Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.

Field and Laboratory Tests of Flow-Proportional Passive Samplers for Determining Average Phosphorus and Nitrogen Concentration in Rivers

Flow responsive passive samplers offer considerable potential in nutrient monitoring in catchments; bridging the gap between the intermittency of grab sampling and the high cost of automated monitoring systems. A commercially available passive sampler was evaluated in a number of river systems encapsulating a gradient in storm response, combinations of diffuse and point source pressures, and levels of phosphorus and nitrogen concentrations. Phosphorus and nitrogen are sequestered to a resin matrix in a permeable cartridge positioned in line with streamflow. A salt tracer dissolves in proportion to advective flow through the cartridge. Multiple deployments of different cartridge types were undertaken and the recovery of P and N compared with the flow-weighted mean concentration (FWMC) from high-resolution bank-side analysers at each site. Results from the passive samplers were variable and largely underestimated the FWMC derived from the bank-side analysers. Laboratory tests using ambient river samples indicated good replication of advective throughflow using pumped water, although this appeared not to be a good analogue of river conditions where flow divergence was possible. Laboratory tests also showed good nutrient retention but not elution and these issues appeared to combine to limit the utility in ambient river systems at the small catchment scale.