The geometry optimization using direct inversion in the iterative subspace (GDIIS) has been implemented in a number of computer programs and is found to be quite efficient in the quadratic vicinity of a minimum. However, far from a minimum, the original method may fail in three typical ways: (a) convergence to a nearby critical point of higher order (e.g. transition structure), (b) oscillation around an inflection point on the potential energy surface, (c) numerical instability problems in determining the GDIIS coefficients. An improved algorithm is presented that overcomes these difficulties. The modifications include: (a) a series of tests to control the construction of an acceptable GDIIS step, (b) use of a full Hessian update rather than a fixed Hessian, (c) a more stable method for calculating the DIIS coefficients. For a set of small molecules used to test geometry optimization algorithms, the controlled GDIIS method overcomes all of the problems of the original GDIIS method, and performs as well as a quasi-Newton RFO (rational function optimization) method. For larger molecules and very tight convergence, the controlled GDIIS method shows some improvement over an RFO method. With a properly chosen Hessian update method, the present algorithm can also be used in the same form to optimize higher order critical points.