Active control of structures against environmental loads such as those due to wind and earthquakes has received much attention recently. Feasibility studies, numerical and experimental, have shown that it is a viable alternative to conventional methods in enhancing the performance of structures under such loadings. Most of the research thus far has concentrated on developing mathematical models and algorithms based on optimal control theory and the necessary hardware to implement the control. Research on control based on neural networks has been very limited in spite of the potential advantages of this method such as its inherent ability to handle nonlinear systems, incorporate leads or delays, and recover from partial system failure. This paper presents a method of control of structures based on neural networks. The rationale for neural network-based control is first outlined, followed by a brief description of the analytical and experimental investigations, and finally illustrative numerical examples are given of control of a non-linear single-degree-of-freedom structure by neural net.