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| 2. |
- Barzegaran, Mohammadreza, et al.
(författare)
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Performance Optimization of Control Applications on Fog Computing Platforms Using Scheduling and Isolation
- 2020
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Ingår i: IEEE Access. - 2169-3536. ; 8, s. 104085-104098
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we address mixed-criticality applications characterized by their safety criticality and time-dependent performance, which are virtualized on a Fog Computing Platform (FCP). The FCP is implemented as a set of interconnected multicore computing nodes, and brings computation and communication closer to the edge of the network, where the machines are located in industrial applications. We use partitioning and static-cyclic scheduling to provide isolation among mixed-criticality tasks and to guarantee their timing requirements. The temporal and spatial isolation is enforced via partitions, which execute tasks with the same criticality level. We consider that the tasks are scheduled using static cyclic scheduling. We are interested in determining the mapping of tasks to the cores of the fog nodes, the assignment of tasks to the partitions, the partition schedule tables, and the tasks’ schedule tables, such that the Quality-of-Control for the control tasks is maximized and we meet the timing requirements for all tasks, including tasks with lower-criticality levels. We are also interested in determining the periods for control tasks to balance the schedulability and the control performance. We have proposed a Simulated Annealing metaheuristic, which relies on a heuristic algorithm for determining the schedules and partitions, to solve this optimization problem. Our optimization strategy has been evaluated on several test cases, showing the effectiveness of the proposed method.
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| 3. |
- Cava, José Manuel Gonzáles, et al.
(författare)
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Robust PID control of propofol anaesthesia: uncertainty limits performance, not PID structure
- 2021
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607. ; 198, s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limitations associated with using a filtered PID controller, as compared to a high-order controller, represented through a Youla parameter.Methods: The comparison consists of a two-steps methodology. First, two robust optimal filtered PID controllers, considering the effect of the inter-patient variability, are synthesised. A set of 47 validated paediatric pharmacological models, identified from clinical data, is used to this end. This model set provides representative inter-patient variability Second, individualised filtered PID and Youla controllers are synthesised for each model in the set. For fairness of comparison, the same performance objective is optimised for all designs, and the same robustness constraints are considered. Controller synthesis is performed utilising convex optimisation and gradient-based methods relying on algebraic differentiation. The worst-case performance over the patient model set is used for the comparison.Results: Two robust filtered PID controllers for the entire model set, as well as individual-specific PID and Youla controllers, were optimised. All considered designs resulted in similar frequency response characteristics. The performance improvement associated with the Youla controllers was not significant compared to the individually tuned filtered PID controllers. The difference in performance between controllers synthesized for the model set and for individual models was significantly larger than the performance difference between the individual-specific PID and Youla controllers. The different controllers were evaluated in simulation. Although all of them showed clinically acceptable results, the robust solutions provided slower responses.Conclusion: Taking the same clinical and technical considerations into account for the optimisation of the different controllers, the design of individual-specific solutions resulted in only marginal differences in performance when comparing an optimal Youla parameter and its optimal filtered PID counterpart. The inter-patient variability is much more detrimental to performance than the limitations imposed by the simple structure of the filtered PID controller.
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| 4. |
- Cervin, Anton, et al.
(författare)
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LQG-Optimal versus Simple Event-Based PID Controllers
- 2020
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Ingår i: 2020 American Control Conference (ACC). - 9781538682661
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Konferensbidrag (refereegranskat)abstract
- In this paper, we study event-based PID control from an optimal stochastic control perspective. The purpose is to better understand what implementation features are critical for achieving good event-based PID performance. For this end, we formulate an LQG control design problem for a double integrator process with an integral disturbance, where the solution is an ideal PID controller. We then consider the trade-off between LQG cost and average sampling rate and give an interpretation of the optimal sampled-data controller and event-based sampling policy in terms of PID control. Based on insights from the optimal solution, we finally discuss how suboptimal but simple event-based PID controllers can be implemented. The proposed implementation is evaluated in a simulation study and compared to earlier work in event-based PID control. The results highlight the importance of considering both the triggering rule and the transmitted information in order to obtain an event-based PID controller with good performance.
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| 5. |
- Nyberg Carlsson, Max, et al.
(författare)
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Timing-Robust Control over the Cloud Using On-Line Parametric Optimization
- 2023
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Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - 2405-8963. ; 56:2, s. 5560-5565
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present a heuristic method for adapting a networked linear feedback controller to improve its robustness to timing complications, such as long delays, aborted computations, and dropped packets. The core concept of the approach is to log successful sampling and actuation events and then, at discrete time-points, use non-convex parametric optimization to improve the expected performance of the controller under the assumption that the future timing behavior will be similar to the current one. To reduce the time complexity of the optimization algorithm, automatic differentiation is integrated for efficient gradient descent. The approach is evaluated on a physical ball and beam plant, where both the controller and optimization algorithm can be located in the Cloud.
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| 6. |
- Rosdahl, Christian, et al.
(författare)
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Dual Control by Reinforcement Learning Using Deep Hyperstate Transition Models
- 2022. - 12
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Ingår i: IFAC papers online. - : Elsevier BV. - 2405-8963. ; 55, s. 395-401
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Konferensbidrag (refereegranskat)abstract
- In dual control, the manipulated variables are used to both regulate the system and identify unknown parameters. The joint probability distribution of the system state and the parameters is known as the hyperstate. The paper proposes a method to perform dual control using a deep reinforcement learning algorithm in combination with a neural network model trained to represent hyperstate transitions. The hyperstate is compactly represented as the parameters of a mixture model that is fitted to Monte Carlo samples of the hyperstate. The representation is used to train a hyperstate transition model, which is used by a standard reinforcement learning algorithm to find a dual control policy. The method is evaluated on a simple nonlinear system, which illustrates a situation where probing is needed, but it can also scale to high-dimensional systems. The method is demonstrated to be able to learn a probing technique that reduces the uncertainty of the hyperstate, resulting in improved control performance.
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| 7. |
- Ruuskanen, Johan, et al.
(författare)
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Distributed online extraction of a fluid model for microservice applications using local tracing data
- 2022
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Ingår i: 2022 IEEE 15th International Conference on Cloud Computing (CLOUD).
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Konferensbidrag (refereegranskat)abstract
- Dynamic resource management is a difficult problem in modern microservice applications. Many proposed methods rely on the availability of an analytical performance model, often based on queueing theory. Such models can always be hand-crafted, but this takes time and requires expert knowledge. Various methods have been proposed that can automatically extract models from logs or tracing data. However, they are often intricate, requiring off-line stages and advanced algorithms for retrieving the service-time distributions. Furthermore, the resulting models can be complex and unsuitable for online evaluation. Aiming for simplicity, we in this paper introduce a general queuing network model for microservice applications that can be (i) quickly and accurately solved using a refined mean-field fluid model and (ii) completely extracted at runtime in a distributed fashion from common local tracing data at each service. The fit of the model and the prediction accuracies under system perturbations are evaluated in a cloud-based microservice application and are found to be accurate.
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| 8. |
- Ruuskanen, Johan, et al.
(författare)
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Improving the Mean-Field Fluid Model of Processor Sharing Queueing Networks for Dynamic Performance Models in Cloud Computing
- 2021
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Ingår i: Performance Evaluation. - : Elsevier BV. - 0166-5316. ; 151
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Tidskriftsartikel (refereegranskat)abstract
- Resource management in cloud computing is a difficult problem, as one is often tasked with balancing between adequate service to clients and cost minimization in dynamic environments of many interconnected components. To make correct decisions in these environments, good performance models are necessary. A common modeling methodology is to use networks of queues, but as these are prohibitively expensive to evaluate for many real-time applications, different approximation methods for important metrics are frequently employed. One such method—that provides both transient solutions and short, scalable computation times—is the fluid model, which approximates the dynamics of the mean queue lengths using a system of ordinary differential equations. However, finding a fluid model that can adequately approximate an arbitrary queueing network is in general difficult. In this paper, we extend the state of the art with the following three contributions. First, we show that for any mixed multiclass queueing network of processor sharing and delay queues with phase-type service time distributions, such a fluid model can be found via the mean-field approximation. Furthermore, we propose an improved model based on smoothing of the processor share function that improves the performance of certain systems. Finally, using the smoothed mean-field model, we introduce an accurate closed-form approximation of the response time CDF over any subset of classes and queues. The contributions are further evaluated in a large simulation experiment, which shows that they can be used to accurately predict performance metrics under some system perturbations common in cloud computing.
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| 9. |
- Ruuskanen, Johan, et al.
(författare)
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On Innovation-Based Triggering for Event-Based Nonlinear State Estimation Using the Particle Filter
- 2020
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Ingår i: 2020 19th European Control Conference (ECC).
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Konferensbidrag (refereegranskat)abstract
- Event-based sampling has been proposed as a general technique for lowering the average communication rate, energy consumption and computational burden in remote state estimation. However, the design of the event trigger is critical for good performance. In this paper, we study the combination of innovation-based triggering and state estimation of nonlinear dynamical systems using the particle filter. It is found that innovation-based triggering is easily incorporated into the particle filter framework, and that it vastly outperforms the classical send-on-delta scheme for certain types of nonlinear systems. We further show how the particle filter can be used to jointly precompute the future state estimates and trigger probabilities, thus eliminating the need for periodic observer-to-sensor communication, at the cost of increased computational burden at the observer. For wireless, battery-powered sensors, this enables the radio to be turned off between sampling events, which is key to saving energy.
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| 10. |
- Vreman, Nils, et al.
(författare)
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Deadline-Miss-Adaptive Controller Implementation for Real-Time Control Systems
- 2022
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Ingår i: 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS).
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Konferensbidrag (refereegranskat)abstract
- The policy used to implement a control algorithm in a real-time system can significantly affect the quality of control. In this paper, we present a method to adapt the controller implementation, with the objective to improve the system’s performance under real-time faults. Our method compensates for missing state updates by adapting the controller parameters according to the number of consecutively missed deadlines. It extends the state-of-the-art by considering dynamic controllers, which have had limited coverage in previous literature. The adaptation mechanism can be precomputed offline, solely based on knowledge about the controller and not on the controlled plant. The approach is indifferent to the control design, as well as to the scheduling policy, and can be automatically realised by the operating system, thus improving the robustness of the control system to intermittent and unexpected real-time faults. We develop a stochastic performance analysis method and apply it to both a real plant and numerous simulated plants to evaluate our adaptive controller. Complementary to the stochastic analysis, we also do worst-case stability analysis of the resulting system. The results confirm the conjuncture that the adaptive controller improves both the performance and robustness in the presence of deadline misses.
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