Robust Liquid Level Control of Quadruple Tank System: A Nonlinear Model-Free Approach

Abstract

In this paper, two new versions of modified active disturbance rejection control (MADRC) are proposed to stabilize a nonlinear quadruple tank system and control the water levels of the lower two tanks in the presence of exogenous disturbances, parameter uncertainties, and parallel varying input set-points. The first proposed scheme is configured from the combination of a modified tracking differentiator (TD), modified super twisting sliding mode (STC-SM), and modified nonlinear extended state observer (NLESO), while the second proposed scheme is obtained by aggregating another modified TD, a modified nonlinear state error feedback (MNLSEF), and a fal-function-based ESO. The MADRC schemes with a nonlinear quadruple tank system are investigated by running simulations in the MATLAB/SIMULINK environment and several comparison experiments are conducted to validate the effectiveness of the proposed control schemes. Furthermore, the genetic algorithm (GA) is used as a tuning algorithm to parametrize the proposed MADRC schemes with the integral time absolute error (ITAE), integral square of the control signal (ISU), and integral absolute of the control signal (IAU) as an output performance index (OPI). Finally, the simulation results show the robustness of the proposed schemes with a noticeable reduction in the OPI.

Liquid Level Control Interface Design on Simulink External Mode with Raspberry Pi

“…Genetic algorithm is used in optimization process of the system. The robustness of the proposed method is proven by simulation results [5].…”

New Control Schemes for Actuators

“…In the work of Hashim et al [21], two new versions of modified active disturbance rejection controls (MADRCs) were proposed, which aimed to stabilize a non-linear quadruple tank system and to control the water levels of the lower two tanks in the presence of exogenous disturbances, parameter uncertainties and parallel varying input set-points. The first proposed scheme was configured from the combination of a modified tracking differentiator (TD), a modified super twisting sliding mode (STC-SM) and a modified non-linear extended state observer (NLESO).…”

Life Cycle Cost Analysis of Pumping System through Machine Learning and Hidden Markov Model

“…The third pump is chosen from a reputable Indian pump manufacturer, and the necessary information is acquired directly from the supplier. The idea of the predicted number of failures in a particular time interval has been used to model the maintenance and repair costs [23]. A methodology for calculating the net present value (NPV), lifetime costs (LCC), energy use, and greenhouse gas emissions related to a water distribution system (WDS) pump using a process-based life cycle assessment (LCA) and an economic input-output LCA (EIO-LCA) model has been described in the research.…”

“…If the output is continuous or nearly so, the calculation is straightforward. A time-based consumption pattern must be established if the production fluctuates over time [21][22][23][24][25][26][27][28][29]. Operating costs are the labour expenses related to running a pumping system.…”