Evaluating supervised models for estimating reference evapotranspiration (ET o ) is crucial when there is a domain shift, meaning the models should be tested at stations not used during training. In such cases, an external k-fold validation can be performed, reserving different stations for testing in each iteration. However, this simple approach may include training data from stations that differ substantially from the testing station, which can reduce the model's generalizability due to domain shift. Therefore, this study focused on transfer-learning (TL) based modeling of ET o to enhance the performance of temperature-based gene expression programming (GEP) models for spatial (external) modeling. Specifically, transductive TL, which emphasizes domain selection via an instance-based approach, was employed by applying preliminary clustering methods for the first time in the literature. Various initial clusters of training stations were defined based on factors such as the aridity index (IA), the continentality index (CICU), principal component analysis (PCA), the self-organizing maps (SOM), and k-means clustering. K-fold validation was conducted within each cluster, which provided intra-cluster and cross-cluster assessments. The models achieved lower accuracy when a global k-fold validation was used without preliminary clustering for source domain selection. The findings revealed the importance of the similarity between source (training) and target stations in model performance, indicating that preliminary clustering may be beneficial before data splitting in supervised machine learning development. When station clustering is appropriate, the intra-cluster approach generally yields more accurate results than the cross-cluster approach.

Geometric Algebra (GA) provides a unified, compact mathematical framework for geometric computing, simplifying relations typically handled with more complex tools like matrix multiplication. In fields like robotics, GA replaces conventional coordinate-based approaches with the multiplication of special elements called rotors, offering greater efficiency. Despite its advantages, GA’s complexity and the lack of symbolic tools hinder its broader adoption among applied mathematicians and engineers. To address this, this article introduces Symbolic and User-friendly Geometric Algebra Routines (SUGAR), an open source Matlab toolbox. SUGAR streamlines GA usage in Matlab through a collection of user-friendly functions that support both numeric and symbolic computations, even in high-dimensional algebras. Designed for applied mathematics and engineering, it enables intuitive manipulation of geometric elements and transformations in two- and three-dimensional projective and conformal GAs, consistent with established computational methods. Moreover, SUGAR manages multivector functions such as exponential, logarithmic, sinusoidal, and cosine operations, enhancing its applicability in domains like robotics, control systems, and power electronics. Finally, this article also presents three validation examples across these fields, showcasing SUGAR’s practical utility in solving real-world engineering and applied mathematics problems.

In industrial microgrids with medium power rating photovoltaic systems, the low-voltage ride-through capability should be incorporated to help keep power system stability. The goal of this paper is to present a control strategy that allows taking advantage of the maximum capability of the inverters to support the most dropped phase in a photovoltaic-based industrial microgrid during voltage sags. Depending on the grid code requirements, the rated current value could be injected by the local inverters during these disturbances. The currents can be injected through the positive and negative sequences depending on the sag characteristics and the power rating of the local inverters. Also, to prevent overcurrent, the controller can apply active power curtailment. Lastly, selected simulation results are presented to validate the performance of the control scheme.

A key objective to be fulfilled by distributed voltage source inverters working in parallel in islanded MicroGrids (MGs) is to ensure active power sharing while keeping the frequency at a desired setpoint. Recently, consensus-based control techniques have been applied at the secondary control level for active power sharing while correcting the frequency deviation that the droop control implemented at the primary control level introduces. To this end, inverters work in a cooperative way by sharing their own corrective action with their neighbors over a digital communication network. The contribution of this paper is to analyze how changes in the network topology affect the consensus-based active power sharing control goal. In particular, the analysis focuses on the network structure in terms of adjacency, that is, in terms of the number of connections that each node has. The theoretical analysis based on graph theory provides results that indicate the pattern that steady-state active power values will follow according to the network structure. Numerical examples are used to illustrate the theoretical results, and select simulations on a low-scale MG complete the analysis. The paper results provide insight into the existing design tradeoff between power sharing accuracy and number of network connections.

Grid codes are continuously evolving to improve the ride-through services during voltage sags. The main reason for this evolution is the increasing flexible capabilities of distribution generation inveters. The problem of selecting an appropriate strategy during grid faults is an open research topic that depends on many aspects. Among the possible solutions, this paper solves an optimization problem based on the maximization of the voltage support during grid faults. The control strategy is based on raising as much as possible the positive sequence voltage. This strategy allows to reduce the risk of disconnection by under-voltage that can led to a blackout. The problem is related to two main issues: the amount of injected current and the grid impedance. Regarding the injected current, it should be desirable to develop the references so as to inject the rated current of the inverter. Therefore the voltage support could be improved while keeping the inverter within a safety operation mode. Regarding the impedance, the strategy for inductive or resistive grids should be different. For a combination of both impedances, an optimal solution should exist in order to maximize the voltage increment. This solution is related to the amount of active and reactive current injected by the inverter. The work proposes a voltage support control strategy intended to increase as much as possible the positive sequence voltage and to inject the maximum rated current of the grid-connected distributed generation inverter. The problem is mathematically solved for any type of grid impedance, even resistive, inductive or a combination of both. Simulation results are presented to corroborate the theoretical solution.

In islanded microgrids, parallel operation of voltage source inverters is commonly enabled by primary droop control to achieve power sharing and secondary control that removes the frequency deviation by mimicking at some extend the operation of an integral controller. Often the main task of the distinct secondary control approaches is to compute a corrective term considering the frequency error that is then used by the droop mechanism for frequency compensation. This paper considers the secondary control approach where local integral controllers that compute the frequency corrective term are implemented at each inverter. And considering that integrals are performed in different nodes, the paper shows that global time between nodes achieved through clock synchronization is mandatory for accurate power sharing and frequency restoration.

The increasing deployment of distributed generation (DG) such as photovoltaic panels (PV) connected to low-voltage (LV) grids is becoming a common trend in urban areas. The advances of information and communication technology (ICT) facilitates the collaborative operation of DG systems to achieve collective benefits. The fusion of these two trends creates a new scenario where reactive power control methods can offer additional features and benefits beyond the conventional voltage regulation provided by the droop method. Taking advantage of this new scenario, this paper formulates the application of reactive power control as an optimization problem where simple and ideal settings are imposed by design in order to facilitate the exploration search as well as to avoid over-constraining the optimization space. By appropriately using the reactive power capacity of inverters, the desired collective benefit is to minimize power losses while individual voltages at each inverter should be kept within the statutory limits. The simulated solution of the optimization problem is applied to a real-inspired PV-LV grid subject to an over-voltage situation, which may typically occur during periods of high production but low consumption. Simulation results reveal unexpected optimal settings for reactive power control set-points at each inverter, which calls for a final discussion to review the applicability of the optimization approach.

A topic of interest within the microgrid (MG) community is to achieve accurate sharing of active and reactive power among voltage source inverters (VSI) working in parallel while keeping the voltage frequency and amplitude stable, and close to a given reference. This problem has been mainly solved by the so-called frequency and voltage droop controllers that are local control loops implemented in each VSI. However, since they introduce a frequency and amplitude deviation, a secondary integral-like control loop using a communication system is usually deployed to enable each VSI to cancel the deviations. This paper evaluates two secondary control implementations of the frequency restoration with respect to properties of the communication system. Networked control applications are subject to known problems that are inherent to the use of a communication system such as message losses or varying sampling/transmission intervals, to name a few. The performance analysis reveals that control policies should be designed accounting also for the properties of the communication system. Otherwise, unexpected results violating the control specifications may appear.

The evolution of technology and application needs leads to design complex systems both at hardware and software levels. Modeling approaches and automatic code generation are mature techniques in several application areas to shorten development times even in complex applications. This paper introduces the application of these techniques to critical embedded systems such as networked control systems (NCS). In particular, the case of an Internet-based control of a ball&plate system is presented. The first part of the paper is devoted to the plant modeling and control design strategy taking into account the distributed layout. The second part covers the automatic code generation process: from ScicosLab diagrams, C code is automatically generated onto multiple and physically distributed threads, with the automatic synthesis of thread scheduling, communication and access to the I/O primitives for sampling and actuation. The case study corroborates that model-based design tools mastering NCS complexity can contribute to the success of future industrial projects.

One of the main concerns in the design of networked control systems (NCS's) is the inherent delays induced by the networking infrastructure. Rather than considering delays as a threat, delays may be considered as an opportunity for novel controller design procedures, where delays become a design parameter. The benefits may range from easier and cheaper implementations to improved performance. To enable procedures where the explicit specification of a delay may be profitable, alternative models for a discrete-time LTI system with an arbitrary delay used for controller design must be investigated. This paper presents a modeling effort different than the common approach of extending the state-space model with new state variables. The new model is also capable of representing the same system with a delay but using a state-space modeling structure that keeps the original system order. The focus of the paper is to show that both models are equivalent. A direct consequence is that it will be possible to design a controller for a system without delay in such a way that the closed loop system behaves like having a delay. In other words, a relation between desired control performance (via e.g. closed-loop system poles), controller, and delay is established, which provides a new design criterion for NCS.

Unbalanced voltages in three-phase power systems is a common perturbation propagated along the grid. Distributed Generation plants have gained widespread attention due to their capability to improve power quality in a distributed manner, including voltage unbalance mitigation. A conventional control strategy to command power plants during balanced grid voltages, is the use of power factor to inject/absorb reactive power depending on grid conditions. Advanced control strategies during unbalanced grid voltages can be selected prioritizing positive or negative sequence active and reactive power. This selection determines the voltage support service and therefore can improve the voltage profile, i.e. phase-voltages can be properly supported and voltage imbalance simultaneously corrected. Based on the definition of effective power factor in IEEE 1459 Standard, the reactive power needed for any control strategy is obtained and the resulting effects are described.

This paper presents a novel power sharing control strategy for islanded mode microgrids (MG). The goal is to enable renewable power sources connected to the point of common coupling (PCC) through three-phase three-wire inverters to cooperatively feed linear and non-linear local loads. The strategy contribution is two-fold. First, a centralized controller is designed to facilitate the power sharing capability of all inverters by means of data communications regardless of load changes and inverter faults. Second, a communication protocol is designed following an event-driven paradigm in such a way that the consumed bandwidth is reduced. Selected simulation results show the main features of the power sharing control strategy.

The majority of existing Networked Control Systems (NCS) models are discrete-time formulations based on the exact discretization of the continuous-time linear plant over a sample interval. In the state-space formalism, standard control textbooks suggest that a simple approach to model discrete-time LTI systems with time delay shorter or equal than the sampling period is to extend the state vector with a new state variable representing the last control signal, which implies increasing the order of the model by one. In this paper an alternative state-space model for discrete-time LTI systems with time delay is introduced that does not require increasing the order of the model. The relation between both the standard model and the new model is established, and the potential benefits of the new model with respect to the standard one are discussed. Numerical examples illustrate the concepts discussed throughout the paper.

Penetration of distributed power generation poses new problems in energy distribution. For example, photovoltaic generation systems may difficult the voltage management in distribution lines and voltage rise may occur. To overcome this problem, several voltage control strategies are available and they can be classified as autonomous or distributed regarding whether communication is available between dispersed generators. Through a preliminary case study, this paper investigates the impact that the communication infrastructure has for a given distributed voltage control strategy. Communication issues like transmission rate, delays, and losses are analyzed with respect to the voltage control application performance.

Grid faults are one of the most severe perturbations to deal with in grid connected systems. To support the grid under voltage-sags (dips), different reactive power control strategies are needed depending on the type of grid fault. One of the possible objectives when supporting the grid voltage under type C voltage sags could be to avoid undervoltage in the faulted phases and over-voltage in the non-faulted phase. Therefore, the fault can ride-through the perturbation and the system disconnection can be avoided. This may be accomplished by injecting positive sequence reactive power to raise the voltages and negative sequence reactive power to equalize them. In this work, a detailed mathematical description is introduced to limit the voltage in the phase that do not suffers the voltage-sag just below over-voltage limit, while increasing as much as possible the other two faulted phases. This voltage support service is limited by the maximum rated current. Selected simulation results are provided to understand the proposed reactive power control during type C voltage-sags.

In Networked Control Systems (NCS), the amount of control data exchanged between sensors, controllers and actuators nodes highly depends on the control performance specifications given to each networked control loop. The periodic execution of each loop helps meeting the control specifications while imposing a static network traffic. This paper presents an alternative execution mechanism for each networked control loop that permits to dynamically lower the traffic while ensuring the same or better control performance than the achieved by the periodic case. Simulation results illustrate the theoretical analysis.

The successful operation of Networked Control Systems (NCS) requires employing appropriate approaches for dealing with network induced time delays, i.e. time intervals elapsed from consecutive sampling and actuation operations. Effective approaches often require to impose periodic execution for the sampling and/or actuation operations, enforcing synchronized constant time delays. And considering that sampling and actuation is performed in different nodes, global time between nodes achieved by clock synchronization is the standard assumption or strategy that enables such synchronized operations. This paper presents a technique that permits to implement these synchronized operations in NCS in the absence of global time. Experimental results corroborate the effectiveness of the presented approach.

The Controller Area Network (CAN) provides the basis for many cost-effective distributed embedded systems. In this paper, we present a novel approach to networked control systems (NCS) analysis and design that provides increased control performance for a set of control loops that share a single CAN network. This is achieved by enabling the following functionality for each control loop: first, standard periodic messaging is guaranteed to ensure stability, and second, non-periodic additional messaging is added whenever bandwidth is available in such a way that the aggregated control performance for all control loops is improved. To validate the presented approach, a proof-of-concept implementation is presented, and the extensive experimental results show the type of benefits that can be achieved as well as the resulting behavior depending on several key parameters. Moreover, it demonstrates that the approach can be implemented in practice.

This paper presents the schedulability analysis for control messages when networked control loops, built on top of the controller area network (CAN), are dynamically allocating bandwidth in terms of their controlled plants' dynamics. The bandwidth allocation policy is theoretically described by an optimization problem and practically solved by the distributed bitwise arbitration of CAN messages when message identifiers, i.e., priorities, reflect control applications demands. This poses the problem of assessing whether the set of real-time messages will meet their deadlines regardless of run-time priority changes. This is solved by a schedulability analysis based on recent results on worst-case response time techniques for real-time CAN applications. The analysis ends up with the schedulability test for this type of applications.

In many application areas, including control systems, careful management of system resources is key to providing the best application performance. Traditional control systems with multiple control loops statically allocate a fixed portion of the system resources to each controller based on their average or worst-case resource requirements. However, controllers' resource needs vary depending on the jobs they perform and the state of the systems they control. A controller of a plant operating close to its equilibrium requires fewer resources than a controller of a plant operating far from its equilibrium point. The Draco dynamic rate control system exploits this fact by dynamically allocating resources to control systems based on system state. Our research demonstrates that Draco provides significantly better overall control performance with much less resources than static controllers. Our experimental evaluation shows that in the control scenarios we examined Draco provides up to 25% better control performance with 30% less resources.

This paper reports the application of artificial neural networks for estimating reference evapotranspiration (ETo) as a function of local maximum and minimum air temperatures and exogenous relative humidity and evapotranspiration in twelve coastal locations of the autonomous Valencia region, Spain. The Penman-Monteith model for ETo prediction, as been proposed by the Food and Agriculture Organization of the United Nations (FAO) as the standard method for ETo forecast, has been used to provide the ANN targets. The number of stations where reliable climatic data are available for the application of the Penman-Monteith equation is limited. Thus, the development of more precise predicting tools for those cases where only scant climatic variables are available is desirable. Concerning models which demand scant climatic inputs, the proposed model provides performances with lower associated errors than the already existing temperature-based models, which only consider local data.

The standard design of control systems is based on theperiodic sampling. Every period the data is read from theinput, the control law is computed, and the output is writtento the actuators. However the periodicity of the samplinginstants is a constraint that arises from the ease of implementationand it is not strictly necessary in the control system.In this paper we present an execution model that samplesthe input "when needed". This model saves a considerableamount of computational resources. We show the schedulabilityanalysis for a set of control-driven tasks using bothFixed Priority (FP) and Earliest Deadline First (EDF).

Embedded control systems are often implemented in small microprocessors enabled with real-time technology. In this context, control laws are often designed according to discrete-time control systems theory and implemented as hard real-time periodic tasks. Standard discrete-time control theory mandates to periodically sample (input) and actuate (output). Depending on how input/output (I/O) operations are performed within the hard real-time periodic task, different control task models can be distinguished. However, existing task models present important drawbacks. They generate task executions prone to violate the periodic control demands, a problem known as sampling and latency jitter, or they impose synchronized I/O operations at each task job execution that produce a constant but artificially long I/O latency. In this paper, the one-shot task model for implementing control systems in embedded multitasking hard real-time platforms is presented. The novel control task model is built upon control theoretical results that indicate that standard control laws can be implemented considering only periodic actuation. Taking advantage of this property, the one-shot task model is shown to remove endemic problems for real-time control systems such as sampling and latency jitters. In addition, it can minimize the harmful effects that long I/O latencies have on control performance. Extensive simulations and real experiments show the feasibility and effectiveness of the novel task model, compared to previous real-time and/or control-based solutions.

In recent years, approaches to control performance and resource optimization for embedded control systems have been receiving increased attention. Most of them focus on theory, whereas practical aspects are omitted. Theoretical advances demand flexible real-time kernel support for multitasking and preemption, thus requiring more sophisticated and expensive software/hardware solutions. On the other hand, embedded control systems often have cost constraints related with mass production and strong industrial competition, thus demanding low-cost solutions. In this paper, it is shown that these conflicting demands can be softened and that a compromise solution can be reached. We advocate that recent research results on optimal resource management for control tasks can be implemented on simple multitasking preemptive real-time kernels targeting low-cost microprocessors, which can be easily built in-house and tailored to actual application needs. The experimental evaluation shows that significant control performance improvement can be achieved without increasing hardware costs.

Transient overload conditions may cause unpredictable performance degradations in computer controlled systems if not properly handled. To prevent such problems, a common technique adopted in periodic task systems is to reduce the workload by enlarging activation periods. In a digital controller, however, the variation applied on the task period also affects the control law, which needs to be recomputed for the new activation rate. If computing a new control law requires too much time to be performed at runtime, a set of controllers has to be designed offline for different rates and the system has to switch to the proper controller in the presence of an overload condition. In this paper, we present a method for reducing the number of controllers to be designed offline, while still guaranteeing a given control performance. The proposed approach has been integrated with the elastic scheduling theory to promptly react to overload conditions. The effectiveness of the proposed approach has been verified through extensive simulation experiments performed on an inverted pendulum. In addition, the method has been implemented on a real inverted pendulum. Experimental results and implementation issues are reported and discussed

This paper presents a resource management strategy for control tasks that maximizes control performance within the available resources by readjusting the task periods at runtime. A feedback scheduler is used to determine on-line the optimal task periods considering the response over a finite time horizon of the plants controlled by arbitrary linear control laws. We show how this problem can be expressed as an optimization problem, where the objective function relates the sampling periods to the transient responses of the controlled plants, and where restrictions are based on EDF schedulability constraints. For the general case, the solution of the optimization problem is computationally expensive, and thus, an approximate procedure to be executed on-line has been developed. We present simulation results that validate the presented approach

Today there is a significant body of results of resource management in real-time systems. However, most of them are based on "open-loop" strategies and techniques that do not take into account application demands to dynamically adjust their behavior. To overcome this problem by focusing on control applications, we show a novel scheduling technique: large error first (LEF). This scheduling algorithm uses feedback information from each controlled plant by the application in order to assign computing resources to control tasks. The LEF is used in simulation. By comparing the performance of LEF versus classical open-loop scheduling techniques, encouraging simulation results have been obtained. There are still many issues to be addressed with regard to LEF algorithm. This paper also shows these issues, with possible approaches that should be investigated further

An optimal bandwidth allocation policy for axis distributed control using networked control systems (NCS) is presented. First, the benefits of structuring highly articulated robots using networked control systems are discussed. Afterwards, an optimal bandwidth allocation policy for axes distributed control that allows to enhance robot tracking within the available bandwidth is introduced. It will be shown that axes control performance and thus tracking can be significantly improved by using feedback to dynamically allocate bandwidth to axis controllers as a function of the current state of each axis. Simulation results on a multiple axes robot corroborate our approach.

In many application areas, including control systems, careful management of system resources is key to providing the best application performance. Most traditional resource management techniques for real-time systems with multiple control loops are based on open-loop strategies that statically allocate a constant CPU share to each controller, independent of their current resource needs. This provides average control performance with minimal overhead but in general fails to provide the best performance possible within the available resources. We show that by using feedback to dynamically allocate resources to controllers as a function of the current state of their controlled systems, control performance can be significantly improved. We present an optimal resource allocation policy that maximizes control performance within the available resources and provide experimental results showing that the optimal policy 1) significantly increases control performance compared to traditional control system implementations (by more than 20% in our experiments), 2) maximizes control performance over other feedback-based policies, 3) saves resources when perturbations occur infrequently, and 4) incurs negligible overhead.

The increasing use of internet in the automation field has brought new challenges in the remote control, supervision and management of industrial processes. Specifically, process data information has to be available anywhere/anytime on the internet. This brings together two main problems: process data abstraction and process data accessibility. In this paper, we present a specification for an environment aimed to virtually model industrial plants, for their remote control, supervision and management. In this environment, we model real industrial plants by means of communication objects called virtual industrial devices (VID). A VID is a software component, which may contain other VIDs and represents, with different degrees of abstraction, an entity of an industrial plant. These objects communicate and are accessible through a peer-to-peer industrial communication protocol that allo15 messaging interchange between virtual industrial devices (and graphic user interfaces) regardless the communication technology that supports the actual messaging.

Closed-loop control systems are dynamic systems subject to perturbations. One of the main concerns of the control is to design controllers to correct or limit the deviation that transient perturbations cause in the controlled system response. The smaller and shorter the deviation, the better the achieved performance. However, such controllers have been traditionally implemented using fixed timing constraints (periods and deadlines). This precludes controllers to execute dynamically, accordingly to the system dynamics, which may lead to sub-optimal implementations: although higher execution rates may be preferable when reacting to perturbations in order to minimize the response deviations, they imply wastage of resources when the system is in equilibrium. In this paper we argue and demonstrate that the responsibility of maximizing the performance of closed-loop systems relies on both the controller designer and the scheduler. We show that the dynamic optimization of the quality of the controlled system response calls for (a) flexible control task timing constraints that deliver effective control performance; flexible constraints allow us to achieve faster reaction by adaptively choosing the controller sampling rate and completion time upon transient perturbations, (b) a quality-of-control (QoC) metric; it associates with each control task timing a quantitative value expressing control performance (in terms of the closed-loop system error), and (c) new scheduling approaches; their goal is to quickly react to perturbations by dynamically scheduling tasks based on the chosen control task execution parameters to maximize the QoC. This combination offers the possibility of taking scheduling decisions based on the control information for each control task invocation, rather than using fixed timing constraints with constant periods and deadlines.

Deals with the use of object oriented technologies in the modeling of industrial plants that have to be remotely monitored and/or controlled. The main goal is to propose a design methodology for obtaining the model of the so-called Virtual Plant, that a remote and certified user will use to access the real plant for performing command actions and/or monitoring. The type of applications and systems targeted must have autonomous behavior and be interconnected and accessible. Reliability, maintainability and flexibility are also required goals, as well as a high rate of reusability of the applications. The methodology has been applied to the remote process monitoring and control of manufacturing processes. The Virtual Plant Model is, in fact, the part of the plant that can be accessed by a certified remote client and thus it can be constituted by a set of sub-models, as many as different types of clients. The Virtual Plant resides inside the Application Server who is responsible of communicating with the cell controller and sends the image of the actual plant state (the Virtual Plant) as required by the remote client (monitoring) or sends the client commands to the cell controller.

The increasing application of flexible and powerful real-time distributed control systems is presently characterizing the industrial automation field. Such systems involve three main disciplines: control systems, real-time systems, and communication systems. Control systems, due their stringent timing constraints, demand real-time computing technology. In addition, communication systems are needed for the data messaging between field devices. We propose an integrated approach to the design and implementation of such systems. We show that by a separate control design and its posterior distributed implementation, the system performance may suffer degradation. That is, when control loops are closed over communication networks, timing problems, as communication induced varying delays, can appear, decreasing the control system performance, and even leading the system to instability. However, we show that by an adequate integrated approach, that takes advantage of control theory, real-time communication properties, an adequate timing analysis, and an appropriate distribution of the control functions, the system performance increases dramatically.

In this paper, we first identify the potential violations of control assumptions inherent in standard real-time scheduling approaches (because of the presence of jitters) that causes, degradation in control performance and may even lead to instability. We then develop practical approaches founded on control theory to deal with these violations. Our approach is based on the notion of compensations wherein controller parameters are adjusted at runtime for the presence of jitters. Through time and memory overhead analysis, and by elaborating on the implementation details, we characterize when offline and on-line compensations are feasible. Our experimental results confirm that our approach does compensate for the degraded control performance when EDF and FPS algorithms are used for scheduling the control tasks. Our compensation approach provides us another advantage that leads to better schedulability of control tasks. This derives from the potential to derive more flexible timing constraints, beyond periods and deadlines necessary to apply EDF and FPS. Overall, our approach provides guarantees offline that the control system will be stable at runtime-if temporal requirements are met at runtime-even when actual execution patterns are not known beforehand. With our approach, we can address the problems due to (a) sampling jitters, (b) varying delays between sampling and actuation, or (c) both-not addressable using traditional EDF and FPS based scheduling, or by previous real-time and control integration approaches.