Proposed Control Procedure Research Articles

A Cooperative Multi-Agent Q-Learning Control Framework for Real-Time Energy Management in Energy Communities

Residential and commercial buildings are responsible for 35% of the EU energy-related greenhouse gas (GHG) emissions. Reducing their emissions is crucial for meeting the challenging EU objective of the agenda for becoming a net-zero continent by 2050. The diffusion and integration of distributed renewable energy sources (RESs) and energy storage systems (ESSs), as well as the creation of energy communities (ECs), have proven to be crucial aspects in reducing GHG emissions. In this context, this article proposes a multi-agent AI-based control framework to solve the EC’s energy management problem in the presence of distributed RESs and ESSs as well as considering a shared ESS. The objectives of the proposed control framework are to satisfy the EC members’ load demand to maximize self-consumption and to manage ESSs charging and discharging processes, to enforce cooperative behavior among the EC members by adopting fair and personalized strategies and to maximize EC members’ profits. The proposed control procedure is based on three sequential stages, each solved by a dedicated local RL agent exploiting the Q-Learning algorithm. To reduce the computational complexity of the proposed approach, specifically defined state aggregation criteria were defined to map the RL agents’ continuous state spaces into discrete state spaces of limited dimensions. During the training phase, the EC members’ profiles and the ESSs’ and RESs’ characteristics were randomly changed to allow the RL agents to learn the correct policy to follow in any given scenario. Simulations proved the effectiveness of the proposed approach for different costumers’ load demand profiles and different EC configurations. Indeed, the trained RL agents proved to be able to satisfy the EC members’ load demands to maximize self-consumption, to correctly use the distributed and shared ESSs, to charge them according to respective personalized criteria and to sell the energy surplus, prioritizing sales to the EC. The proposed control framework also proved to be a useful tool for understanding EC performance in different configurations and, thus, for properly dimensioning the EC elements.

Stabilization control of rotary inverted pendulum using a novel EKF-based fuzzy adaptive sliding-mode controller: design and experimental validation

This article methodically develops an improved self-regulating fuzzy-adaptive Sliding Mode Controller (SMC) that strengthens the disturbance compensation capacity of the nonlinear rotary pendulum systems while effectively attenuating the chattering content and curbing the control energy consumption. The article contributes to augmenting the SMC with online adaptation tools to achieve the said objectives. It employs the conventional Gao’s power-rate reaching law as the baseline. The scaling gain and the power rate of the said reaching law are adaptively modulated via a pre-calibrated two-input state-error-driven fuzzy nonlinear function. Additionally, the sign function in the law is also replaced with an odd-symmetric nonlinear fuzzy function to address the hard limits imposed by the former. Finally, the membership functions of the fuzzy function are self-regulated using the Extended-Kalman-Filter to improve the compensator’s adaptability in handling the system’s rapidly changing control requirements under exogenous disturbances. The aforementioned propositions are verified by performing customized and reliable hardware-in-loop experiments on the Quanser single-link rotary pendulum platform. As compared to baseline SMC law, the proposed control procedure contributes a ∼45.2%, ∼48.5%, and ∼34.8% reduction in position-regulation errors, control energy consumption, and peak overshoots, respectively. The experimental assessment validates the proposed control system’s enhanced robustness and chattering-suppression capability.

Adaptive optimal control of under-actuated robotic systems using a self-regulating nonlinear weight-adjustment scheme: Formulation and experimental verification.

This paper formulates an innovative model-free self-organizing weight adaptation that strengthens the robustness of a Linear Quadratic Regulator (LQR) for inverted pendulum-like mechatronic systems against perturbations and parametric uncertainties. The proposed control procedure is devised by using an online adaptation law to dynamically adjust the state weighting factors of LQR's quadratic performance index via pre-calibrated state-error-dependent hyperbolic secant functions (HSFs). The updated state-weighting factors re-compute the optimal control problem to modify the state-compensator gains online. The novelty of the proposed article lies in adaptively adjusting the variation rates of the said HSFs via an auxiliary model-free online self-regulation law that uses dissipative and anti-dissipative terms to flexibly re-calibrate the nonlinear function's waveforms as the state errors vary. This augmentation increases the controller's design flexibility and enhances the system's disturbance rejection capacity while economizing control energy expenditure under every operating condition. The proposed self-organizing LQR is analyzed via customized hardware-in-loop (HIL) experiments conducted on the Quanser's single-link rotational inverted pendulum. As compared to the fixed-gain LQR, the proposed SR-EM-STC delivers an improvement of 52.2%, 16.4%, 55.2%, and 42.7% in the pendulum's position regulation behavior, control energy expenditure, transient recovery duration, and peak overshoot, respectively. The experimental outcomes validate the superior robustness of the proposed scheme against exogenous disturbances.

Complex-order PID controller design for enhanced blood-glucose regulation in Type-I diabetes patients

Type-I Diabetes (TID) is a chronic autoimmune disease that elevates the glucose levels in the patient’s bloodstream. This paper formulates a fractional complex-order Proportional-Integral-Derivative (PID) control strategy for robust Blood Glucose (BG) regulation in TID patients. The glucose-insulin dynamics in blood plasma are modeled via the Bergman-Minimal-Model. The proposed control procedure employs the ubiquitous fractional order PID controller as the baseline BG regulator. The design flexibility of the baseline regulator to effectively normalize the BG levels is enhanced by assigning complex orders to the integral and differential operators instead. The resulting Complex Order PID (CO-PID) regulator strengthens the controller’s robustness against abrupt variations in the patient’s BG levels caused by meal disturbances or sensor noise. The controller parameters are numerically optimized offline. The aforesaid propositions are justified by performing credible simulations in which the proposed controller is tasked to effectively track a set point value of 80 mg/dL from an initial state of hyperglycemia under various disturbance factors. As compared to the FO-PID controller, the CO-PID controller improves the reference tracking-error, transient recovery-time, and control expenditure by 13.1%, 33.4%, and 28.1%, respectively. The simulation results validate the superior reference-tracking accuracy of the proposed CO-PID controller for BG regulation.

Finite-time adaptive practical tracking control for high-order nonlinear systems with full-state constraints and input saturation

This paper focuses on finite-time adaptive practical tracking control for a class of high-order nonlinear systems with full-state constraints and input saturation. The state constraints are handled by applying nonlinear transformed functions (NTFs) and the input saturation is estimated by an auxiliary hyperbolic tangent function. On the basis of adding a power integrator technique and adaptive control method, an adaptive state feedback controller is designed for the closed-loop system. With the aid of finite-time stability theory, the tracking error converges to a bounded neighbourhood of the origin in a finite time, and all the signals in the closed-loop system are bounded. At last, a simulation example and a practical example are presented to show the effectiveness of the proposed control procedure.

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights.

This article presents flexible online adaptation strategies for the performance-index weights to constitute a variable structure Linear-Quadratic-Integral (LQI) controller for an under-actuated rotary pendulum system. The proposed control procedure undertakes to improve the controller's adaptability, allowing it to flexibly manipulate the control stiffness which aids in efficiently rejecting the bounded exogenous disturbances while preserving the system's closed-loop stability and economizing the overall control energy expenditure. The proposed scheme is realized by augmenting the ubiquitous LQI controller with an innovative online weight adaptation law that adaptively modulates the state-weighting factors of the internal performance index. The weight adaptation law is formulated as a pre-calibrated function of dissipative terms, anti-dissipative terms, and model-reference tracking terms to achieve the desired flexibility in the controller design. The adjusted state weighting factors are used by the Riccati equation to yield the time-varying state-compensator gains.

Complex Fractional-Order LQIR for Inverted-Pendulum-Type Robotic Mechanisms: Design and Experimental Validation

This article presents a systematic approach to formulate and experimentally validate a novel Complex Fractional Order (CFO) Linear Quadratic Integral Regulator (LQIR) design to enhance the robustness of inverted-pendulum-type robotic mechanisms against bounded exogenous disturbances. The CFO controllers, an enhanced variant of the conventional fractional-order controllers, are realised by assigning pre-calibrated complex numbers to the order of the integral and differential operators in the control law. This arrangement significantly improves the structural flexibility of the control law, and hence, subsequently strengthens its robustness against the parametric uncertainties and nonlinear disturbances encountered by the aforementioned under-actuated system. The proposed control procedure uses the ubiquitous LQIR as the baseline controller that is augmented with CFO differential and integral operators. The fractional complex orders in LQIR are calibrated offline by minimising an objective function that aims at attenuating the position-regulation error while economising the control activity. The effectiveness of the CFO-LQIR is benchmarked against its integer and fractional-order counterparts. The ability of each controller to mitigate the disturbances in inverted-pendulum-type robotic systems is rigorously tested by conducting real-time experiments on Quanser single-link rotary pendulum system. The experimental outcomes validate the superior disturbance rejection capability of the CFO-LQIR by yielding rapid transits and strong damping against disturbances while preserving the control input economy and closed-loop stability of the system.

Robust Control and Thermal Analysis of a Reduced Model of Kirchhoff Composite Plate with Random Distribution of Thermopiezoelectric Sensors and Actuators

This paper presents an implementation of a robust control LQG-Kalman model applied to composite Kirchhoff plate dynamics. A reduced model of a finite element method and control procedure is considered in the modeling of a structure because of the important number of piezoelectric patches used in control. Replacing the full model with a short model reduces the computational and time costs, especially when the number of degrees of freedom is significant. In robust control, the measurement of all states is not necessary and the observability and estimability criteria can be exploited, while conventional LQR control assumes that the data accessibility of all states is available. For this reason, robust control is proposed to control the random external disturbances and is compared to LQR control to illustrate its practicability and efficiency. The sensors and actuators in the thermo-piezoelectric material are randomly distributed on both sides of the plate to establish the control procedure. A Monte Carlo simulation is used in the selection of the degrees of freedom of sensors presenting high electrical outputs. Numerical simulations are performed to demonstrate the effectiveness of the proposed control procedure in a reduced model and under mechanical and thermal disturbances in comparison with the LQR control.

A New Nonparametric Multivariate Control Scheme for Simultaneous Monitoring Changes in Location and Scale.

Real-time monitoring of the breast cancer index is becoming increasingly important. It can help create advances in the diagnosis and treatment of breast cancer. In today's modern medical processes, simultaneously monitoring changes in observations in terms of location and scale are convenient for the implementation of control schemes but can be challenging. In this paper, we consider a new nonparametric control scheme for monitoring location and scale parameters in multivariate processes. The proposed method is easy to implement, and the performance of the proposed control procedure is discussed. Then, we compare the proposed scheme with some competing methods. Simulation results show that the proposed scheme can efficiently detect a range of shifts. The proposed chart can trigger an alert and timely discover the change of the breast cancer index.

Intuitive Multiphase Matrix Converter Control Procedures Applied to Power-System Phase Shifters

The article presents the concept of application of a multiphase matrix converter (MMC)-based device working as a phase-shifting control device in a power system. A matrix M × M multiphase converter is a simple structure incorporating M × M bidirectional switches, connecting M input phases to M output phases (a square structure is used). The device, in this research and under proposed control, is able to build M output sinusoidal-shape phases (desired output) from parts of input voltages. The proposed MMC-based device can be considered as a new flexible AC transmission system (FACTS) apparatus. Three basic control systems that enabled the creation of output waveforms as the combination of input ones were presented. Both 6 × 6 and 12 × 12 matrix structures were introduced, since 3 × 6 and 3 × 12 transformers are already in use. The mathematical, Simulink, and laboratory models were built to extract characteristic features of the MMC. The chosen “area-based” control procedure was based on finding a common point of area representing a certain switch (connecting a certain input and a certain output) and a time-dependent trajectory. Practical application of the MMC in a power system involves not only MMC analysis, but also the study of application requirements, possible converter topologies, and the development of new, reliable control algorithms. Particular consideration was given to the simplicity of the control and the analysis of the converter properties. The proposed control procedure did not use the PWM technique, but created output in similar way to a multilevel converter.

Instantaneous Power Theory For Unbalanced Voltage Compensation Of 3-Phase Power Systems

This paper presents another control technique for a three-phase power systems which depends on instantaneous power hypothesis for unbalanced voltage. In this paper we will dissect power quality issues under distortional and unbalanced voltage conditions, In this methodology, the voltage and source voltages are utilized to create the reference voltages of an arrangement dynamic power channel and source currents are utilized to produce the reference currents of a shunt dynamic power channel. The proposed control approach depends on instantaneous power and is streamlined by utilizing a self-tuning channel, without utilizing any filters or phase bolted circle, and without estimating voltage or channel currents. The presentation of the proposed control approach is assessed regarding power factor adjustment, source impartial current alleviation, voltage adjusting and relief of the current and voltage harmonics of distortional and unbalanced voltages in a three-phase system. Accordingly, the occasions that current is estimated is diminished and system execution is improved. The outcomes got by MATLAB/SIMULINK programming show the viability of the proposed control procedure in contrast with the regular technique.

Verification of Infection Prevention Control Using a Spatial Random Walk Model

To stop pandemic of the 2019 novel coronavirus (COVID-19), "an 80 percent reduction of person to person contact opportunities" was proposed by the Japanese government. This guideline was based on the result of macroscopic differential equation model akin to the SIR (Susceptible-Infected-Recovered) model. For the purpose of indicating person to person’s infection mechanism intuitively, we built a new model to calculate infections between two persons who are in contact each other. This model adopted a spatial random walk model to express random movement of people in a specific 2-D geographical space. This model was applied to verify the effect of the proposed infection control procedure, "80 percent reduction". The result of the numerical simulation supported a proposed infection control procedure of "an 80 percent reduction" derived by the SIR model.

A Novel Sensorless Control for Multiphase Induction Motor Drives Based on Singularly Perturbed Sliding Mode Observer-Experimental Validation

This paper aims to develop an innovative sensorless control approach for a five-phase induction motor (IM) drive. The operation principle of the sensorless scheme is based on the sliding mode theory, within which a sliding mode observer (SMO) estimates the speed and rotor resistance simultaneously. The operation methodology of the proposed control technique is formulated using the mathematical model of the machine and the two-time-scale approach. The observation technique offers a simple and robust solution of speed and rotor resistance estimation for the sensorless control approach of the multiphase drive. The paper considers the five-phase induction motor (IM) as a case study; however, the proposed control algorithm can be employed by different types of multiphase machines. To test the applicability of the proposed sensorless control approach, the drive performance is firstly validated using MATLAB/Simulink-based simulation. Then, the simulation results are verified using real-time simulation and experimentally using TMS320C32 DSP-based control board. The obtained results confirm and validate the ability of the proposed control procedure in achieving a robust dynamic performance of the drive against the system uncertainties such as parameter variation.

Optimum design and analysis of a dynamic energy management scheme for HESS in renewable power generation applications

A novel control strategy for a hybrid energy storage system (HESS) is outlined and examined in this paper. In the proposed system, the battery is utilized to stabilize the moderate changing of power surges, whereas supercapacitor is utilized to stabilize the rapidly changing of power surges. A two-loop proportional-integral controller is designed for the closed-loop operation of HESS. The source power and load power is not balanced because of the fluctuating conditions of photovoltaic (PV) power generation and load demand. This power imbalance causes fluctuations in direct current (DC) grid voltage. The DC bus voltage variations are mitigated using HESS, which is connected to DC grid through bi-directional DC–DC converter to enables the bidirectional power flow between energy storage devices and the DC bus. To enhance the life span and to reduce the current stress on the battery, the proposed method is employed with charge/discharge rate control feature. The proposed control procedure is realized in MATLAB/Simulink and the results are presented for different case studies. Experimental results are obtained for a two-input bi-directional converter at the sudden change in PV generation and load demand with the proposed controller. The proposed control strategy is effective for maintaining constant DC microgrid voltage under source and load fluctuations.

Reactive Power Transfer via Matrix Converter Controlled by the “One Periodical” Algorithm

The article describes the application of a straight forward energy converter, a multiphase matrix converter (MC), as part of a device, connected parallel to the power grid, and able to supply variable reactive power flow to the power system. The research performed by authors included the development of control procedures for a multiphase MC, based on a new approach and power system (application) requirements. The multiphase MC structure (6 × 6, 12 × 12) was used since the proposed control procedure creates output as the combination of input voltages. The increased number of phases decreases the order of harmonics in the MC converter similarly as in multilevel converters. This manuscript concentrates on the mathematical analysis of MC work under the “one periodical” algorithm and links it introduces in the power system. The previously developed, spatial-temporal mathematical model of the MC was limited to the dominant (first) harmonic and applied between the grid and reactive load. The results obtained from the analysis of the model showed that, for the applied control procedure (one periodical algorithm), the output voltage is built only from positive or negative sequences of input voltage. Three cases were recognized where the sign input power factor depends on input voltage and control sequence as well as on the value of control frequency. The effects of the model simulation were compared to those obtained from the MATLAB simulation and from the real laboratory 30 kVA-rated model. The main factors analyzed during this research include the expected value and distortion of input current and sign of reactive input power.

RETRACTED: Low-voltage ride-through capability enhancement of wind energy conversion system using an ant-lion recurrent neural network controller

This paper proposes a hybrid controller to improve the low-voltage ride-through ability of the grid-connected wind energy conversion system. The hybrid controller is the joined execution of the ant-lion optimizer with the recurrent neural network called the ant-lion recurrent neural network. At voltage drop and fault conditions, the proposed control technique guarantees the low-voltage ride-through ability of the wind energy conversion system. The ant-lion optimizer in the perspective of objective function approach will be utilized in the offline manner to distinguish the optimal solutions from the accessible looking space and it makes the training dataset. Identifying the low-voltage ride-through ability, the ant-lion optimizer method considers voltage, current, and real and reactive power. Using these parameters, the objective function of the ant-lion optimizer strategy is described and explained. The recurrent neural network predicts the best possible control signals of grid-side and generator-side converters in light of the achieved dataset. The proposed method is utilized for system regulation and instability problem of voltage amid the fault conditions. In this way, the system’s low-voltage ride-through capability is upgraded and besides, the many-sided quality is diminished with the help of the proposed strategy. By applying the comparative investigation with the existing approaches, the proposed control procedure is actualized in the MATLAB/Simulink working stage and the performances are assessed.

An anfis converter control approach of grid connected wind/PV/battery system

The major objective of this task is a control technique for power flow management of a network associated hybrid PV-wind-battery based system with multi-input transformer coupled bidirectional DC-DC converter using ANFIS controller is introduced. The proposed system intends to fulfill the demand of load, deal with the power flow from the distinctive sources, injects surplus power into the network and charge the battery from framework as and when required. A transformer coupled boost half-bridge converter is used to tackle power from wind, while bidirectional buck-boost converter is used to outfit control from PV alongside battery charging/releasing control. A single stage full-bridge bidirectional converter is used for ac loads and collaboration with grid. The proposed converter has reduced number of intensity change stages. This enhances the effectiveness and unwavering quality of the framework. In this article Adaptive Neuro Fuzzy interference System (ANFIS) is proposed for better performance of the system. Neural system has many inputs and also has multiple outputs but the fuzzy logic has multiple inputs and single output, so the combination of this two is known as ANFIS which is utilized for nonlinear applications. The proposed paper of simulation results acquired using MATLAB/Simulink demonstrate the execution of the proposed control procedure for power stream the executives under different methods of activity.

Model analysis and real-time implementation of model predictive control for railway power flow controller

Railway power flow controllers (RPFCs) are known as a power electronics based full-fledged compensator in the field of electric railway systems (ERSs). They have attracted experts attention over the last years due to their outstanding performance in dealing with power quality (PQ) problems. The complexity, randomness and uncertainty characteristic of ERS and traction loads have led the control of RPFC to be difficult. In this paper, a precise modeling method based on space-state model (SSM) and dynamic switching pattern is presented. Applying the extracted equivalent model and mathematical equations, a modified model predictive control (MMPC) method is proposed to improve the compensation and dynamic performance of RPFC. To eliminate the low frequency oscillation (LFO) and other external disturbance effects, a dual-loop modified d-q frame control is implemented with frequency locked capability. Precise simulations have been provided to verify the modeling and proposed control procedure performance. Moreover, a real-time laboratory setup based on RT-LAB and Opal-RT is provided to confirm the simulation results and theoretical analysis according to the desired specifications of the real ERS.

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods.

Positioning and control of the orbital structure of the Arktika-M innovative space system (marking the 50 years of Lavochkin Association’s space activities)

The orbital positioning options and orbital structure control methods are considered for the Arktika-M highly elliptical hydrometeorological space system, which is designed for continuous 24-hour imaging of the Earth’s Arctic region. The purpose of the control is to ensure on-going performance during the entire operational life of the space system given a major spatial and temporal deformation of its orbital structure due to the nonuniform evolution of the orbital parameters. The highly elliptical Molniya orbits are considered. The proposed control procedure is based on the minimization of the spatial and temporal deformation of the orbital structure by means of the differential choice of the initial orbital parameters during the deployment and follow-up of the space system.