A survey on gain-scheduled control and filtering for parameter-varying systems

Copyright © 2014 Guoliang Wei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This paper presents an overview of the recent developments in the gain-scheduled control and filtering problems for the parameter-varying systems. First of all, we recall several important algorithms suitable for gain-scheduling method including gain-scheduled proportional-integral derivative (PID) control, H 2, H ∞ and mixed H 2 / H ∞ gain-scheduling methods as well as fuzzy gain-scheduling techniques. Secondly, various important parameter-varying system models are reviewed, for which gain-scheduled control and filtering issues are usually dealt with. In particular, in view of the randomly occurring phenomena with time-varying probability distributions, some results of our recent work based on the probability-dependent gain-scheduling methods are reviewed. Furthermore, some latest progress in this area is discussed. Finally, conclusions are drawn and several potential future research directions are outlined.The National Natural Science Foundation of China under Grants 61074016, 61374039, 61304010, and 61329301; the Natural Science Foundation of Jiangsu Province of China under Grant BK20130766; the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning; the Program for New Century Excellent Talents in University under Grant NCET-11-1051, the Leverhulme Trust of the U.K., the Alexander von Humboldt Foundation of Germany

An EPTAS for machine scheduling with bag-constraints

Machine scheduling is a fundamental optimization problem in computer science. The task of scheduling a set of jobs on a given number of machines and minimizing the makespan is well studied and among other results, we know that EPTAS's for machine scheduling on identical machines exist. Das and Wiese initiated the research on a generalization of makespan minimization, that includes so called bag-constraints. In this variation of machine scheduling the given set of jobs is partitioned into subsets, so called bags. Given this partition a schedule is only considered feasible when on any machine there is at most one job from each bag. Das and Wiese showed that this variant of machine scheduling admits a PTAS. We will improve on this result by giving the first EPTAS for the machine scheduling problem with bag-constraints. We achieve this result by using new insights on this problem and restrictions given by the bag-constraints. We show that, to gain an approximate solution, we can relax the bag-constraints and ignore some of the restrictions. Our EPTAS uses a new instance transformation that will allow us to schedule large and small jobs independently of each other for a majority of bags. We also show that it is sufficient to respect the bag-constraint only among a constant number of bags, when scheduling large jobs. With these observations our algorithm will allow for some conflicts when computing a schedule and we show how to repair the schedule in polynomial-time by swapping certain jobs around

The predictive functional control and the management of constraints in GUANAY II autonomous underwater vehicle actuators

Autonomous underwater vehicle control has been a topic of research in the last decades. The challenges addressed vary depending on each research group's interests. In this paper, we focus on the predictive functional control (PFC), which is a control strategy that is easy to understand, install, tune, and optimize. PFC is being developed and applied in industrial applications, such as distillation, reactors, and furnaces. This paper presents the rst application of the PFC in autonomous underwater vehicles, as well as the simulation results of PFC, fuzzy, and gain scheduling controllers. Through simulations and navigation tests at sea, which successfully validate the performance of PFC strategy in motion control of autonomous underwater vehicles, PFC performance is compared with other control techniques such as fuzzy and gain scheduling control. The experimental tests presented here offer effective results concerning control objectives in high and intermediate levels of control. In high-level point, stabilization and path following scenarios are proven. In the intermediate levels, the results show that position and speed behaviors are improved using the PFC controller, which offers the smoothest behavior. The simulation depicting predictive functional control was the most effective regarding constraints management and control rate change in the Guanay II underwater vehicle actuator. The industry has not embraced the development of control theories for industrial systems because of the high investment in experts required to implement each technique successfully. However, this paper on the functional predictive control strategy evidences its easy implementation in several applications, making it a viable option for the industry given the short time needed to learn, implement, and operate, decreasing impact on the business and increasing immediacy.Peer ReviewedPostprint (author's final draft

Analyzing the effect of gain time on soft task scheduling policies in real-time systems

In hard real-time systems, gain time is defined as the difference between the Worst Case Execution Time (WCET) of a hard task and its actual processor consumption at runtime. This paper presents the results of an empirical study about how the presence of a significant amount of gain time in a hard real-time system questions the advantages of using the most representative scheduling algorithms or policies for aperiodic or soft tasks in fixed-priority preemptive systems. The work presented here refines and complements many other studies in this research area in which such policies have been introduced and compared. This work has been performed by using the authors' testing framework for soft scheduling policies, which produces actual, synthetic, randomly generated applications, executes them in an instrumented Real-Time Operating System (RTOS), and finally processes this information to obtain several statistical outcomes. The results show that, in general, the presence of a significant amount of gain time reduces the performance benefit of the scheduling policies under study when compared to serving the soft tasks in background, which is considered the theoretical worst case. In some cases, this performance benefit is so small that the use of a specific scheduling policy for soft tasks is questionable. © 2012 IEEE.This work is partially funded by research projects PROMETEO/2008/051, CSD2007-022, and TIN2008-04446.Búrdalo Rapa, LA.; Terrasa Barrena, AM.; Espinosa Minguet, AR.; García Fornes, AM. (2012). Analyzing the effect of gain time on soft task scheduling policies in real-time systems. IEEE Transactions on Software Engineering. 38(6):1305-1318. https://doi.org/10.1109/TSE.2011.95S1305131838

Investigating the Perceived Human Errors in 4D-BIM Construction Scheduling

Four-dimensional building information modeling (4D-BIM or 4D Scheduling) is well known to benefit the construction industry in many ways. 4D-BIM is an effective scheduling technique which integrates traditional scheduling methods and advanced visualization of the construction sequences in a 3D environment. Despite the potential benefits of 4D-BIM to improve scheduling quality, errors still often occur in construction schedules. The objective of this research is to understand the association between human errors and computer-aided scheduling. This paper focuses on examining the current practices of 4D-scheduling to gain insights on potential errors during the process of scheduling. Furthermore, the paper discusses a set of root causes of scheduling errors based on different types of human errors in cognition error theories. The research determined human errors through an integrated approach of literature review and a survey. The results of this study are expected to provide new knowledge about what human errors that commonly occur during the scheduling processing using BIM and their root causes. This study also discusses a few error reduction/prevention methods that can help BIM practitioners, schedulers, organizations to avoid perceived human errors during 4D-BIM work process

Velocity Estimate Following Air Data System Failure

Modern high performance aircraft can provide amazing performance due in part to their advanced flight control systems that require gain scheduling to provide optimum performance over a huge flight envelope. In modern fighter aircraft, this gain scheduling is a function of airspeed, and almost all of the research involving aircraft gain scheduling assumes aircraft airspeed to be a known quantity. The purpose of this research was to investigate a method of determining an aircraft’s airspeed in the event of total air data system failure. The process began by combining known aircraft information following an air data system failure to determine an estimate of the inertial velocity. Then, an innovative airspeed estimation algorithm was developed using Kalman filtering with geometric concepts based on the velocity triangle that defines the relationship between airspeed, wind speed, and groundspeed. This algorithm used the inertial velocity and heading and provided a real-time estimate of the current wind and the aircraft’s true airspeed, which can be used in the flight control system for gain scheduling. The true airspeed estimate was also converted to calibrated airspeed for display in the cockpit to provide the pilot situational awareness. The culmination of this effort resulted in a successful flight test program as part of a Test Management Project at the United States Air Force Test Pilot School. The project consisted of two ground test and six flight test evaluation sorties. The average true airspeed error from the estimator algorithm during in-flight maneuvers was determined to be 12 knots, non-divergent, and minimally variable. The results of this research clearly showed the potential of the algorithm to determine an aircraft’s airspeed in the event of an air data system failure. Recommendations for future research and improvements to the operation of the velocity estimator algorithm are discussed

Optimal routing and scheduling for a simple network coding scheme

We consider jointly optimal routing, scheduling, and network coding strategies to maximize throughput in wireless networks. While routing and scheduling techniques for wireless networks have been studied for decades, network coding is a relatively new technique that allows for an increase in throughput under certain topological and routing conditions. In this work we introduce k-tuple coding, a generalization of pairwise coding with next-hop decodability, and fully characterize the region of arrival rates for which the network queues can be stabilized under this coding strategy. We propose a dynamic control policy for routing, scheduling, and k-tuple coding, and prove that our policy is throughput optimal subject to the k-tuple coding constraint. We provide analytical bounds on the coding gain of our policy, and present numerical results to support our analytical findings. We show that most of the gains are achieved with pairwise coding, and that the coding gain is greater under 2-hop than 1-hop interference. Simulations show that under 2-hop interference our policy yields median throughput gains of 31% beyond optimal scheduling and routing on random topologies with 16 nodes.National Science Foundation (U.S.) (grant CNS-0915988)United States. Office of Naval Research (grant N00014-12-1-0064)United States. Office of Naval Research. Multidisciplinary University Research Initiative (grant number W911NF-08-1-0238)United States. Air ForceUnited States. Dept. of Defense (Contract No. FA8721-05-C-0002