Author :
Mattingley, Jacob ; Wang, Yang ; Boyd, Stephen
Abstract :
In this article we have shown that receding horizon control offers a straightforward method for designing feedback controllers that deliver good performance while respecting complex constraints. A designer specifies the RHC controller by specifying the objective, constraints, prediction method, and horizon, each of which has a natural choice suggested directly by the application. In more traditional approaches, such as PID control, a designer tunes the controller coefficients, often using trial and error, to handle the objectives and constraints indirectly. In contrast, RHC con trollers can often obtain good performance with little tuning. In addition to the straightforward design process, we have seen that RHC controllers can be implemented in real time at kilohertz sampling rates. These speeds are useful for both real-time implementation of the controller as well as rapid Monte Carlo simulation for design and testing purposes. Thus, receding horizon control can no longer be considered a slow, computationally intensive policy. Indeed, RHC can be applied to a wide range of control problems, including applications involving fast dynamics.
Keywords :
Monte Carlo methods; control system synthesis; feedback; predictive control; Monte Carlo simulation; PID control; feedback controller design; prediction method; receding horizon control; trial-and-error; Convex functions; Feedback control; Generators; Nonlinear dynamical systems; Predictive control; Real time systems;