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Lexicographic multi-objective MPC for constrained nonlinear systems wi by Defeng He, Haiping Li et al

Abstract This paper proposes a new lexicographic multi-objective model predictive control (MoMPC) scheme for constrained nonlinear systems with changing objective prioritization. The lexicographic optimization-based receding horizon optimal control problem is firstly formulated to accommodate the concern on prioritized control of multiple (economic) objectives. Then an elaborate generic function and the notion of general terminal constraints are introduced to regain feasibility of lexicographic MoMPC in the presence of constraints and changing objective prioritization. Moreover, the LaSalle invariance set theorem is used to establish stability of the closed-loop system with the lexicographic MoMPC. An example of a coupled-tank level control problem with three conflicting objectives is adopted to demonstrate the effectiveness of the proposed scheme.

Best Readings in Communications in Wireless Networked Control | IEEE Communications Society

Best Readings in Communications in Wireless Networked Control Wireless networked control has attracted a lot of attention from both academia and industry in the past two decades, and has become a hot topic in recent years, mainly driven by mission-critical Industrial Internet of Things (IIoT) applications requiring closed-loop control, such as intelligent transportation, Tele-surgery, industry automation, power systems automation, and power electronics control. Specifically, a wireless networked control system (WNCS) is a spatially distributed control system consisting of networked sensors, actuators and a controller. The wireless sensors measure and report the physical process states of interest, the remote controller collects the sensors’ measurements and generates control signals, and the wireless actuators receive the control signals and control the processes. Due to its spatially distributed nature, reliable, dynamic and secure wireless communications among sensor, contro

Tetra Pak, Rockwell team up to advance powder solutions

Tetra Pak, Rockwell team up to advance powder solutions Lausanne, Switzerland, 12 days ago Tetra Pak and Rockwell Automation, announced a strategic business collaboration for Cheese and Powder Solutions. The combined business expertise will deliver data and technology to reduce variability and improve quality consistency, helping ensure finished products are produced sustainably and cost effectively within demand-driven manufacturing environments, a statement said.   The collaboration – starting with Evaporation and Spray Drying – has resulted in Tetra Pak’s new Powder Plant Booster solution, to be packaged with Rockwell Automation’s Model Predictive Control (MPC) and its Pavilion8 and PlantPAx MPC technology.   The combination of Tetra Pak’s food application expertise and the leading digital technology of Rockwell Automation1 will help producers to adapt to fluctuating demand-driven manufacturing far more quickly and more cost effectively.

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