Two control strategies for multivariable processes are proposed that are based on a decentralised and a steady state decoupling approach. The designed controllers are fractional order PIs. The efficiency and robustness of the proposed strategies is tested and validated using a non-minimum phase process. Previous research for the same non-minimum phase process has proven that simple decentralised or decoupling techniques do not yield satisfactorily results and a multivariable IMC controller has been proposed as an alternative solution. The simulation results presented in this paper, as well as the experimental results, show that the proposed fractional order multivariable control strategies ensure an improved closed loop performance and disturbance rejection, as well as increased robustness to modelling uncertainties, as compared to traditional multivariable IMC controllers.

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Design and analysis of a multivariable fractional order controller for a non-minimum phase system:

In this paper, the problem of designing a multi-input multi-output (MIMO) system for studying the non-minimum phase (NMP) behaviour is considered. For this purpose, a NMP MIMO circuit is proposed and studied under different conditions. The main reason for designing this circuit is the lack of a simple and flexible benchmark for examining different control methods. Due to the simple structure and capability of showing different NMP characteristics, our proposed system is a suitable choice to study the behaviour of these systems. Also, our proposed system can be extended by series and parallel connections to generate more complicated benchmarks. The other advantages of this system are the large number of tunable parameters, adjustable interaction, variable number of poles and zeros, and inexpensive cost. Moreover, this benchmark can be used as a tool for hardware simulation. Finally, an optimal decoupling control is applied to this benchmark to verify its effectiveness.

A benchmark system to investigate the non-minimum phase behaviour of multi-input multi-output systems

Quadruple Conical Tank System (QCTS) is benchmark a laboratory setup for testing of various linear and nonlinear control algorithms for the multivariate control system. The multiple process configuration for multivariate input-output can be obtained from quadruple conical tank system. This article is concerned with designing a novel FaultTolerant Control (FTC) using Interval Type 2 Fuzzy Control (IT2FLC) subject to actuator and system component (Leak) faults. Additionally, paper explores the pen loop response with given operating points of quadruple conical tank system linearized model for non-minimum phase configuration obtained from MATLAB. The proposed control design method is simulated on prototype model of quadruple conical tank process for onminimum phase configuration. The performance of the proposed controller is studied through extensive simulations with regulatory and servo responses. Through comparative studies of proposed controller with other model based H∞, LQR, 2 DoF Decentralized PI Controller and model free Type 1 Fuzzy Logic controller (T1FLC) responses in MATLAB simulation environment, the effect of interaction, coupling, time variations and change in dynamic behaviour of QCTS confirmed.

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Design of Interval Type 2 Fuzzy Fault-Tolerant Controller for a Non-Minimum Phase System: Application to quadruple conical tank system.

The paper presents a fuzzy logic modified multi-stage hierarchical Fuzzy Logic PID Control Scheme for hybrid AC Grid-Drive-Battery Charging System. The multistage control scheme includes two fuzzy control stages for the separate PD and PID parts to ensure fast dynamical response, robust and effective speed control and efficient energy utilization with minimal ripple currents and transient over voltages during battery charging. The scheme ensures effective robust reference speed tracking of the dc PMDC motor drive with minimal transient currents and excursion voltage conditions. The use of dc side green plug and switched capacitor filters ensures effective stabilized damping and optimized performance on both dc and ac sides of the utilization hybrid AC-DC scheme. Dynamic speed regulation is enhanced by the introduced DC and AC filters regulated by multistage fuzzy logic multi loop controllers. AC side Switched Filter-Voltage stabilization is fully effective to ensure decoupled AC-DC operation and improved energy utilization and power factor enhancement.

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A Multi-Stage Fuzzy Logic Controller for Hybrid-AC Grid-Battery Charging Drive System

This paper is focused on the design of an algorithm for decoupling multivariable systems based on generalized predictive control and its application to control of a quadruple tank system. The quadruple-tank process is representative of a multivariable control problem that may be found in a chemical engineering process control application. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy system is suggested to model the plant dynamics at relevant operating regions. The developed model is used as a predictive model for a decoupling model predictive control algorithm.

Decoupling neuro-fuzzy model predictive controllers applied to quadruple tanks

Multivariable systems exhibit complex dynamics because of the interactions between input variables and output variables. This paper presents an approach to design auto tuned decentralized PI controller using ideal decoupler and adaptive techniques for controlling a class of multivariable process with a transmission zero. Using the decoupler, the MIMO system is transformed into two SISO systems. The controller parameters are adjusted using the Model Reference Adaptive reference Control (MRAC). A benchmark quadruple tank system (QTS) is considered to illustrate the benefits of the design paradigm. The performance of this set up was studied for reference tracking and disturbance rejection cases. Simulation results confirm the effectiveness of the proposed system. Keyword- Multivariable control, Decoupler, PI controller, Quadruple Tank process, Relative gain array, Model reference adaptive control.

/pdf/design-of-decentralised-pi-controller-using-model-reference-2megp6fqd2.pdf

Design of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process

Most of the industrial and chemical processes are raultivariable in nature. There are always complicated interactions existing between the measurement signals and control signals. Because of the interactions among the input and output variables, it is difficult to design suitable controller for Multi Input Multi Output (MEMO) systems. In control engineering, the goal of any controller design is to stabilize the system to track the set point and to reject the load disturbances in spite of the control challenges such as non-minimum phase behaviour, model uncertainties, unmeasured disturbances and constraints on input and output variables. In this paper, a model based controller is designed for a nonlinear multivariable process with a transmission zero to enhance its performance. To accomplish this goal, the experimental multivariable system, used in various control literature, called Quadruple Tank System (QTS) is taken for the controller synthesis. Internal Model Control (IMC) concept is used for the model based multi loop control for QTS and its performance is analyzed through simulation using MATLAB/SIMULENK. Simulation results proved the robustness of the proposed controller against the conventional controller under control challenges.

Design of model based controller to improve the performance of a nonlinear multivariable system with control challenges

Model Predictive Control design for a Non Linear Multivariable System with a Transmission Zero

Generating power through the wind mills is very common and essential now-a-days. In wind mills, designing a proper Condition Monitoring System is a difficult task. The main objective of this paper is a) to monitor the parameters like generator current, temperature, voltage, vibration, turbine speed in wind mills b) to detect fault in the temperature sensor and in the storage unit c) to control the parameters such as speed, temperature, current through LabVIEW. Basically, signal parameters will be detected by sensor units and conditioned with the help of Signal Conditioning Unit (SCU). Generally most of the signals will be analogies, and so it"s not convenient to process it further to the PIC Microcontroller. In order to do that, an Analog to Digital Converter (ADC) to be used for digital conversion and the PIC microcontroller has In-Built with ADC. Then, the controller will process those data and sends the appropriate output signal to Personal Computer (PC). Thus the information such as the temperature sensor fault, battery/storage unit fault, fault current etc is received and stored in the PC. The controller is interfaced to the PC through LabVIEW using Ethernet. The measured parameters is displayed through LabVIEW and based upon the data, the faults are rectified. The sequential monitoring of the data is possible through the LabVIEW and any variations that have to be made to maintain the stability of the control system is done with the help of Ethernet at any time. The Ethernet is the advanced communication link that enables us the faster transmission. This paper prevents the replacement of the Microcontroller every time an error occurs as done before and also reduces the total number of Microcontrollers used.

/pdf/multiple-parameter-monitor-and-control-in-wind-mills-4czkr8wn4g.pdf

Multiple parameter Monitor and Control in Wind Mills

This study presents the design of a Two- Degree-of-Freedom (2DOF) controller using Coefficient Diagram Method (CDM) techniques for three tank interacting system. By using the Taylor series, the mathematical modeling of nonlinear three tank interacting system is approximated as First Order Plus Dead Time (FOPTD) transfer function. Based on the CDM technique, the parameters of 2DOF controller are designed and implemented in three tank interacting system using MATLAB software. The servo performance of the proposed 2DOF controller using CDM technique control strategy is compared with the conventional PI controller. Finally, the performances of the two controllers are compared and analysed. The simulation results show that the proposed 2DOF controller using CDM technique control strategy is effective and potential for severe nonlinear control problem.

https://www.irjet.net/archives/V2/i9/IRJET-V2I916.pdf

D. Angeline Vijula

Papers

Design of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process

Design of model based controller to improve the performance of a nonlinear multivariable system with control challenges

Model Predictive Control design for a Non Linear Multivariable System with a Transmission Zero

Multiple parameter Monitor and Control in Wind Mills

Implementation of two-degree-of-freedom (2dof) controller using coefficient diagram method (cdm) techniques for three tank interacting system