Taylor Series-Based Fuzzy Model Predictive Control for Wheeled Robots

In this paper, a new hybrid method for controlling a wheeled robot is introduced. Model predictive control (MPC) is the main controller and a fuzzy controller is used as a compensator. The wheeled robot is a nonlinear, multi-input–multi-output system that requires new and combined methods for precise control. In order to stabilize the system the appropriate control input is set, and at the same time, attention is paid to the reference signal tracking. In the simulation section, several different scenarios are applied and parameter uncertainties and their effects on the controller’s performance are evaluated. The simulation results show the success and efficiency of the proposed method.

Development of a Dynamic Modeling Approach to Simulate a Segmented Distillation Column for Flexible Operation

The need for flexible process equipment has increased over the past decade in the chemical industry. However, process equipment such as distillation columns have limitations that significantly restrict flexible operation. We investigate a segmented tray column designed to allow flexible operation. The design consists of radial trays connected at the downcomer of each tray. Each segment can be operated separately, but depending on the capacity of the feed stream, additional segments can be activated or deactivated. The connection between the trays aims to transfer liquid from one stationary segment to the adjacent inactive segment, thereby reducing the time required for the start-up process. In a case study on the separation of methanol and water, we perform dynamic simulations to assess the reduction in the start-up time of inactive segments. The results confirm the advantages over standard tray designs. The segmented distillation column is a step towards improving the flexibility of separation operations.