  The paper deals with stochastic control problems associated with $H_2$
performance indices such as energy or power norms or energy measurements when
norms are not defined. They apply to a class of systems for which a stochastic
process conveys the underlying uncertainties, known as CSVIU (Control and State
Variation Increase Uncertainty). These indices allow various emphases from
focusing on the transient behavior with the discounted norm to stricter
conditions on stability, steady-state mean-square error and convergence rate,
using the optimal overtaking criterion -- the long-run average power control
stands as a midpoint in this respect. A critical advance regards the explicit
form of the optimal control law, expressed in two equivalent forms. One takes a
perturbed affine Riccati-like form of feedback solution; the other comes from a
generalized normal equation that arises from the nondifferentiable local
optimal problem. They are equivalent, but the latter allows for a search method
to attain the optimal law. A detectability notion and a Riccati solution grant
stochastic stability from the behavior of the norms. The energy overtaking
criterion requires a further constraint on a matrix spectral radius. With these
findings, the paper revisits the emerging of the inaction solution, a prominent
feature of CSVIU models to deal with the uncertainty inherent to poorly known
models. Besides, it provides the optimal solution and the tools to pursue it.
