We consider a discrete time time-axis, T = 0,1,2,….
The manager controls playing/recording of scenarios by using a discrete time representation which divides time into time-slice quantas.
Starting from the robust-optimal design based on the sensitivity function of a continuous time PID controller, a discrete time equivalent is built.
The algorithms for particle ejection and loading find the value at a discrete time from those at a given time.
This paper considers the problem of finding a controller for a discrete time linear periodically time-varying system with structured parametric uncertainty which achieves robust ℓ2 semi-norm performance (the equivalent of robust H2 norm performance for time-varying systems).
Let (t^{text {(dis).}}_{infe}) be an infection time of a discrete time random walk and (t^{text {(con).}}_{infe}) an infection time of a continuous time random walk.
We simulate the time paths using a discrete time increment Δt with a length of 1 month, equivalent to 1/12 year.
But calculating the time derivative of a discrete time series is numerically unstable to even relatively small amounts of random noise.
Stochastic epidemic models treat information propagation as a discrete time process (Discrete Time Markov Chain) [7, 14] being more suitable for small-scale systems whereas deterministic epidemic models assume continuous processes relying on the law of large numbers and applying differential equations or inclusions [15, 16], thus being more suitable for large-scale systems.
In this section, we consider exponentially practical stability problems for the following four cases: a discrete time system with disturbance, a discrete time singular system with disturbance, a discrete time system with delay and disturbance, and a discrete time singular system with delay and disturbance.
The output is estimated from a discrete time representation of the continuous time model and the tuning of the controllers can be made by any classical control design approach for systems without delay.
