Integral Action Research Articles

Enhancing Management Capacities for Rural Tourism Development: A Perspective from University-Industry Collaboration

Introduction: Municipal autonomy in crafting and executing local development strategies is pivotal for reducing reliance on central authority and fostering solutions to economic, social, and environmental challenges at the grassroots level. Strengthening management capacities within each municipality is therefore crucial for driving local initiatives that effectively address these issues. Objective: To identify, through university-industry collaboration, strategies for expanding management capacities for rural tourism as a catalyst for local development at the municipal level. Methodology: This research adopts a descriptive, qualitative approach. Methods such as documentary analysis, scientific observation, and interviews were employed to underpin the proposal, drawing from experiences in the Avileño municipalities of Florencia, Chambas, and Bolivia. Results: Several integrated actions and workshops have been structured within the university-industry-municipality framework, offering a suite of tools that enhance learning and foster innovative management capacities at the municipal level, with a focus on leveraging tourism activity for local development. Conclusions: The proposed actions and workshops represent a significant stride in rural tourism management within these municipalities. Establishing structures and operational systems is crucial for driving the local economy and organizing knowledge in tourism, thus facilitating a direct impact on local development.

Homogeneous Unit Sliding Mode Control

The methodology of the unit sliding mode control design (known since 1970s) for linear systems is revised based on the concept of the generalized homogeneity. The restriction about a consistency of the number of control inputs with the dimension of the sliding surface is eliminated. A simple procedure of control parameters tuning based on a known maximal magnitude of matched perturbations is developed. To deal with perturbations of unknown magnitude, a homogeneous sliding mode control with integral action is designed as well. The theoretical results are supported by numerical simulations.

Data-Driven Decentralized Online System Identification-Based Integral Model-Predictive Voltage and Frequency Control in Microgrids

This article proposes a decentralized online system identification-based integral model-predictive control strategy for the voltage and frequency regulation in the microgrids (MGs). The main advantage of the proposed architecture is that the approach is inherently adaptive to the changing system conditions and does not require the knowledge of system parameters. In addition, as the decentralized system parameters are identified online utilizing local/global measurements, the controller is robust against unknown system disturbances. The decentralized nature of the proposed architecture is evolved from an extended Kalman filter that is utilized to synchronize the states of the identified model, thereby enabling a plug-and-play capability. The proposed controller is constructed utilizing the identified augmented incremental model that incorporates optimal integral action required to mitigate the steady-state errors in the MG voltage and frequency. Furthermore, controller formulation as a quadratic optimization problem including the constraints limits the control inputs within the bounds during electrical faults, thus assisting the downstream primary controller in accomplishing ride-through capability. The proposed framework is validated utilizing a section of the IEEE 123-bus distribution network for the different grid events including the effect of communication latency. Model-in-the-loop real-time simulation results demonstrate that the proposed framework offers significant transient performance improvement compared to the optimal proportional–integral strategy, especially around 50% faster regulation, when the communication latency is considered.

Trajectory tracking with integral action of switched periodic affine systems

This paper deals with integral control of a class of switched affine systems characterised by time-varying differential equations that, along with the discontinuities caused by the switching, also depend periodically on an exogenous parameter, which is an affine function of time. The goal is to design a state-dependent switching function with integral action that ensures global asymptotic tracking of a trajectory of interest. The integral action is responsible for providing robustness to the system against uncertainties and load variations, whenever the discrepancy between the model and the real system is sufficiently bounded. Due to the integrator, all the convex combinations of the dynamic matrices are non-Hurwitz. In this case, the main difficulty is to guarantee that the time derivative of the Lyapunov function is strictly negative definite, which is done by means of LMIs and conditions on the affine terms. To the best of our knowledge, this is the first Lyapunov-based switching rule with integral action able to ensure global asymptotic tracking of a pre-specified profile. When applied to AC circuits the advantage is to design the switching rule based on the original system, without resorting to averaged models. The theory is illustrated by the control of a three-phase AC-DC converter.

Robust Control System for DFIG-Based WECS and Energy Storage in reel Wind Conditions

This research work focuses on addressing the challenges of controlling a wind energy conversion system (WECS) connected to the grid, particularly when faced with variable wind speed profiles. The system consists of a Doubly-Fed Induction Generator (DFIG) connected to the grid through an AC/DC/AC converter, along with a Li-ion battery storage system connected to the Back-to-Back converter DC link via a DC/DC converter. The non-linearity and internal parametric variation of the wind turbine can negatively impact energy production, battery charging performance, and battery lifespan. To overcome these issues, the study proposes a robust control approach called Integral action Sliding Mode Control (ISMC) to enhance the dynamic performance of the WECS based on DFIG. Additionally, the battery charging and discharging controllers play a crucial role in efficiently distributing power to the grid and storage unit based on the battery's state of charge, extracted energy, and power injected into the grid. Two current regulation modes, buck charging and boost discharging, are employed to ensure proper energy distribution. Furthermore, a storage system energy management algorithm is implemented to ensure battery safety during one of the charging modes. The effectiveness and robustness of the proposed control method were validated through simulations of a 1.5 MW wind power conversion system using Matlab/Simulink. The results confirmed the method's efficiency and efficacy.

Induction Motor Performance Improvement using Super Twisting SMC and Twelve Sector DTC

Induction motor (IM) direct torque control (DTC) is prone to a number of weaknesses, including uncertainty, external disturbances, and non-linear dynamics. Hysteresis controllers are used in the inner loops of this control method, whereas traditional proportional-integral (PI) controllers are used in the outer loop. A high-performance torque and speed system is consequently needed to assure a stable and reliable command that can tolerate such unsettled effects. This paper treats the design of a robust sensorless twelve-sector DTC of a three-phase IM. The speed controller is conceived based on high-order super-twisting sliding mode control with integral action (iSTSMC). The goal is to decrease the flux, torque, the current ripples that constitute the major conventional DTC drawbacks. The phase current ripples have been effectively reduced from 76.92% to 45.30% with a difference of 31.62%. A robust adaptive flux and speed observer-based fuzzy logic mechanism are inserted to get rid of the mechanical sensor. Satisfactory results have been got through simulations in MATLAB/Simulink under load disturbance. In comparison to a conventional six-sector DTC, the suggested technique has a higher performance and lower distortion rate.

Management of Audiovisual Archiving in the Context of Tunisia's National Artificial Intelligence Strategy

This study aims to analytically highlight the efforts made by Tunisian national television to integrate artificial intelligence (AI) applications into its audiovisual production management policy, within the framework of implementing and overcoming the challenges associated with a national strategy for this innovative technology. The research is based on a qualitative methodology that includes both field observations and semi-structured interviews with experts working in the documentary management unit of the national television. Additionally, it involves a documentary analysis of all reports and strategic documents that reflect the process of implementing the national AI strategy and the various modernization projects of the national television. The results, informed by the experience of the French Audiovisual Institute (INA-France) in using AI applications for processing, analyzing, and enhancing audiovisual resources, demonstrate the vital need for Tunisian national television to adopt AI techniques within a coherent national context. Furthermore, there is a necessity for a complete digital transformation to fully play its role and remain competitive in the intelligent media landscape. By examining possible collaborations between the ambitions of Tunisian national television and the proven practices of major international channels, the study highlights the importance of strategic planning and proactive actions for AI integration. It also details the benefits and potential obstacles of this integration, emphasizing the need for a collective effort to incorporate AI into Tunisian media production, thereby positioning the country at the forefront of technological innovation.

An optimal membership function based Fuzzy-[formula omitted] stabilizer design to suppress low frequency oscillation in synchronous generator

An optimal membership function-based fractional order fuzzy proportional integral (Fuzzy-PIλ) power system stabilizer (PSS) is designed to suppress low frequency oscillation (LFO) in a synchronous generator connected to an infinite bus power system. Speed deviation and the change in speed deviation of synchronous generator due to LFO are taken as inputs of the fuzzy controller, and the parameters of a fractional-order PI controller (proportional gain, integral gain, and the fractional term in integral control action) are taken as fuzzy output variables. The range, scaling, and shape of the membership functions of the fuzzy controller are optimized such that it can tune the fractional order proportional integral (PIλ) stabilizer under any disturbance or parametric uncertainty in the synchronous generator. The advantage of the proposed stabilizer is that it can handle a wide range of disturbances and adjust the gains of the control parameters for the system. A nonlinear dynamic acceleration coefficient-based class-topper optimization is applied to optimize the fuzzy settings. The robustness and sensitivity of the proposed optimal Fuzzy-PIλ stabilizer are verified under different scenarios for the synchronous generator and compared with available results.

Simultaneous Compensation of Actuation and Communication Delays for Heterogeneous Platoons via Predictor-Feedback CACC with Integral Action

Simultaneous Compensation of Actuation and Communication Delays for Heterogeneous Platoons via Predictor-Feedback CACC with Integral Action

Port-Hamiltonian modeling and control of a curling HASEL actuator

This paper is concerned with the modeling and control of a curling Hydraulically Amplified Self-healing Electrostatic (HASEL) actuator using the port-Hamiltonian (PH) approach. For that purpose, we use a modular approach and consider the HASEL actuator as an interconnection of elementary subsystems. Each subsystem is modeled by an electrical component consisting of a capacitor in parallel with an inductor connected through the conservation of volume of the moving liquid to a mechanical structure based on inertia, linear, and torsional springs. The parameters are then identified, and the model is validated on the experimental setup. Position control is achieved by using Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) with integral action (IA) for disturbance rejection. Simulation results show the Efficiency of the proposed controller.

Genetic-Algorithm-Assisted Self-Scheduled Multidelay PIR Control: Experiments in a Car-Like Vehicle System.

The path-tracking control of an intelligent vehicle always suffers from the high-frequency measurement noises. To confront this issue, this work puts forward a novel delayed output-feedback implementation of proportional-integral-derivation (PID) control, which is called multidelay proportional-integral-retarded (PIR) control. The mathematical model of the vehicle system is represented in the form of a linear parameter-varying (LPV) system, which uses the car position as the scheduling variable for regulation. On this basis, the multidelay PIR controller is designed such that the tracking errors gradually converge to zero with the aid of the proportional and integral actions, and the harmful high-frequency measurement noises are attenuated by the retarded term consisting of a few delayed proportional actions. To tune the PIR controller parameters, linear matrix inequalities (LMIs), derived by applying Taylor's expansion to the retarded term, are used to compute the convex subcontroller gains. Then, the self-scheduled tracking controller is formulated as the weighted sum of convex subcontrollers, and the weight functions scheduled by the current position are adaptive to the different operational conditions. Experiments in real time using a laboratory car-like vehicle are employed to assess the performance of the proposed controller.

The role of nicotinamide adenine dinucleotide salvage enzymes in cardioprotection.

The increasing trend of cardiac diseases is becoming a major threat globally. Cardiac activities are based on integrated action potential through electronic flux changes within intra- and extracellular molecular activities. Nicotinamide adenine dinucleotide (NAD) is a major electron carrier present in almost all living cells and creates gated potential by electron exchange from one chemical to another in terms of oxidation (NAD+) and reduction (NADH) reactions. NAD+ plays an important role directly or indirectly in protecting against various cardiovascular diseases, including heart failure, occlusion, ischemia-reperfusion (IR) injury, arrhythmia, myocardial infarction (MI), rhythmic disorder, and a higher order of cardiovascular complexity. Nicotinamide phosphoribosyl transferase (NAMPT) is well known as a rate-limiting enzyme in this pathway except for de-novo NAD synthesis and directly involved in the cardioprotective activity. There are two more enzymes - nicotinate phosphoribosyl transferase (NAPRT) and nicotinamide riboside kinase (NRK) - which also work as rate-limiting factors in the NAD+ synthesis pathway. This study concentrated on the role of NAMPT, NAPRT, and NRK in cardioprotective activity and prospective cardiac health.

PI Tracking Control of a Nonlinear plant

The tracking control design for nonlinear plants by model inversion, following the Linear Algebra Based methodology, usually assumes a proportional to the error approaching of the process variables to the references evolution as a design criterion for the control. In this paper, by using the well-known properties of the integral action, a PI-like control is assumed, countering constant disturbances and model parameters uncertainty. The application to a simple mass-spring nonlinear system illustrates the procedure.

An integrated action plan to fund and support drug development for Dup15q syndrome: a patient organization perspective.

Maternal 15q11.2-13.1 duplication syndrome, or Dup15q syndrome (Dup15q), is a rare neurodevelopmental disorder affecting as many as 1 in 5000 to 1 in 20,000 children worldwide. Autism and seizures are two of the most commonly observed phenotypes in Dup15q, with intellectual disability, hypotonia, gastrointestinal distress, and substantial fine and gross motor deficits also commonly reported. The community that is now known as the Dup15q Alliance started in 1994 as a small group of families raising children with chromosome 15q duplications. Originally named IsoDicentric 15 Exchange, Advocacy and Support (IDEAS), the group received official nonprofit organization status 10 years later and rebranded to its current name, Dup15q Alliance, shortly thereafter. Today, there are over 2200 families affiliated with Dup15q Alliance, with an average intake of 10 new families each month. Historically, Dup15q Alliance has provided the community with access to family and caregiver resources in addition to serving as a repository for basic educational information about Dup15q and research developments. The recent installation of a dedicated director of scientific and clinical initiatives alongside other infrastructural changes has now primed the Dup15q Alliance to expand its scientific footprint by funding cutting-edge research, supporting clinical sites and trials, and investing in novel therapeutics that have the potential to change the reality of a Dup15q syndrome diagnosis. To do this, we have developed the LEARN. TREAT. CURE. program to align initiatives, fast-track progress, and bring hope and reality into coexistence. Briefly, we seek to learn as much as we can about the syndrome through cutting-edge research, natural history studies, and patient registry utilization, identify and develop methods to treat the symptoms of our patient community, with the ultimate goal of developing a cure for the disease-causing symptoms of the syndrome.

Energy-based modeling and robust position control of a dielectric elastomer cardiac assist device

This paper is concerned with the port Hamiltonian modeling and control of a dielectric elastomer actuator used for a cardiac assistance device. The proposed non-linear model is identified under different applied voltages and pressures, and validated against experimental results with relative errors of less than 0.3%. Subsequently, two passivity-based controllers are designed to stabilize the actuator at a desired position. The first controller is designed using control by interconnection. The second one considers additional integral action to reject disturbances while preserving the passivity of the closed-loop system.

The impact of force equalization in minimizing the effect of drift in feedback transducers in torque-summed electromechanical actuators

This paper focusses on implementing force equalisation to reduce or eliminate torque disparities in a four-lane torque-summed electromechanical actuator that drives the inner board aileron control surface on the Sea Harrier aircraft. Proportional, integral, and derivative control action achieved position control of the common output shaft, following two failures. The analysis included the effect of inherent motor disparities and drift in feedback transducers. Three-phase motor models were considered to account for the influence of the inherent torque ripple effect, and the influence of inertial and aerodynamic loads over various flight envelopes were also included in the analysis. Simulation tests demonstrated that although torque disparities between mismatched lanes are influenced by drift in potentiometer readings, force equalization was proven to be effective in eliminating such deviations.

Global consensus-based formation control of perturbed nonholonomic mobile robots with time varying delays

This paper proposes a smooth time-variant PID-like control scheme for networks composed of nonholonomic vehicles modeled as differential drive robots affected by unknown input constant disturbances and transmission variable time-delays in the communication channel. Using Barbalat’s Lemma and under the fact that the interconnecting graph is undirected and connected, it is proved that all robots positions asymptotically converge to a position in a given desired formation and they all agree on the center of this formation, while the orientations asymptotically reach a consensus value. Besides, it is proved that given the structure of the proposed new integral action, the external constant disturbances are rejected (exactly estimated) and that velocities converge to zero. Simulation results, with a robot network composed of eight nonholonomic vehicles and considering disturbances subjected to step changes, are presented to illustrate the robustness of the proposed control scheme.

Neural tracking trajectory of discrete-time nonlinear systems based on an exponential sliding mode algorithm

For a class of discrete-time nonlinear systems, this paper proposes a discrete-time sliding mode control algorithm with an exponential term that acts as a variable gain to improve the convergence to a bounded region around the origin for the state variable. To compensate for unknown, but bounded disturbances, it has been employed a discontinuous function through a discrete-time integral action. A discrete-time neural network has also been employed to identify such nonlinear system with a block controllable structure. Finally, the proposed controller and the neural network algorithms are applied to a discretised direct current (DC) motor to follow a desired admissible trajectory. Numerical simulations show the effectiveness of the proposed control law.

Analysis of Adaptive Individual Pitch Control Schemes for Blade Fatigue Load Reduction on a 15 MW Wind Turbine

Individual pitch control (IPC) is a method to mitigate periodic blade loads in wind turbines, and it is typically implemented using the multi-blade coordinate (MBC) transform, which converts the blade load measurements from a rotating frame into the non-rotating tilt axis and yaw axis. Previous studies have shown that by including an additional tuning parameter in the MBC, the azimuth offset reduces the coupling between non-rotating axes, allowing for higher performance levels for diagonal controller structures. In these studies, the decentralized control of IPC was composed of two identical integral controllers. This work analyzes and compares the improvement that the azimuth offset can provide in different adaptive gain scheduling IPCs where the diagonal controllers can have integral or proportional action with different gains. They are applied to a 15 MW wind turbine simulated with OpenFAST v3.5 software. The controller parameter tuning is addressed as an optimization that reduces blade fatigue load based on the damage equivalent load (DEL) and is resolved through genetic algorithms. Simulations show that only using different controller gains in IPC does not provide significant improvements; however, including azimuth offset in the optimal IPC schemes with integral controllers allows for the greatest DEL reduction with a lower actuator effort.

Robust Speed Control of a Multi-Mass System: Analytical Tuning and Sensitivity Analysis

The regeneration of highly dynamic driving maneuvers on vehicle test benches is challenging due to several influences, such as power losses, vibrations in the overall system that involves the vehicle with the test bench, uncertainties in the model parameterization, and time delays from both the test bench and the measurement systems. In order to improve the dynamic response of the vehicle test bench and to overcome system disturbances, we employed different types of control algorithms for a mechanical multi-mass model. First, those controllers are extensively investigated in the frequency domain to analyze their stability and evaluate the noise rejection quality. Then, the expectations from the frequency analysis are confirmed in a time-domain simulation. Furthermore, sensitivity analysis tests were conducted to evaluate each controller’s robustness against the modeling parameters’ uncertainty. The linear quadratic controller with integral action demonstrated the best compromise between performance and robustness.