Order Reference Model Research Articles

State Space Model Reference Adaptive Control for a Class of Second-Degree Fractional Order Systems with Different Eigenvalues

This study proposes an adaptive control synthesis for a class of second-degree fractional order systems with different eigenvalues in the state-space domain. The proposed fractional order adaptive controller is a generalization of the MRAC controller for the class of scalar fractional order systems. In order to control the fractional order plant, an adaptive state space feedback controller is applied based on the error between the system output and a chosen reference model using a fractional adaptation law to make the fractional order plant track the fractional order reference model. We show that the resulting adaptive regulator is able to stabilize the fractional order second degree system with a satisfying performance. A simulation example illustrating these performance properties is provided along with a comparison with a fractional order sliding mode control (FOSMC) to demonstrate the superiority of the proposed control scheme.

Error-Based Switched Fractional Order Model Reference Adaptive Control for MIMO Linear Time Invariant Systems

This paper presents the design and analysis of Switched Fractional Order Model Reference Adaptive Controllers (SFOMRAC) for Multiple Input Multiple Output (MIMO) linear systems with unknown parameters. The proposed controller uses adaptive laws whose derivation order switches between a fractional order and the integer order, according to a certain level of control error. The switching aims to use fractional orders when the control error is larger to improve transient response and system performance during large disturbed states, and to obtain smoother control signals, leading to a better control energy usage. Then, it switches to the integer order when the control error is smaller to improve steady state. Boundedness of all the signals in the scheme is analytically proved, as well as convergence of the control error to zero. Moreover, these properties are extended to the case when system states are affected by a bounded non-parametric disturbance. Simulation studies are carried out using different representative plants to be controlled, showing that fractional orders and switching error levels can be found in most of the cases, such as when SFOMRAC achieves a better balance among control energy and system performance than the non-switched equivalent strategies.

Bi-fractional-order reference model parameters-based control system design

It is known that analytical manipulation of the time-domain representation of fractional order transfer function is, hitherto, a challenging task. In this study, a controller design methodology based on the direct synthesis design method is proposed using bi-fractional order transfer function as a reference model and certain time-domain criteria. First, an analysis examines the effects of bi-fractional order transfer function parameters, that is, commensurate fractional order, damping ratio and natural frequency, on the system time-domain criteria. This examination has allowed us to set up a relation between damping ratio and commensurate fractional order. Next, a polynomial function fitting is established in order to express the damping ratio in terms of this commensurate order. Bi-fractional-order reference model is regenerated using the above-mentioned relationship. Furthermore, a control design algorithm that utilizes the newly derived bi-fractional order reference model is developed by considering control signal limitations. The proposed fractional order control design method is then compared with globally optimized fractional order proportional-integral-derivative (PID) controllers under the same circumstances and performance index. Finally, the implementation of the proposed controller design algorithm is done on a real-time active suspension system. The results are very satisfactory and incoherent with the simulations.

Accurate detection of hidden material changes as fictitious heat sources

In this article we present a numerical method for the estimation of hidden material changes, interpreted as fictitious source terms. The method adapts the parameters of its reference model in order to cancel the estimated fictitious source terms and thus it indirectly estimates the hidden material changes. The novelty of this method is triple: first, a parsimonious minimization strategy that effectively avoids local minima, by using the maximum principle as a barrier against falling into; second, an error indicator based on estimates of fictitious heat sources, instead of the temperatures-prediction-error, because it is smeared by diffusion; third, the adaptation of model parameters is computed without the problematic matrix inversion which would arise in Newton-based procedures. As a particular example application, we show that, in thermographic experiments for hidden corrosion detection, the gradient of the temperatures-prediction-error, often used in the literature, is quite inefficient, while the fictitious-source-term estimation behaves intrinsically better. Its accuracy and moderate computational demand are highlighted in the numerical tests. Moreover, this approach is applicable to general hidden material change problems.

Performance comparison of discrete-time robust adaptive controllers for grid-tied power converters under unbalanced grids

Renewable energy generation systems largely use grid-tied power converters with LCL filters. A well-known issue in this kind of system is the resonance of the LCL filter, whose frequency is straightforwardly affected by grid condition. Variations on grid impedance tends to make the controller performance poor and until turn the closed-loop unstable. Therefore, some controllers are designed for specific operation ranges to ensure performance and global stability. However, a deep study of Model Reference Adaptive-based Controllers for this kind of issue was not conducted yet. The aim of this paper is to fit this research gap. Thus, this paper presents a performance comparison of feasible discrete-time robust adaptive controllers, based on reduced order reference model, for grid-tied power converters with LCL filter under unbalanced grid conditions, providing an assessment of the benefits and drawbacks of each considered control strategy. The evaluated control laws are: Robust Model Reference Adaptive Controller, Robust Model Reference-based Adaptive Super-Twisting Sliding Mode Controller, Robust Adaptive One Sample Ahead Preview Controller, and Robust Adaptive Proportional-Integral Controller. Through performance comparison, it can be defined what controller is more adequate in face of grid condition, taking into consideration grid-injected currents quality and design complexity of controller. Experimental results of grid-injected current control of a grid-tied 5.8 kW Voltage-Source Inverter with LCL filter considering relevant grid voltage unbalance are presented to corroborate the controllers’ performance and discuss their reference tracking response, robustness to the parametric variation, exogenous disturbance rejection, parameters adaptability, and global stability. In evaluated scenarios, Robust Adaptive Proportional-Integral controller presented slower regulation dynamics between compared adaptive structures, but reduced tracking error, as well as lower total harmonics distortion, while Robust Model Reference-based Adaptive Super-Twisting Sliding Mode Controller has the smaller overshoot in the initial transient regime, as well as the shorter transient regime.

Record Management Practices and Service Delivery in Devolved System of Governance of Mavoko Sub-County, Machakos County Kenya

The purpose of this paper was to assess records management practices and service delivery in Mavoko sub-county, Machakos County. Records management practices are widely acknowledged as important resources for social, economic development. Due to resource constraints, records management practices has been taken rather slowly but it is needed for the business running and effective service delivery. The aim of the study was to assess records management practices and services delivery effects in devolved system of governance of Mavoko sub-county, Machakos County Kenya. The specific objectives of the study were to assess records management practices undertaken on service delivery in Mavoko Sub- County, Machakos County. Objective two, was to analyse the effects of records management practices on service delivery in Mavoko Sub-County. Third objective was to investigate the challenges experienced in managing records in Mavoko Sub-County and the fourth objective was to propose strategies to improve service delivery by use of effective records management practices at Mavoko sub county, Machakos County. Knowledge of records management practices is the research gap of the study. The study has contributed a lot towards the importance of records management practices in Mavoko Sub-County. The study used a combination of theories such as records life cycle theory, information governance reference model and systems theory in order to inform the study. Both descriptive and survey design method have been used since the research study involved description and survey. Questionnaires and survey method have been applied to collect data that a quantitative research design was adopted to address the research problem. The target population was 38 and a sample of 38 respondents comprising 7 respondents from Deputy Commissioner’s office in Mavoko Sub-County, 7 respondents from Mavoko municipal office and 24 respondents representing staff working with records and administrators in the six county wards reached by using census. Quantitative data was collected through questionnaires and survey of records in Mavoko Sub-County where a questionnaire was used to collect data from both staff and users. Questionnaires were used to collect data by the researcher because they are simple and easy to understand when analyzing. The researcher used simple random sampling method that included everyone who had been chosen at random by use of census. Using simple random sampling enabled the researcher get enough and accurate information that led to better recommendation. Quantitative data was analyzed using statistical package for social science (SPSS) and presented by means of tables, figures, graphs and pie charts. The use of quantitative approach has made the research more understandable in solving the research problem. The result of the study was beneficial in social, economic development in Mavoko Sub-County and adjacent areas. The key findings of the study indicated that records management practices are not fully practiced in Mavoko Sub-County due to lack of training of staff in the field of records management. Records management practices are useful in all organizations in Mavoko Sub-County since they ease service delivery. The recommendations of the study are that training of staff on records management and on other related field was needed highly to improve service delivery. Also to minimize work failure, there is need to equip adequate facilities and good safety for records keeping and records management policies are necessary when handling record management practices. Since this was the first time the research study was conducted in Mavoko Sub-County, the researcher recommended another further study to be conducted in another sub county in Machakos County since change of technology may bring implications in records management practices. The researcher also recommended the application of information technology on records management practices for future study in the county.

Fractional order adaptive MRAC controller design for high-accuracy position control of an industrial robot arm

Most of conventional feedback controllers become inefficient in hard industrial environments like in steel industry, because of uncertainties in the plant model, or process dynamics variation due to nonlinear actuators, and changes in the character of the disturbances. This paper proposes an adaptive control design based on fractional order model reference adaptive control (FOMRAC) strategy in order to deal with an uncertain horizontal positioning control of an unloading machine in a rotary hearth furnace for hot rolling operation. The proposed FOMRAC scheme uses the MIT rule as an adaptive mechanism with two main modifications comparatively to the conventional MRAC: the reference model is an adequate fractional order system and the parameter adjustment rule contains a fractional order integrator. Stability analysis of the proposed control scheme is performed using the Lyapunov stability theorem. Numerical simulations are presented to show the effectiveness of the proposed fractional adaptive schemes applied to an industrial robot arm loading round steel blocks from inside a rotary hearth furnace. After comparison with the conventional MRAC, it is shown that the performances of FOMRAC are superior to classical control schemes.

High-Tracking-Precision Sensorless Control of PMSM System Based on Fractional Order Model Reference Adaptation

In order to solve parameter fluctuations and disturbances, a novel fractional order model reference adaptive speed observer that estimates the rotor position and the angular velocity from the stator currents is proposed for sensorless control of permanent-magnet synchronous motors (PMSM). Firstly, a novel fractional order model reference adaptive controller (FOMRAC) for adaptive identification is designed to achieve fast response and high precise identification of load torque in the full speed range when the motor is running at variable-speed or variable-load. Additionally, an appropriate adjustable matrix P is chosen to make the convergence of the adaptive law meet the requirements. Next, an improved model reference adaptive observer (MRAO) is proposed to suppress the serious chattering and compensate rotor position error, which can stabilize the system. The validity of the proposed fractional order model reference adaptive sensorless control strategy for PMSM is demonstrated with simulations.

Switched Fractional Order Model Reference Adaptive Control for First Order Plants: A Simulation-Based Study

Abstract This paper presents the results and analysis of an exhaustive simulation study where switched fractional order model reference adaptive control (SFOMRAC) is used for first order plants, along with the analytical proof of boundedness and convergence of the scheme. The analysis is focused on the controlled system behavior through the integral of the time-weighted squared control error (ITSE) and on the control energy through the integral of the squared control signal (ISI). Controller parameters such as fractional order, adaptive gain, and switching time are varied along the simulation studies, as well as plant parameters and reference models. The results show that SFOMRAC controllers can be found for every plant and reference model used such that both system behavior and control energy can be improved, compared to equivalent nonswitched fractional order and integer order control strategies.

Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

AbstractThe main idea of the current paper consists in introducing the fractional order calculus in a control system. To control the system, an adaptive control technique with reference model is used. The fractional order models for the plant and reference model are obtained. To achieve the performances imposed by the fractional order reference model, a fractional order adaptive control law is proposed, which is a combination of two methods (MIT and Lyapunov stability). The original contribution in this paper is the use of fractional order calculus in the combined MIT and Lyapunov stability method and showing the dynamic behavior of the system. Several simulations are used to emphasize the effectiveness and benefits of the proposed method.

Efficient Fractional Order Reference Model of Adaptive Controller Design for Multi-input Multi-output Thermal System

The diverse control techniques have been combined with fractional calculus to enhance the control system performance. This paper presents an efficient fractional-order model reference adaptive controller (FOMRAC) design, which aims to demonstrate the solution for temperature reference tracking and cross-coupling rejection in the multi-input multi-output thermal system as well as cognizing of power consumption saving constraints. The mathematical modeling, nonlinear dynamic characteristic details, and system identification of the thermal system are described while the fractional-order controller combined with a model reference adaptive control (FOMRAC) based on MIT rule is developed so that to create the nonlinear adaptive mechanism which enables the excellent performance to control the multi-input multi-output thermal system. Likewise, a decoupling compensator is constructed to remunerate the effect of the cross-coupling interaction. The validation of the proposed control scheme is performed through the Matlab simulation and the experiment on the multi-input multi-output thermal system. The results illustrated the FOMRAC technique in which the controller's adjustable parameters can provide efficiency stability and performance to minimize the settling time and percent overshoot of the control system response. Besides, the analysis of the power consumption in the control system is addressed to reinforce the useful ability of the proposed method compared with the integral-order model reference adaptive controller (IOMRAC) and the traditional PID controller. The results revealed that the proposed FOMRAC technique exhibited much better than other methods because of the effective optimization of adaptive gain mechanism and fractional-order operators.

Model Reference Robust Adaptive Control of Control Element Drive Mechanism in a Nuclear Power Plant

In the nuclear power plant, the control element drive mechanism (CEDM: A type of solenoid actuators) is used to insert nuclear fuel rods into the core to regulate the neutron absorption within the reactor. The control environment is full of uncertainty and disturbance, and the CEDM is supposed to cope with the varying conditions in the reactor. In this paper, a model reference adaptive control (MRAC) of CEDM is investigated. The existing MRAC scheme that assumes the known system order is first extended to the system with unknown high-frequency gain and output disturbance, and then the extended version is applied to the control problem of CEDM. A simplified relationship between the input voltage and the magnetic force of the CEDM is established based on Kirchhoff’s voltage law and the magnetic co-energy theory. The system order of the plant is identified by the prediction error method using experimental input/output data: A 3rd order linear model with three poles and two zeros turns out to be the best model for control. Based on this model, a 3rd order reference model is selected, and an adaptive control law with s-modified adaptation laws is designed under output disturbance. The performance of the proposed control law is compared with a well-tuned PI controller and the conventional MRAC. The superiority of the proposed method is also demonstrated in an abnormal condition. Simulation and experiment results are provided.

Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants

In the literature, many applications of Digital Twin methodologies in the manufacturing, construction and oil and gas sectors have been proposed, but there is still no reference model specifically developed for risk control and prevention. In this context, this work develops a Digital Twin reference model in order to define conceptual guidelines to support the implementation of Digital Twin for risk prediction and prevention. The reference model proposed in this paper is made up of four main layers (Process industry physical space, Communication system, Digital Twin and User space), while the implementation steps of the reference model have been divided into five phases (Development of the risk assessment plan, Development of the communication and control system, Development of Digital Twin tools, Tools integration in a Digital Twin perspective and models and Platform validation). During the design and implementation phases of a Digital Twin, different criticalities must be taken into consideration concerning the need for deterministic transactions, a large number of pervasive devices, and standardization issues. Practical implications of the proposed reference model regard the possibility to detect, identify and develop corrective actions that can affect the safety of operators, the reduction of maintenance and operating costs, and more general improvements of the company business by intervening both in strictly technological and organizational terms.

Routing Efficiency of Infrastructureless Networks: A Comparative Analysis

This paper presents a novel approach to analyse the traffic efficiency of infrastructureless networks. Wireless communication is rapidly moving towards more infrastructureless routing schemes, where the devices encounter frequent topology changes and communicate with each other anonymously and sporadically. Nodes do not have the opportunity to choose an optimum routing path, they do rather obtain a valid routing path on the fly during the data exchange by cooperating with the nearest neighbours. Packets emanated from an infrastructureless node are disseminated through each node found in the vicinity. This produces a vast number of packet duplicates within the entire communication environment, causing the problem of increased congestion, increased packet delay, more packet drops, and undesirable energy consumption compared to the infrastructured networks. Data exchange and packet routing operations in large networks are highly stochastic. Thus, the performance analysis of routing operations is modeled as a stochastic queueing system, where the input and output traffics and throughput operations of routing systems are precisely formulated in the form of stochastic processes. A hypothetical routing algorithm is also defined here as a reference model in order to perform a comparative analysis of the infrastructureless routing scheme.

Switched Fractional Order Model Reference Adaptive Control for Unknown Linear Time Invariant Systems

Abstract This paper presents a model reference adaptive controller for linear time invariant systems with unknown parameters. The adaptive laws used to estimate the controller parameters are based on fractional differential equations, whose orders are switched among a fractional value in the interval (0,1) and 1 at certain time instants. Boundedness of the signals in the resulting controlled system is proved using recent results. A simulation study is provided for a second order system to show how the proposed control strategy can improve the behavior and decrease the control energy used, compared to the classic model reference adaptive controllers and fractional order model reference adaptive controllers with non-switched adaptive laws.

A Numerical Approach for Buildings Reduced Thermal Model Parameters Evaluation

This paper introduces an efficient PSO-based optimization method to identify parametric values of buildings reduced thermal RC network models. A high order reference model representing energy flow through building envelope is developed based on Crank-Nicolson finite difference method. Thermal network models performance with random resistance and capacitance values are compared with a reference model then PSO is used for parameters identification to match the actual reference model thermal dynamics. The accuracy and computational cost of these optimized models are validated against reference model for different construction classes. The proposed methodology presents an effective way to develop a reliable thermal network model representing realistic thermal dynamics in building that can be used to improve efficiency of controlling techniques.

Genetic model reference adaptive control of shell heavy oil fractionator

Fractionators are characterised by high nonlinear dynamic behaviour, strong loop interactions and model uncertainties. Relative gain array (RGA) was used to determine the level of loop interaction. Dynamic decoupler was used to remove the interactions which were obtained using feed-forward design technique. A feedback control system is designed for the dynamic decoupled plant using Ziegler-Nichols tuned proportional integral (PI) controller. A genetic model reference adaptive controller (GMRAC) is designed to control the fractionator using a second order reference model and adaptation mechanism based on genetic algorithm (GA). Genetic algorithm uses real-coded data generation for optimisation. Comparison is made with the PI controller. Performance indices were based on settling time, rise time and overshoot.

Genetic model reference adaptive control of shell heavy oil fractionator

Fractionators are characterised by high nonlinear dynamic behaviour, strong loop interactions and model uncertainties. Relative gain array (RGA) was used to determine the level of loop interaction. Dynamic decoupler was used to remove the interactions which were obtained using feed-forward design technique. A feedback control system is designed for the dynamic decoupled plant using Ziegler-Nichols tuned proportional integral (PI) controller. A genetic model reference adaptive controller (GMRAC) is designed to control the fractionator using a second order reference model and adaptation mechanism based on genetic algorithm (GA). Genetic algorithm uses real-coded data generation for optimisation. Comparison is made with the PI controller. Performance indices were based on settling time, rise time and overshoot.

Adaptive Cruise Control System for an Electric Vehicle Using a Fractional Order Model Reference Adaptive Strategy

Abstract With the depletion of fossil fuels, and the increased environment concerns, there is more and more interest in Electric Vehicles (EVs) from automobile manufacturer and governments in the entire world. In this paper, a fractional order model reference adaptive control (FOMRAC) system is designed for the cruise control of a DC motor-driven electric vehicle. The vehicles powertrain model is exposed and the control design is developed and detailed. The major contribution in this work is to use fractional order reference adaptive controllers for both two layer control loops: regulating the current for the inner loop and the desired speed tracking for the outer. Numerical simulations illustrate the performance improvement using the proposed control strategy.

Fractional-order model reference adaptive control of a multi-source renewable energy system with coupled DC/DC converters power compensation

We propose a supervision strategy based on a fractional order model reference adaptive control (FO-MRAC) design for the control of electrical energy transfers in a multi-source renewable energy system. We consider a two sources system (photo-voltaic and lead-acid battery bank) with a specific zero voltage switch full-bridge isolated buck DC/DC power converter and the load which is supposed to be resistive. The global energy system involving coupled DC/DC converters on a DC bus is accurately modelized in the state space domain. Then, a fractional order MRAC control law is designed in order to stabilize the system’s current and voltage. We show by means of numerical simulation tests that the proposed FO-MRAC control is very efficient and robust even in presence of renewable sources fluctuations and load variations.