Summary: This paper studies the following form of nonlinear stochastic partial differential equation: \[ \begin{multlined} -d\Phi_ t=\inf_{v\in U}\left\{\frac12 \sum_{i,j}[\sigma\sigma^*]_{ij}(x,v,t)\partial_{x_ ix_ j}\Phi_ t(x)+\sum_ i b_ i(x,v,t)\partial_{x_ i}\Phi_ t(x)+L(x,v,t)+\right. \\ \left.+\sum_{i,j}\sigma_{ij}(x,v,t)\partial _{x_ i}\Psi_{j,t}(x)\right\}\,dt-\Psi_ t(x)\,dW_t, \Psi_T(x)=h(x),\end{multlined} \] where the coefficients \(\sigma_{ij}\), \(b_i\), \(L\), and the final datum \(h\) may be random. The problem is to find an adapted pair \((\Phi,\Psi)(x,t)\) uniquely solving the equation. The classical Hamilton-Jacobi-Bellman equation can be regarded as a special case of the above problem. An existence and uniqueness theorem is obtained for the case where \(\sigma\) does not contain the control variable \(v\). An optimal control interpretation is given. The linear quadratic case is discussed as well.