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Reconfiguration in Flight Critical Aerospace Applications
Published in Jitendra R. Raol, Ajith K. Gopal, Mobile Intelligent Autonomous Systems, 2016
Partitions across APEX-IMA platform are scheduled using cyclic, static table-driven pre-defined fixed priority and non-pre-emptive schedule. This provides resource access to all the partitions based on preset duration. Schedules are created offline constraining all partitions at least once. Some may appear more than once, depending upon the relationship between a partition period and length of the schedule. Partition can contain one or more application processes and each process having additional attributes such as Period: Processes can be periodic or aperiodic. Periodic process have fixed period defined between successive releases of the process. Aperiodic processes are set with a unique value to indicate they are not periodic and hence they do not have fixed period.Time capacity: Each process has fixed time for execution and has a deadline by which time the process should complete execution, which is a constant value.Priority: Each process has fixed priorities. This is the default and current priority of the process, based on the selection. The priority of the processes is pre-fixed as part of static scheduling.State: Process state can be dormant, ready, waiting or running based on the actual execution condition.
Interprocess Communication Based on Shared Variables
Published in Ivan Cibrario Bertolotti, Gabriele Manduchi, Real-Time Embedded Systems, 2017
Ivan Cibrario Bertolotti, Gabriele Manduchi
From Section 3.4 in Chapter 3, we know that the process state diagram already comprises a state, the Blocked state, reserved for processes that cannot proceed for some reason, for instance, because they are waiting for an I/O operation to complete. Any process belonging to this state does not proceed with execution but does so without wasting processor cycles and without preventing other processes from executing in its place. This kind of wait is often called passive wait just for this reason.
A model-based tracking control scheme for nonlinear industrial processes involving joint unscented Kalman filter
Published in Journal of Control and Decision, 2023
Sanjay Bhadra, Atanu Panda, Parijat Bhowmick, Somasundar Kannan
In this paper, we consider a class of finite dimensional, causal, nonlinear, well-defined, continuous-time systems described as where denotes the state vector, is the control input vector, is the output vector. While , and represent the external disturbance, process noise and measurement noise. The matrix models the effects of on the process state x. The following technical assumptions are satisfied by the class of systems described in (1a)–(1b).
A mathematical multi-dimensional mechanism to improve process migration efficiency in peer-to-peer computing environments
Published in Cogent Engineering, 2018
Ehsan Mousavi Khaneghah, Reyhaneh Noorabad Ghahroodi, Amirhosein Reyhani ShowkatAbad
Generator space, as demonstrated on Equation (6), is defined on Initial ProcessState, next state, Processstate sets. The first set indicates the state of the available process before starting the migration operation, whereas the second set indicates the state of the available process after the migration operation has been done. The state of the process explains the state of load balancing in the system, allocated time to the process, and the waiting time of the process on the local machine. This data structure is described by five process generator space parameters. The SizeGDP variable indicates which related mechanism can be matched to which size of the processes. Table 3 shows the span of suitable process size for each mechanism.
Application of the theory of Markov chains to theoretical study of processes in a circulating fluidized bed
Published in Particulate Science and Technology, 2019
Andrey Mitrofanov, Vadim Mizonov, Arnold Camelo, Katia Tannous
The height of the reactor is separated into m perfectly mixed cells of the height Δx. The cross-section area of the riser is taken as the conditional unit. The current state of the particle content distribution is presented by the column vector S = {Sj} of the size mx1 where j is the cell number counted form the riser’s bottom. The successive states of the process are observed in the discrete moments of time tk = (k –1)Δt where Δt is the time of transition duration and k is the transition number (discrete analog of time). Evolution of the process state is described by the recurrent matrix equalities: where P are the matrices of transition probabilities that contain the elements describing the fractions exchange between neighboring cells. The rule of their construction is described in detail in Mizonov, Zhukov, and Zaitsev (2014). It is necessary to remind that any Markov chain model manipulates with transition probabilities, which are dimensionless and cannot exceed 1. The convection transition probabilities are connected with the dimensional physical velocities by the equality w = WΔt/Δx where W is the dimensional gas flow velocity, w is the dimensionless convection transition probability, Δx is the cell height. The same equality must be used for any velocity participating in the model. However, in order to avoid using too many terms, we shall call w as the gas flow velocity having in mind its dimensionless form. The condition w<1 can be met by the right choice of the values Δt and Δx.