Multiple Kernel Learning issue

Suppose I have a set of normalised Kernels that line on the unit semi definite cone. While combining these kernels in a MKL algorithm how should I set the constraints on the optimization problem so that the resultant kernel \sum{i}^{N} \theta{i} K_{i} also lie on the unit semi definite cone ?