Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process

This paper introduces optimization of machining parameters for high-pressure abrasive water jet cutting of Hardox 500 steel utilizing desirability function analysis (DFA). The tests were carried out according to the orthogonal matrix (Taguchi) L9. The control parameters of the process such as pressure, abrasive flow rate, and traverse speed was optimized under multi-response conditions namely cutting depth and surface roughness. The optimal set of control parameters was established on the basis of the composite desirability value obtained from desirability function analysis and the significance of these parameters was determined by analysis of variance (ANOVA). The effects show that optimal sets for high cutting depth and small surface roughness is high pressure, middle abrasive flow rate, and small traverse speed. A confirmation test was also leaded to validate the test results. Results of the research have shown that machining efficiency at keeping good level quality of cut surface can be improved this approach.

A Control Parameters Design Method With Multi-Constrains for an LCL-Filtered Grid-Connected Inverter in a Weak Grid

Under weak grid conditions, the variation of the grid impedance will affect the steady-state and dynamic performance of the LCL-filtered grid-connected inverter and even make the inverter unstable. To ensure the system stability and further improve the dynamic performance in a weak grid, a control parameter design method with multi-constrains considering the system bandwidth for the current controller and active damping is proposed in this paper. First, based on the current controller and active damping with only grid current feedback, the effects of control parameters and grid impedance on the LCL resonant suppression and the performance of the inverter are analyzed. Moreover, the parameter constraints of the controllers are derived considering the grid impedance, including stability, resonance suppression, and margin constraints. Furthermore, as the system bandwidth affects the dynamic performance of the inverter, combined with the obtained multi-constraints, the optimal control parameters are determined by achieving the maximum bandwidth of the system against the impedance variation. Compared with other two methods, when the proposed method is applied, the system can operate with a better dynamic and steady-state performance. Finally, experiments are performed on a 2 kW three-phase grid-connected inverter in the weak grid, which verify the effectiveness of the parameter design method proposed in this paper.

Identification and Control of Game-Based Epidemic Models

The effectiveness of control measures against the diffusion of the COVID-19 pandemic is grounded on the assumption that people are prepared and disposed to cooperate. From a strategic decision point of view, cooperation is the unreachable strategy of the Prisoner’s Dilemma game, where the temptation to exploit the others and the fear of being betrayed by them drives the people’s behavior, which eventually results in a fully defective outcome. In this work, we integrate a standard epidemic model with the replicator equation of evolutionary games in order to study the interplay between the infection spreading and the propensity of people to be cooperative under the pressure of the epidemic. The developed model shows high performance in fitting real measurements of infected, recovered and dead people during the whole period of COVID-19 epidemic spread, from March 2020 to September 2021 in Italy. The estimated parameters related to cooperation result to be significantly correlated with vaccination and screening data, thus validating the model. The stability analysis of the multiple steady states present in the proposed model highlights the possibility to tune fundamental control parameters to dramatically reduce the number of potential dead people with respect to the non-controlled case.

Optimal Control for Cleaner Hybrid Vehicles: A Backward Approach

This work presents an application of the optimal control theory to find trade offs between fuel consumption and pollutant emissions (CO, HC, NOx) of sustaining hybrid vehicles. Both cold start and normal operations are considered. The problem formulation includes two state variables: battery state of energy and catalyst temperature; and three control variables: torque repartition between engine and motor, spark advance, and equivalence ratio. Optimal results were obtained by delaying the first engine crank after the urban part of the mission. The results show that a quick catalyst light off is performed. Once the catalyst is primed, special control parameters values are adopted to operate the engine.

Trapping patterns during capillary displacements in disordered media

We investigate the impact of wettability distribution, pore size distribution and pore geometry on the statistical behaviour of trapping in pore-throat networks during capillary displacement. Through theoretical analyses and numerical simulations, we propose and prove that the trapping patterns, defined as the percentage and distribution of trapped elements, are determined by four dimensionless control parameters. The range of all possible trapping patterns and how the patterns are dependent on the four parameters are obtained. The results help us to understand the impact of wettability and structure on trapping behaviour in disordered media.

Coupled exoskeleton assistance simplifies control and maintains metabolic benefits: A simulation study

Assistive exoskeletons can reduce the metabolic cost of walking, and recent advances in exoskeleton device design and control have resulted in large metabolic savings. Most exoskeleton devices provide assistance at either the ankle or hip. Exoskeletons that assist multiple joints have the potential to provide greater metabolic savings, but can require many actuators and complicated controllers, making it difficult to design effective assistance. Coupled assistance, when two or more joints are assisted using one actuator or control signal, could reduce control dimensionality while retaining metabolic benefits. However, it is unknown which combinations of assisted joints are most promising and if there are negative consequences associated with coupled assistance. Since designing assistance with human experiments is expensive and time-consuming, we used musculoskeletal simulation to evaluate metabolic savings from multi-joint assistance and identify promising joint combinations. We generated 2D muscle-driven simulations of walking while simultaneously optimizing control strategies for simulated lower-limb exoskeleton assistive devices to minimize metabolic cost. Each device provided assistance either at a single joint or at multiple joints using massless, ideal actuators. To assess if control could be simplified for multi-joint exoskeletons, we simulated different control strategies in which the torque provided at each joint was either controlled independently or coupled between joints. We compared the predicted optimal torque profiles and changes in muscle and total metabolic power consumption across the single joint and multi-joint assistance strategies. We found multi-joint devices–whether independent or coupled–provided 50% greater metabolic savings than single joint devices. The coupled multi-joint devices were able to achieve most of the metabolic savings produced by independently-controlled multi-joint devices. Our results indicate that device designers could simplify multi-joint exoskeleton designs by reducing the number of torque control parameters through coupling, while still maintaining large reductions in metabolic cost.

Power Consumption Simulation of Servo Motors Focusing on the Influence of Mechanical Vibration on Motor Efficiency

This paper presents a simulation method for the power consumption of servo motors, focusing on the influence of vibrations on the motor efficiency. An apparatus consisting of two servo motors connected through a coupling was specifically designed for this study. The efficiency of the servo motor was experimentally investigated for several torque vibration levels imposed through the selection of the control parameters, and the torque vibration level was quantified through the standard deviation of the torque signal. The efficiency map characteristics for each torque oscillating level were determined. A numerical model of the apparatus clarifying the dependency of the coupling characteristics on the oscillating torque was developed, and the torque oscillation of the system was simulated. A model based on the measured motor efficiency maps and the torque oscillation level was developed to simulate the motor efficiency under several torque vibrating conditions. Finally, the power consumption of the motor was simulated based on the simulated efficiency and mechanical power. A balance of input, output, and loss powers was presented, and the experimental measurements were compared with the simulation results. The power consumption of the motor increased when the torque oscillated owing to vibrations, and the loss of power due to both oscillations and the loss of motor efficiency was quantified.