Sentence examples for transformed constraints from inspiring English sources

For easy identification, we rename the transformed constraints in (18) and (19) as (overline {C1.1}) and (overline {C1.2}), respectively.

Effectively, the search is not conducted anymore for a single optimum, but for a set of Pareto optima between the original objective and transformed constraints.

The transformed constraints are convex in p ¯ = p ¯ 0, p ¯ 1, …, p ¯ C − 1 and p ¯ var = p 0, var, p 1, var, …, p C − 1, var since all left-hand sides are compositions of non-negative sum of exponentials, which are convex functions with affine mappings as shown in [28].

Through the simulation, we also perform a comparison study between BLF-Tan and the logarithmic BLF (BLF-Log) to illustrate the difference in control performance, and show that the performance of asymmetric BLF-Tan based controller depends on the position of initial tracking error with respect to the transformed constraint boundary.

Notice that, as earlier, each column of the transformed constraint matrices includes exactly one nonzero (unit) element so that ({mathbf{e}}_{N}^{prime } {mathbf{G}}_{N times NM} {mathbf{E}}_{J times NM}^{prime } = {mathbf{e}}_{M}^{prime } {mathbf{H}}_{M times NM} {mathbf{E}}_{J times NM}^{prime } = {mathbf{e}}_{J}^{prime }).

Vectorization converts classical scalar optimization formulation, which strictly separates the objective from constraints, into a vector-based optimization, transforming constraints into objectives.

In order to make (P2) tractable, we first transform constraint C2 of (P2) into a convex form.

Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control.

Secondly, the objectives whose values vary within small ranges during the optimization process are transformed into constraints.

The combinatorial conditions for hybrid distance-bearing information were derived by transforming bearing constraints into direction constraints which were studied in discrete geometry literature.

At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach.