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This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project. • State machine-based supervisory controller for fuel cell system is designed. • The designed control structure is implemented in a prototype hydrogen-based vehicle. • The controller comprises: State Machine, Setpoint Generator, Power Limit Calculator. • The proposed control structure handles the startup and shutdown process of PEMFC. • Minimizing stack degradation by implementing a fuel cell power limit calculator. [ABSTRACT FROM AUTHOR]

Purpose: A hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable of achieving a high range and endurance due to the low energy density of its batteries. Alternatively, conventional UAVs (cUAVs) using fuel with an internal combustion engine (ICE) produces more noise and thermal signatures which is undesirable, especially if the air vehicle is required to patrol at low altitudes and remain undetected by ground patrols. This paper aims to investigate the impact of implementing hybrid propulsion technology to improve on the endurance of the UAV (based on a 13.6 kg UAV). Design/methodology/approach: A HE-UAV model is developed to analyze the fuel consumption of the UAV for given mission profiles which were then compared to a cUAV. Although, this UAV size was used as reference case study, it can potentially be used to analyze the fuel consumption of any fixed wing UAV of similar take-off weight. The model was developed in a Matlab-Simulink environment using Simulink built-in functionalities, including all the subsystem of the hybrid powertrain. That is, the ICE, electric motor, battery, DC-DC converter, fuel system and propeller system as well as the aerodynamic system of the UAV. In addition, a ruled-based supervisory controlled strategy was implemented to characterize the split between the two propulsive components (ICE and electric motor) during the UAV mission. Finally, an electrification scheme was implemented to account for the hybridization of the UAV during certain stages of flight. The electrification scheme was then varied by changing the time duration of the UAV during certain stages of flight. Findings: Based on simulation, it was observed a HE-UAV could achieve a fuel saving of 33% compared to the cUAV. A validation study showed a predicted improved fuel consumption of 9.5% for the Aerosonde UAV. Originality/value: The novelty of this work comes with the implementation of a rule-based supervisory controller to characterize the split between the two propulsive components during the UAV mission. Also, the model was created by considering steady flight during cruise, but not during the climb and descend segment of the mission. [ABSTRACT FROM AUTHOR]

ASHRAE RP-1747 is a CO 2 -based demand-controlled ventilation (DCV) approach which uses trim and respond logic to dynamically adjust variable air volume (VAV) terminal units' minimum airflow setpoints based on zones' ventilation requirements. While simulation results and laboratory testing have estimated the impact on heating, ventilation, and air conditioning (HVAC) systems compared to traditional ventilation, there have been limited applications of RP-1747 in occupied, real-world buildings to date. This paper introduces a real-world implementation of RP-1747 DCV in an institutional office building over an eight-month period, using a supervisory control approach. During this implementation, a complementary temperature setback approach was also developed and employed in the case study building. These changes to the sequences of operation, as well as corrections to other sub-optimal sequences of operation discovered during implementation, resulted in a 36 ± 2 % and 2 ± 6 % reduction in heating and cooling energy use, respectively, while improving per person ventilation rates in the case study. The results aim to contribute to the body of literature on this emerging DCV approach and provide anecdotal evidence of its benefits and interactions with other control logic in a real-world application, while also demonstrating the benefits of supervisory control when implementing complex process control functions. [ABSTRACT FROM AUTHOR]

In this study, a supervisory control system with an adaptive Mamdani-type fuzzy controller (AMFC) is used to control an omnidirectional spherical mobile robot (ODSMR). The system combines an adaptive Mamdani-type fuzzy controller and a supervisory controller for ODSMRs with unknown external disturbances. Tracking is provided by a Mamdani-type fuzzy controller that approximates a theoretically exact control law, and a separate controller is used to cancel the residual of the approximation error. The control law is derived using Lyapunov stability theory to ensure the stability of the closed-loop system. Many external factors can cause the system to become unstable, so a supervisory controller is included. A decoupled control approach provides a simple method to achieve asymptotic stability for a fourth-order nonlinear system. The main concept of this approach is to decouple the system into two subsystems. Then, the primary subsystem combines the information provided by the secondary subsystem to generate a control that drives both subsystems to their desired states. This platform can move in any direction with no constraints. The efficiency of the proposed controller is verified with tests on an actual robot. The contributions of this study are: (1) the implementation of an ODSMR and (2) the application of the proposed AMFC with a supervisory control system to real-time control of the ODSMR. [ABSTRACT FROM AUTHOR]

Equal power-rating inverters operating with different power set-points in either an islanded or grid-connected mode may lead to inter-unit circulating power caused by a large mismatch between power generation and demand during network contingencies (faults on the heavy load side or unintentional islanding). This circulating power may violate the dc-link voltage limit and, as a result, the protection scheme may shut down the inverter and reduce the microgrids reliability. This paper proposes a regulator for controlling the dc-link voltage of the microgrid's inverter during a period of circulating power. It includes a discharging resistor with a series-connected switch across the dc-link capacitor which is turned on through a control algorithm if the dc-link voltage exceeds its pre-defined limit. Case studies of parallel-connected inverters are conducted and their stability assessed through a small-signal analysis. In addition, a realistic microgrid is designed as a low-voltage (LV) network and tested to verify the concept and regulator actions presented. The simulation results validate the effectiveness of the proposed regulator during network contingencies. [ABSTRACT FROM AUTHOR]

This paper focuses on dynamic modeling, simulation, control and energy management in an agricultural experiment station located at Sahline–Tunisia consisting of a 1.5 kW photovoltaic panel (PV) and a 25 A h Lead Acid battery storage supplying an induction motor coupled to a centrifugal pump as mechanical load. The cost-optimally design and the new suitable power management approach are the two main objectives. An iterative optimization approach namely, the Deficiency of Power Supply Probability (DPSP), the Relative Excess Power Generated (REPG), the Energy Cost (EC) as well as the Total Net Present Cost (TNPC) have been developed in order to find the optimal configuration of PV/battery. To reach the second object, three new supervisory controllers are designed, a neuro-fuzzy controller, a fuzzy controller and an algorithm controller. In order to show the effectiveness of the first one, a comparison of the three controllers is proposed. The principal objectives of the three supervisory controllers are: (i) the design of an adequate tracking system maximum power point (MPPT) to extract the maximum power which is given by the theory of conservation of energy, (ii) the insurance of the control speed needed for the vectorial control of the induction motor, (iii) the regulation of the water in the tank which is taken as a second storage system and finally (iv) the insurance of the correct operation for all the conversion string in order to optimize the quantity of water pumped. [ABSTRACT FROM AUTHOR]

With the increasing penetration of wind power into electric power grids, energy storage devices will be required to dynamically match the intermittency of wind energy. This paper proposes a novel two-layer constant power control scheme for a wind farm equipped with doubly fed induction generator (DFIG) wind turbines. Each DFIG wind turbine is equipped with a supercapacitor energy storage system (ESS) and is controlled by the low-layer wind turbine generator (WTG) controllers and coordinated by a high-layer wind farm supervisory controller (WFSC). The WFSC generates the active power references for the low-layer WTG controllers according to the active power demand from or generation commitment to the grid operator; the low-layer WTG controllers then regulate each DFIG wind turbine to generate the desired amount of active power, where the deviations between the available wind energy input and desired active power output are compensated by the ESS. Simulation studies are carried out in PSCAD/EMTDC on a wind farm equipped with 15 DFIG wind turbines to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Abstract: This study presents paper presents an analysis of the potential CO2 savings that could be gained through the introduction of hydrogen-powered fuel cells on a commuter-style railway route. Vehicle is modelled as a fuel cell series hybrid. The analysis consists of power/energy flow models of a fuel cell stack, battery pack and hybrid drive controller. The models are implemented in a custom C# application and are capable of providing key parametric information of the simulated journey and individual energy drive components. A typical commuter return journey between Stratford Upon Avon and Birmingham is investigated. The fuel cell stack and battery pack behaviour is assessed for different stack sizes, battery sizes and control strategies to evaluate the performance of the overall system with the aim of understanding the optimum component configuration. Finally, the fuel (H2) requirements are compared with typical diesel and hybrid-diesel powered vehicles with the aim of understanding the potential energy savings gained from such a fuel cell hybrid vehicle. [ABSTRACT FROM AUTHOR]

Abstract: This paper attempts to propose a hybrid adaptive cerebellar model articulation controller (CMAC) sliding mode control (SMC; called HAC-SMC) with a supervisory controller for a class of nonlinear system, in which the HAC composed of a direct adaptive CMAC and an indirect adaptive CMAC control is performed as the SMC. There are two methods to design the switching control law of SMC. One is the sign switching controller. The other is the CMAC switching controller. Besides, a supervisory controller is appended to the HAC-SMC to guarantee the states staying in the boundary layer. The adaptive laws of the control system are derived in the sense of Lyapunov theorem so that the asymptotic stability of the system could be guaranteed. Simulation results show that the proposed control system has satisfactory performance on the inverted pendulum system and the Chua''s chaotic circuit. [Copyright &y& Elsevier]

The advent of reconfigurable manufacturing systems (RMSs) has given rise to a challenging problem, i.e., how to reconfigure rapidly and validly a RMS supervisory controller in response to frequent changes in the manufacturing system configuration driven by fluctuating market. This paper presents an improved net rewriting system (INRS)-based method for automatic reconfiguration of Petri net (PN) supervisory controllers for RMS. We begin with presenting the INRS which overcomes the limitations of the net rewriting system and can dynamically change the structure of a PN without damaging its important behavioral properties. Based on INRS, a method for design reconfigurable PN controllers of RMS is introduced. Subsequently, we presented an INRS-based method for rapidly automatic reconfiguration of this class of PN controllers. In the reconfiguration method, changes in a RMS configuration can be formalized and act on an existing controller to make it reconfigure rapidly into a new one. Noticeably, no matter the design or reconfiguration, the expected behavioral properties of the resultant PN controllers are guaranteed. Thus, efforts for verification of the results can be avoided naturally. We also illustrate the reconfiguration of a PN controller for a reconfigurable manufacturing cell. Note to Practitioners--This paper presents an automatic reconfiguration method for PN supervisors of RMS in response to RMS configuration changes. First, INRSs are introduced that can dynamically change the structure of a PN with preserving its important behavioral properties. Second, a method for designing a class of PN controllers is proposed with an approach of INRS. Third, the INRS-based method for reconfiguration of this class of controllers is presented as well. Using this method, an existing controller can be reconfigured rapidly and validly with reconfiguration of the RMS. Finally, a reconfigurable manufacturing cell is provided for illustrating the presented reconfiguration method. [ABSTRACT FROM AUTHOR]

In real-time applications a discrete supervisory controller should stabilise the fuzzy control system. For this reason a discrete supervisory controller was developed and applied together with the fuzzy controller. The discrete supervisory controller performs like a continuous one. The main difference is in the sign function of the appended controller. We have proved that the fuzzy control system equipped with the discrete supervisory controller is globally stable only if we can predict the sign of supervisory action. On the other hand, discrete supervisory controllers require the knowledge of the bounds of the non-linear functions in the system, same as continuous one. Application to a balance control system was successful, both in simulations and in real-time control. [ABSTRACT FROM AUTHOR]