  
Process Models ◽  
Proportional Integral Derivative ◽  
Controller Tuning ◽  
Spherical Tank ◽  
Pid Controller Tuning ◽  
Tank System ◽  
Tuning Methods

An enhanced bacteria foraging optimization (EBFO) algorithm-based Proportional + integral + derivative (PID) controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.

Higher-Order Stabilized Perturbation for Recursive Eigen-Decomposition Estimation

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Paul Mucchielli ◽  
Basuraj Bhowmik ◽  
Budhaditya Hazra ◽  
Vikram Pakrashi
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Higher Order ◽  
Mode Shapes ◽  
Accurate Estimation ◽  
Perturbation Approach ◽  
Mode Identification ◽  
First Order ◽  
Ill Conditioned Matrices ◽  
Eigen Decomposition

Abstract Eigen-decomposition remains one of the most invaluable tools for signal processing algorithms. Although traditional algorithms based on QR decomposition, Jacobi rotations and block Lanczos tridiagonalization have been proposed to decompose a matrix into its eigenspace, associated computational expense typically hinders their implementation in a real-time framework. In this paper, we study recursive eigen perturbation (EP) of the symmetric eigenvalue problem of higher order (greater than one). Through a higher order perturbation approach, we improve the recently established first-order eigen perturbation (FOP) technique by creating a stabilization process for adapting to ill-conditioned matrices with close eigenvalues. Six algorithms were investigated in this regard: first-order, second-order, third-order, and their stabilized versions. The developed methods were validated and assessed on multiple structural health monitoring (SHM) problems. These were first tested on a five degrees-of-freedom (DOF) linear building model for accurate estimation of mode shapes in an automated framework. The separation of closely spaced modes was then demonstrated on a 3DOF + tuned mass damper (TMD) problem. Practical utility of the methods was probed on the Phase-I ASCE-SHM benchmark problem. The results obtained for real-time mode identification establishes the robustness of the proposed methods for a range of engineering applications.

scholarly journals PSO-Based PID Controller Design for a Class of Stable and Unstable Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
K. Latha ◽  
V. Rajinikanth ◽  
P. M. Surekha
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Pid Controller ◽  
Controller Design ◽  
Pso Algorithm ◽  
Search Space ◽  
Process Models ◽  
Stabilizing Controller ◽  
Fixed Weight ◽  
Unstable Process

Nonlinear processes are very common in process industries, and designing a stabilizing controller is always preferred to maximize the production rate. In this paper, tuning of PID controller for a class of time delayed stable and unstable process models using Particle Swarm Optimization (PSO) algorithm is discussed. The dimension of the search space is only three (, , and ); hence, a fixed weight is assigned for the inertia parameter. A comparative study is presented between various inertia weights such as 0.5, 0.75, and 1. From the result, it is evident that the proposed method helps to attain better controller settings with reduced iteration number. The efficacy of the proposed scheme has been validated through a comparative study with classical controller tuning methods and heuristic methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Finally, a real-time implementation of the proposed method is carried on a nonlinear spherical tank system. From the simulation and real-time results, it is evident that the PSO algorithm performs well on the stable and unstable process models considered in this work. The PSO tuned controller offers enhanced process characteristics such as better time domain specifications, smooth reference tracking, supply disturbance rejection, and error minimization.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

Challenging the Multidimensional Conception of Perceived Person-Environment Fit

2020 ◽  
pp. 1-9
Author(s):  
Julian M. Etzel ◽  
Gabriel Nagy
Keyword(s):  
Higher Education ◽  
University Students ◽  
Educational Outcomes ◽  
Factor Model ◽  
Higher Order ◽  
Substantial Proportion ◽  
Unique Variance ◽  
First Order ◽  
Person Environment Fit ◽  
Order Factor

Abstract. In the current study, we examined the viability of a multidimensional conception of perceived person-environment (P-E) fit in higher education. We introduce an optimized 12-item measure that distinguishes between four content dimensions of perceived P-E fit: interest-contents (I-C) fit, needs-supplies (N-S) fit, demands-abilities (D-A) fit, and values-culture (V-C) fit. The central aim of our study was to examine whether the relationships between different P-E fit dimensions and educational outcomes can be accounted for by a higher-order factor that captures the shared features of the four fit dimensions. Relying on a large sample of university students in Germany, we found that students distinguish between the proposed fit dimensions. The respective first-order factors shared a substantial proportion of variance and conformed to a higher-order factor model. Using a newly developed factor extension procedure, we found that the relationships between the first-order factors and most outcomes were not fully accounted for by the higher-order factor. Rather, with the exception of V-C fit, all specific P-E fit factors that represent the first-order factors’ unique variance showed reliable and theoretically plausible relationships with different outcomes. These findings support the viability of a multidimensional conceptualization of P-E fit and the validity of our adapted instrument.

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