Comparison of Gradient Estimation Methods for Real-time Optimization
Various real-time optimization techniques proceed by controlling the gradient to zero. These methods primarily differ in the way the gradient is estimated. This paper compares various gradient estimation methods. It is argued that methods with model-based gradient estimation converge faster but can be inaccurate in the presence of plant-model mismatch. In contrast, model-free methods are accurate but typically take longer to converge.