Multivariable Control Systems Research Articles

Decoupling Control Applied to the Smart Grid Power Dispatching Problem

This paper presents controller designs of the decoupling issue dedicated to renewable decentralized generators or new generation grids known as smart grids. The control methods were based on a three-phase voltage source grid representation that integrated wind and photovoltaic generators. The utilized decoupling strategies (Boksenbom and Hood, Zilkind and Luyben, and inverted decoupling) allowed the optimization of energy transfers and costs through the routing grid distribution path. Simulations were conducted in Matlab/Simulink. The trustworthiness of the multivariable control system design in addition to the tuning method was established using three test batches, totally decoupled and stable from input dependencies.

Automated maneuvering using model-based control as key to autonomous shipping

Abstract The paper discusses methods to increase the level of automation in ship handling towards autonomous operations with a focus on conventional vessels in maneuvering situations. In this context, a model-based approach for control system design of maneuvering vessels is introduced. The resulting model is applied to a multivariable control system including allocation, feedforward, and feedback modules. The established hybrid control system distinguishes between a transit mode with control in two degrees of freedom in compliance with the prevailing traffic regulations and a dynamic positioning mode in three degrees of freedom for the final stages of a berthing maneuver. The supervisor switches automatically between these two modes. The methods are validated on board the German research vessel DENEB in the port of Rostock.

Design and Analysis of Decentralized Dynamic Sliding Mode Controller for TITO Process

In this paper, a decentralized dynamic sliding mode control (DySMC) strategy is applied to a multivariable level control system. The time derivative of the control input of the DySMC is considered a new control variable for an augmented system which is composed of the original system and the integrator. This DySMC can transfer discontinuous terms to the first-order derivative of the control input and effectively reduce the chattering. The interactions between input/output variables are a common phenomenon and a challenging task in the design of multi-loop controllers for interacting multivariable processes. For reducing the interaction among variables, ideal decouplers are used. Independent diagonal controllers are designed for each decoupled subsystem, which is reduced to the first-order plus dead-time (FOPDT) model. A numerical simulation test has been carried out on a reactor system of the Industrial-Scale Polymerization (ISP). Experimental tests are performed to check the efficacy of the proposed controller using a laboratory-level coupled tank system. A comparison of the proposed approach and sliding mode controller (SMC) is presented. Simulation and experiment results show that the DySMC approach reduces the chattering, and compensates for the effect of the external disturbances, and parametric uncertainties.

Cooperative Control of Interconnected Air Suspension Based on Energy Consumption Optimization

In this study, a cooperative control method based on model predictive control and multiagent theory is proposed to control an interconnected air suspension system with three controllable structures of interconnection mode, damping, and vehicle height. The model predictive controller is constructed based on a discrete-time state-space model. The optimal interval for suspension force is obtained through solving cost functions while satisfying a set of constraints on controlled variables and thereby reducing the coupling complexity of a multivariable control system. Deliberative agents are involved in building cost functions of interconnection mode, vehicle height adjustment, and damping force, and the energy consumption control strategy is established to realize suspension force distribution with low energy consumption. Finally, the test results show that the proposed control method can significantly improve vehicle ride comfort and restrain rollover on the premise of ensuring energy efficiency. Compared with traditional control, the peak value of the sprung mass acceleration speed decreases by 70% and the peak value of the unsprung mass acceleration speed decreases by 75% under straight-driving condition. The roll angle decreases by 40% under the steering condition. As for the traditional control, they are skyhook, imitation skyhook, and PID-PWM control strategies.

The Impact of Fractional Order Control on Multivariable Systems

In this work a fractional order filter proportional integer (FOF-PI) controller is proposed for the control of multivariable system which is a distillation column model. In addition to the design of fractional controller, a comparison between integer controller employing the most used method the biggest log modulus (BLT) and the internal model control (IMC) with the fractional method. The purpose of this comparison is to improve the quality control and show the superiority and the increase of flexibility by the additional fractional parameter of the fractional control. An analyzed study between performance indices of the three methods as the overshoot, settling time, integral absolute error (IAE) and rise time is exhibited. The simulation graphs of the outputs provided by the three used controllers are presented to confirm the results and show the improvement in the control of multivariable system domain by the fractional method.

Multivariable run-to-run control of thermal atomic layer etching of aluminum oxide thin films

With the growing scarcity of semiconducting devices stemming from volatile prices, shortened supplies, and increased demand that are attributed to the Covid-19 pandemic, manufacturers are looking for efficient ways to facilitate the production of nanoscale semiconducting devices. Thermal atomic layer etching (ALE) is a promising method that can overcome the obstacles encountered during the production of semiconducting devices via conventional approaches by delivering precise dosages of reagent to etch monolayers of substrate surface material in a cyclic operation. However, thermal ALE has not been extensively studied and characterized to become fully embraced by the semiconductor manufacturing industry. Recent work by our group has led to the development of a multiscale computational fluid dynamics modeling framework that was used to optimally design a desirable reactor configuration and operating conditions for the thermal ALE process. Despite this progress, additional research is needed to ensure that the film quality is maintained in the presence of operational disturbances. Therefore, the present work is focused on the development of a multivariable run-to-run (R2R) control system to mitigate the impact of critical operational disturbances. It is demonstrated that the developed multivariable R2R control system can efficiently overcome the negative effects of unknown disturbances that may impact film uniformity by regulating input variables within a minimal number of batch runs.

Robust Control and Co-simulation of a Multivariable Nonlinear Liquid Level Control System

Robust Control and Co-simulation of a Multivariable Nonlinear Liquid Level Control System

Improved multivariable reasoning control method for carbon content control of argon–oxygen refining ferrochrome

In order to control the end-point carbon content in the process of argon–oxygen refining ferrochromium alloys, according to the mechanism model of the oxygen supply rate and carbon content variation, the mechanism model of the argon supply rate and carbon content variation, and the mechanism model of the supply rate of the two gases and molten iron temperature variation, this paper proposes an improved multivariable inference control system and uses expert control to realize the automatic adjustment of the filter time constant in the multivariable reasoning controller. The simulation results show that this method can ensure the stability of the control system without errors and maintain the furnace temperature below the maximum withstanding temperature, further improving the dynamic response of the system and effectively shortening the smelting time of the entire argon–oxygen refining ferrochromium alloy. It is beneficial for improving smelting efficiency and prolonging furnace service.

Event-Triggered Adaptive Output Feedback Control of Multivariable Systems With Nonsmooth Actuator Nonlinearities

In this article, the event-triggered adaptive output feedback control of multivariable system under nonsmooth actuator nonlinearities, including deadzone, backlash, and hysteresis is investigated. The nonsmooth actuator nonlinearities are handled with a unified framework by modeling them with a time-varying disturbance and a control input. With an event-triggered mechanism and an one-parameter estimation approach, the communication consumption for the control of multivariable system is significantly reduced. It is shown that all signals in the closed loop system are bounded. The Zeno behavior is also avoided. The simulation results demonstrate the effectiveness of the control scheme.

Local input‐to‐state stability analysis on compact set for disturbance observer‐based uncertain multivariable nonlinear control systems

AbstractThis article proposes a local input‐to‐state stability (LISS) analysis as a practical stability analysis approach. In existing LISS analysis approaches, a region including a state trajectory is not specified, and the decrement of a Lyapunov function must be guaranteed in the entire domain of the system state. This reduces the advantage of LISS by limiting the state region, and limits the class of systems for which stability can be guaranteed. To expand the class of systems for which stability can be guaranteed, the LISS Lyapunov function on a compact set (LISS LF CS) is proposed to guarantee LISS. By using the LISS LF CS, the region containing the state trajectory was revealed and the LISS condition was relaxed. In addition, the convergence rate and steady state error bound were determined for systems with LISS LF CS. The input‐to‐state stability (ISS) and LISS were analyzed for a multivariable disturbance observer‐based control system using the ISS and LISS LFs, respectively. The advantages of the proposed LISS analysis are demonstrated by comparing the ISS and LISS conditions. The analytical results were verified by conducting numerical simulations.

Filtering‐based recursive least squares estimation approaches for multivariate equation‐error systems by using the multiinnovation theory

SummaryThis article researches the filtering‐based parameter estimation issues for a class of multivariate control systems with colored noise. A filtering‐based recursive generalized extended least squares algorithm is derived, in which the data filtering technique is used for transforming the original system into two subidentification systems and the least squares principle is used for estimating parameters of these two subsystems. Furthermore, in order to improve the parameter estimation accuracy, the multiinnovation theory is added for deducing a filtering‐based multiinnovation recursive generalized extended least squares algorithm. The numerical example confirms that these two proposed algorithms are effective.

Development of Resilient Control Systems for Technological Plants

The aims of the research are increasing resiliency of industrial process control systems, the de-velopment of methods of creating resilient industrial process control systems and creating a resil-ient control system of the distillation column for the production of food alcohol. The set of ob-jectives were achieved without the use of hardware backup, but using the developed algorithms which were based on the use of the model of dynamics of technological plants in the software of the control system and modern theory of multivariable automatic control systems. The opti-mal linear-quadratic controller with disturbances model and a state observer was used as a full controller. The most important result was improvement of the survivability of industrial process control systems using the developed algorithm. Also, the resilient distillation column control sys-tem was developed. For the further researches significant results are formulas which allow de-fining new mode values of controls in a distillation column at failure event of corresponding control output channels and formulas of logic algebra for a choice of optimum configuration of control system of a distillation column of food spirit industry. The basis of the developed tech-nique was reconfiguration of the control system with inclusion, instead of the failed, additional devices, which were not being used in a current configuration, but were carried out the similar function taking into account dynamics coupling of a technological plant. The significance of these results is that they can be applied to the development of cyber-production systems that do not require permanent maintenance by personnel.

Design and Comparison of Plasma H∞ Loop Shaping and RGA-H∞ Double Decoupling Multivariable Cascade Magnetic Control Systems for a Spherical Tokamak

The article aims to present an approach to design and compare cascade Hinf loop shaping and essentially new cascade RGA-Hinf double decoupling magnetic control systems for a multivariable dynamical plant, specifically plasma in a vertically elongated tokamak. Identification of the present control closed-loops containing a plasma linear model of a relatively high order for the spherical Globus-M tokamak (Ioffe Institute, St Petersburg, Russia) to derive a low order linear model (without the application of reduction algorithms) as a plant under control is undertaken. A robust H¥ loop shaping method was applied to the identified model to design a plasma position, current, and shape (6 gaps between the first wall and plasma separatrix) multivariable controller. A structural analysis was done to get the most effective structure of the square plant with the 3rd gap eliminated in the feedback and a separate loop for the plasma current control. The methodology of the relative gain array (RGA) was applied to this structure to choose the proper correspondences between inputs and outputs (pairing), which brought the plant model closer to a decoupling plant (first decoupling in the open plant model). Further, the Hinf adjustment of the control system with the pairing plant and an additional feedback decoupling matrix (second decoupling of the plant model in the feedback) and PI controllers in the feedback gave increased control system accuracy while tracking references. Comparison of the two control systems designed has shown that double decoupling gives higher performance accuracy and a less robust stability margin, while the robust loop shaping method allows the stability margin to be increased but gave less accurate control of the gaps.

Identification, Uncertain Modelling, and Robust Control of Embedded Systems

This paper presents a methodology embodying identification procedures, uncertain modeling, and robust control design of embedded multivariable control systems. Concerning the identification, this methodology involved the determination of probabilistic uncertainty bounds for multivariable plants based on the black box or gray box identification. The bounds obtained were used in the derivation of an uncertain model in the form of upper Linear Fractional Transformation (LFT). This model was used in the robust control design implementing μ-synthesis. The problems arising on the different design stages were illustrated by an example presenting the embedded robust control of a two-input two-output analog model. The plant was identified by using black box and gray box identification methods that produced the necessary information to develop the corresponding uncertainty models. Two discrete-time robust controllers relevant to the two types of identification were designed and embedded in the physical system. Simulation results for the embedded closed-loop system and experimental results obtained by using the robust controllers were compared.

Robust Adaptive Control of a Quadruple Tank Process with Sliding Mode and Pole Placement Control Strategies

Many industrial processes have challenging issues such as complex nonlinear nature, high sensitivity to disturbances and existence of parametric uncertainties. A Quadruple Tank Process (QTP) is used in the laboratory as a scaled representation of many industrial processes involving liquid level control problems. Conventional controllers are relatively slow in tracking the reference inputs and in reacting to disturbances, and they tend to lack the ability in dealing with parametric changes in the QTP. The aim of this paper is to design and test an Adaptive Pole Placement Controller (APPC) and a robust Adaptive Sliding Mode Controller (ASMC) with the purpose of high-efficacy control of a minimum phase QTP. The controllers are tested via simulations and performance indices resulting from the simulation of these controllers are compared with a PID controller in terms of the three cases of robustness to set point variations, rejection of disturbance inputs, and robustness to parametric uncertainties. Simulation results reveal that the proposed adaptive control configurations perform better than the PID controller with lower performance indices and faster settling times due to the paramater estimation method used in the design processes. ASMC outperforms APPC in different variations of inputs and in regulation performances due to the invariant nature of the Sliding Mode Control (SMC). The results show that a decentralized ASMC can be used to improve the rapidity and robustness of many multivariable industrial process control systems.

Disturbance observer based dead‐beat control of multi‐input systems with unknown disturbances and bounded inputs using discrete‐time higher order sliding mode

AbstractThis article proposes a new robust dead‐beat controller for multivariable systems using multirate sampled data. Applying a discrete‐time higher order sliding mode control approach, the proposed dead‐beat controller design uses the state‐space nominal model (model without disturbances) of the system and its controllability indices to compute the state feedback matrix. The obtained control annihilates the system state in a minimal number of sampling periods. For example, a heuristic procedure for selecting a sampling time is considered in order to keep maximal amplitudes of control inputs within the allowable limits. Since the dead‐beat control has poor robustness, a new discrete‐time supertwisting disturbance observer is used to suppressed disturbance effects. Stability analysis of the proposed observer has shown that it is suitable for Lipschitz type of disturbances. The sampling period of the disturbance observer is generally smaller than the control sampling period. Properties of the proposed control system are demonstrated in simulation examples.

Research on the Temperature Control System of 6KA Neodymium Oxide Electrolysis Furnace with BAS_PID Algorithm

In order to solve the obvious temperature fluctuations in the cell during the neodymium oxide electrolysis process, the traditional PID control algorithm has a large lag, the timeliness of the multi-variable electrolysis temperature control system is poor, and the manual parameter adjustment is difficult, the beetle PID automatic temperature control system is proposed. Through the control of the key variable cathode current density, speed up the system to adjust the output speed; use the orthogonal temperature measurement method to replace the traditional single point temperature measurement, and use the domain temperature to represent the point temperature to solve the problem of large temperature measurement errors. This algorithm model is based on MATLAB2017 platform for modeling simulation and experimental research. Compared with traditional PID, this method has better adaptive ability and robust performance. The maximum deviation between the actual electrolysis temperature and the set target temperature is 45°C, and the overshoot is 3.3 %, to meet the process index requirements in the actual production process, and provide a reference case for the improvement of neodymium oxide electrolysis process.

A Multivariable Twin-Rotor System Control Design

This paper presents the design of a Multi-Input Multi-Output (MIMO) PID controller for a twin-rotor MIMO system. A multivariable control system consisting of two loops is designed for a non-linear system with two inputs and two outputs. The designed controllers have been tested on a simulated model with different possibilities and real-time results were taken. The designed PID controller efficiently controls the loops of the system and does not suffer from any process interactions. The results indicate that the performance of the PID controllers is excellent and both the transient and the steady-state enactment are adequate. The yaw and pitch rotor’s real-time responses are almost the same as the desired ones.

MISO Nonlinear Gauss-Hammerstein Model Identification of Ultrasonic Motor

A novel two-input nonlinear Hammerstein model of ultrasonic motor is proposed to provide the basis for the design and analysis of motor’s multivariable control system. The static nonlinear part of the model is designed as Gauss function to describe the nonlinear characteristics of ultrasonic motor more accurately. Differential evolution algorithm is used to identify the model parameters, and the algorithm is improved to ensure the correctness and validity of the modeling process. The debugging method of optimization algorithm parameter value is also proposed to ensure the robustness of the algorithm. The comparison between the experimental data and the calculated results of the model indicates that the established model has higher precision and the modeling method is effective.

РАЗРАБОТКА ДЕМОНСТРАЦИОННОГО МАКЕТА МНОГОСВЯЗНОЙ СИСТЕМЫ РЕГУЛИРОВАНИЯ МНОГОПОТОЧНОЙ ПЕЧИ

The article contains a description of the developed mathematical models of a control object (a multi-flow furnace of an oil refinery), a MATLAB application that demonstrates the simulation process, as well as a multivariable automatic control system. The block diagrams of the model of the control system of the multi-stream furnace are presented. The purpose of this work is to develop a demonstration model of a multi-connected control system for a multi-flow furnace of an oil refinery. A description of the created software package based on the MATLAB interactive environment for scientific and engineering calculations with the Simulink and AppDesigner extension packages is presented, which contains tools for modeling the processes of the selected object under the conditions of disturbances acting on the object, as well as allowing visualization of the results obtained and plotting time characteristics.