This paper introduces a novel bang–bang sliding control of a class of single-input bilinear systems. The sliding function is chosen via the well-known pole-assignment method for linear time-invariant systems. Importantly, the bang–bang sliding control generates a reaching-and-sliding region and a stable-sliding region, each expressed by a set of linear inequalities. Both regions comprise the eq...

We revisit recent results about optimal periodic control for scalar dynamics with input integral constraint, under lack of convexity and concavity. show that in this more general framework, the solutions are bang-singular-bang generalize bang-bang convex case purely singular concave one. introduce a non-local slope condition to characterize arcs. The illustrated on class bioprocesses models.

The Network Enabled Optimization Server (NEOS) for solving tough optimal control problems (OCPs) is introduced. Though NEOS is generally used to solve static optimization problems, in solving dynamic optimizations (OCPs) in a general form, we show that the NEOS Server has some advantages over the existing dedicated optimal control software packages. After a step by step introduction of how to s...

Here, we assume that Ω is a bounded domain in R, 1 ≤ n ≤ 3, with a Lipschitz boundary Γ, Q = Ω × (0, T ), Σ = Γ × (0, T ), and y0 ∈ L∞(Ω). BV (0, T ) denotes the space of bounded variation functions defined in (0, T ), with 0 < T < ∞ given. The controllers in (P) are supposed to be separable functions with respect to fixed spatial shape functions gj and free temporal amplitudes uj . The specifi...