The Cu-based MOF loaded on macroporous carbon (MPC) creates novel Cu-MOF-MPC hybrids for the first time. The obtained Cu-MOF-MPC composites are used as electrocatalysts for the oxidation of NADH and reduction of H2O2 in neutral solution.

We develop a model predictive control (MPC) design for systems with discrete-time dynamics evolving on smooth manifolds. We show that the properties of conventional MPC for dynamics evolving on R are preserved and we develop a design procedure for achieving similar properties. We also demonstrate that for discrete-time dynamics on manifolds with Euler characteristic not equal to 1, there do not...

We present CODEV, a Matlab-based tool for verifying systems employing Model Predictive Control (MPC). The MPC solution is computed offline and modeled together with the physical system as a hybrid automaton, whose continuous dynamics may be nonlinear with a control solution that remains affine. While MPC is a widely used synthesis technique for constrained and optimal control in industry, our t...

This paper considers discrete-time nonlinear, possibly discontinuous, systems in closed-loop with Model Predictive Controllers (MPC). The aim of the paper is to provide a priori sufficient conditions for asymptotic stability in the Lyapunov sense and robust stability, while allowing for both the system dynamics and the value function of the MPC cost to be discontinuous functions of the state. T...

Due to climate change energy efficiency is becoming increasingly important. This is particularly true for the building system control sector, where a large energy saving potential exists. Model Predictive Control (MPC) is a new control technique in this sector that minimises the building energy use while taking into account comfort and other constraints through the use of a simplified building ...

In recent years, MPC algorithm as a new method has been successfully applied for the design of motion cueing algorithm. By using an adequate formulation of MPC model and an efficient QP solver, the MPC algorithm can provide better motion restitution results than the more conventional algorithms. However, few papers give a description in detail of the used MPC technique together with the right t...

Model predictive control (MPC) has been successfully applied to many transportation systems. For the control of overhead cranes, existing MPC approaches mainly focus on improving the regulation performance, such as tracking error or steady-state error. In this paper, energy efficiency as well as safety is newly considered in our proposed MPC approach. Based on the system model designed, the MPC...

In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an efficient solution strategy for the unconstrained subproblems that give the search-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This...

In this work, we develop model predictive control (MPC) designs, which are capable of optimizing closed-loop performance with respect to general economic considerations for a broad class of nonlinear process systems. Specifically, in the proposed designs, the economic MPC optimizes a cost function, which is related directly to desired economic considerations and is not necessarily dependent on ...

RATIONALE Allogeneic mesenchymal precursor cells (MPCs) have been effective in large animal models of ischemic and nonischemic heart failure (HF). OBJECTIVE To evaluate the feasibility and safety of 3 doses (25, 75, or 150 million cells) of immunoselected allogeneic MPCs in chronic HF patients in a phase 2 trial. METHODS AND RESULTS We sequentially allocated 60 patients to a dosing cohort (...