It is shown that an explicit oblique projection nonlinear feedback controller is able to stabilize semilinear parabolic equations, with time-dependent dynamics and with a polynomial nonlinearity. The actuators are typically modeled by a finite number of indicator functions of small subdomains. No constraint is imposed on the sign of the polynomial nonlinearity. The norm of the initial condition can be arbitrarily large, and the total volume covered by the actuators can be arbitrarily small. The number of actuators depend on the operator norm of the oblique projection, on the polynomial degree of the nonlinearity, on the norm of the initial condition, and on the total volume covered by the actuators. The range of the feedback controller coincides with the range of the oblique projection, which is the linear span of the actuators. The oblique projection is performed along the orthogonal complement of a subspace spanned by a suitable finite number of eigenfunctions of the diffusion operator. For rectangular domains, it is possible to explicitly construct/place the actuators so that the stability of the closed-loop system is guaranteed. Simulations are presented, which show the semiglobal stabilizing performance of the nonlinear feedback.2010 Mathematics Subject Classification. 93D15, 93C10, 93B52, 93C20.is globally exponentially stable, with the feedback control operatorprovided the conditionholds true. In (1.3) and (1.4), 1 is the identity operator, λ > 0 is an arbitrary constant, and P E ⊥ M U M stands for the oblique projection in H onto the closed subspace U M along the closed subspace E ⊥ M . Where U M := span{Ψ i | i ∈ {1, 2, . . . , M }} is the linear span of our M linearly independent actuators and E M := span{e i | i ∈ M}, with M = {1, 2, . . . , M }, is the linear span of "the" first M linearly independent eigenfunctions of the diffusion operator A : D(A) → H, with domain D(A) d,c −→ H. Further, α M +1 is the (M + 1)st eigenvalue of A. The eigenvalues of A, denoted by α i , are supposed to satisfyIt is not difficult to see that we can follow the arguments in [31, Thms. 3.5, 3.6, and Rem. 3.8] to conclude that system (1.2) is still stable if we replace (1.4) by F(y) = Ay + λ1y. Observe that (1.5) concerns a single M ∈ N and a single pair (U M , E M ). The following result, which follows straightforwardly from the sufficiency of (1.5), concerns a sequence of pairs (U M , E M ) M ∈N . Theorem 1.2. Assume that we can construct a sequence (U M , E M ) M ∈N such that P E ⊥ M U M L(H) ≤ C P remains bounded, with C P > 0 independent of M . Then system (1.2) is globally exponentially stable for large enough M , with F(y) ∈ {λ1y, Ay + λ1y}. P E M (ςA+λ1)P E M ,M,N U M , because P E M commutes with both A and 1 and because P E ⊥ M U M P E M = P E ⊥ M U M . Notice also that when F is linear and N = 0, then y → K F ,M U M (t, y) is linear, while y → K F ,M,N U M (t, y) is nonlinear.1.2. Motivation and short comparison to previous works. We find systems in form (1.1) when, for example, we want to stabilize a system to a...