Hybrid Parametrically Optimized Adaptive Control Framework for Generator Reactor Pressurizer

Many processes (e.g., power grid, mechanical processes, such as power plant cooling systems, etc.) exhibit non-linear behavior. Various control strategies have been used with such processes, depending on the characteristics of the system. However, a single control method alone may not always provide optimal stable performance, based on the process conditions. This paper proposes a hybrid adaptive control architecture. The main purpose of the proposed hybrid control architecture is to provide an adaptive control method that produces optimized performance for a nonlinear process for improved performance during transient conditions. The hybrid adaptive control technique combines controllers with separate cost functions (each desirable during different process conditions) to leverage the strengths of each control method. The paper first introduces the proposed control architecture (i.e., mathematical models for the hybrid control architecture). A simulation example is presented, based on a real-life nonlinear system model (e.g., pressurizer), to validate the proposed control method for a physical nonlinear process (pressure control), with performance compared to conventional control and other adaptive control methods. It is demonstrated that the proposed control method reduces the peak time and overshoot by 18% when compared to a linear quadratic regulator (LQR) acting alone.