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This paper presents a tube-based robust economic MPC controller for discrete-time nonlinear systems that are perturbed by disturbance inputs. The proposed algorithm minimizes a modified economic objective function which considers the worst cost within a tube around the solution of the associated nominal system. Recursive feasibility and an a-priori upper bound to the closed-loop asymptotic average performance are ensured. Thanks to the use of dissipativity of the nominal system with a suitable supply rate, the closed-loop system under the proposed controller is shown to be asymptotically stable, in the sense that it is driven to an optimal robust invariant set. Finally, some illustrative examples, optimally operated at qualitatively different regimes, are addressed and the performances by using our new controller and those in the literature are compared.

Summary In this paper, we propose the novel concept of “control storage function” and introduce upper and lower bounds to the best asymptotic average performance for nonlinear control systems based on suitable notions of dissipativity and controlled dissipativity. This allows to extend and unify the formulation and analysis of economic model predictive control for general optimal operation regimes, including, in particular, steady‐state or periodic operation. A closed‐loop economic performance and stability analysis are carried out within this generalized framework. As a special case, when the optimal operation is periodic, we present a new approach to formulate terminal cost functions. Finally, several examples and counterexamples are proposed and discussed to show the merits of the proposed approach.

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This paper presents an optimization-based control framework for the autonomous forced landing of a fixed-wing Unmanned Aircraft (UA). A two-level MPC scheme is proposed to realize this framework, where an EMPC in a long piece-wise constant fashion is proposed at the high-level while a short fixedhorizon linear time-varying MPC at the low-level responds to fast dynamics of UA and tracks the optimal path provided by the high-level controller, alleviating computational burden compared to the high frequency single-layer MPC scheme. Comparing with single EMPC setup with high sampling frequency, this hierarchical EMPC controller can significantly reduce the computational complexity and make it feasible to be implemented in realtime. In addition, it also responds to disturbances (e.g. wind) and aircraft fast dynamics in a timely manner. The recursive feasibility and stability of the high and low-level MPC schemes are established. The performance of the proposed EMPC forced landing function is illustrated by simulation case studies on both Aerosonde and Skywalker X8, compared favorably with competing schemes.