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This paper proposes a hybrid system comprising multiple unmanned aerial vehicles (UAVs) to monitor nature. The proposed tributary mapping system consists of perception and control systems. A perception system is established for tributary mapping using three-dimensional light detection and ranging (LiDAR) semantic segmentation for surface water recognition. The system defines a water point cloud and segments the surface water area using singular value decomposition, applying the water-absorbing property of LiDAR. A path is generated through random sample consensus by calculating the center point from the segmented area. Each UAV is modeled using a continuous-time dynamic-based low-level model and a discrete event-time dynamic-based high-level model to control the multiple UAVs system. The desired plant behavior is designed considering the control objectives of the plant, and a supervisory controller is developed accordingly. A physics-based robot simulator is employed to verify the proposed tributary mapping system in perception and path generation and the performance of the hybrid system-based supervisory controller.

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]

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 reconfigurable manufacturing systems (RMSs), the architecture of a system can be modified during its operation. This reconfiguration can be caused by many motivations: processing rework and failures, adding new products, adding new machines, etc. In RMSs, sharing of resources may lead to deadlocks, and some operations can therefore remain incomplete. The objective of this article is to develop a novel two-step solution for quick and accurate reconfiguration of supervisory controllers for deadlock control in RMSs with dynamic changes. In the first step, the net rewriting system (NRS) is used to design a reconfigurable Petri net model under dynamic configurations. The obtained model guarantees boundedness behavioral property but may lose the other properties of a Petri net model (i.e., liveness and reversibility). The second step develops an automatic deadlock prevention policy for the reconfigurable Petri net using the siphon control method based on a place invariant to solve the deadlock problem with dynamic structure changes in RMSs and achieve liveness and reversibility behavioral properties for the system. The proposed approach is tested using examples in the literature and the results highlight the ability of the automatic deadlock prevention policy to adapt to RMSs configuration changes. [ABSTRACT FROM AUTHOR]

In reconfigurable manufacturing systems (RMSs), the architecture of a system can be modified during its operation. This reconfiguration can be caused by many motivations: processing rework and failures, adding new products, adding new machines, etc. In RMSs, sharing of resources may lead to deadlocks, and some operations can therefore remain incomplete. The objective of this article is to develop a novel two-step solution for quick and accurate reconfiguration of supervisory controllers for deadlock control in RMSs with dynamic changes. In the first step, the net rewriting system (NRS) is used to design a reconfigurable Petri net model under dynamic configurations. The obtained model guarantees boundedness behavioral property but may lose the other properties of a Petri net model (i.e., liveness and reversibility). The second step develops an automatic deadlock prevention policy for the reconfigurable Petri net using the siphon control method based on a place invariant to solve the deadlock problem with dynamic structure changes in RMSs and achieve liveness and reversibility behavioral properties for the system. The proposed approach is tested using examples in the literature and the results highlight the ability of the automatic deadlock prevention policy to adapt to RMSs configuration changes.

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]

In this paper, a fault-tolerant supervisory controller is proposed for a hybrid ac/dc micro-grid. In the hybrid micro-grid, dc sources, energy storage, and loads are connected to a main dc bus, while the ac sources and sinks are coupled with a main ac bus. A bidirectional converter/inverter exchanges power between both sides. Such structure should be supervised by a main controller or management system. In this approach, the power flow is supervised based on solving an optimization problem, while the maximum available powers for fault-free and erroneous wind, solar, and energy storage sub-systems are taken into account. It is shown that solar and wind sub-system failures affect maximum available powers from those resources. In order to satisfy the demanded power with maximum utilization of renewable resources, the tolerance of the proposed supervisory controller (SC) toward shading and converter faults in the solar system, and lubricant system failure and converter fault in the wind system is considered in the design procedure. Moreover, the tolerance of the proposed power management system toward energy storage failure in each micro-grid is also incorporated in the overall control scheme. Effectiveness of the proposed SC is evaluated through extensive simulation runs based on dynamical models of the power resources. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to design and utilize a supervisory controller for networked power converters in residential applications. Wireless networks have been interfaced to multiple power factor correction (PFC) converters which are proposed to support reactive power. Unregulated reactive power support from PFC converters could cause reactive power deficiency and instability. Therefore, a supervisory controller is necessary to govern the operation of PFC converters. WiFi and WirelessHART networks have been used to implement the supervisory controller. Different nodes of the power network are connected by wireless communication links to the supervisory controller. Asynchronous communication links latency and uncertain states affect the control and response of the PFC converters. To overcome these issues, the supervisory controller design method has been proposed based on the system identification and the Ziegler-Nichols rule. The proposed supervisory controller has been validated by using a hardware-in-the-loop (HIL) test bed. The HIL testbed consisted of an OP4510 simulator, a server computer, Texas Instrument-Digital Signal Controllers (TI-DSCs), WiFi and WirelessHART modules. Experimental results show that the proposed supervisory controller can help to support and govern reactive power flow in a residential power network. The proposed method of controller design will be useful for different small-scale power and wireless network integration.

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 study proposes and implements a novel adaptive supervisory Takagi-Sugeno-Kang fuzzy cerebellar model articulation controller (adaptive supervisory TSK-FCMAC) in a sensorless vector control for induction motor drives. The proposed adaptive supervisory TSK-FCMAC includes a supervisory controller and an adaptive TSK-FCMAC. The later controller incorporates the TSK-fuzzy control with an adaptive CMAC to perform the desired control action. Adaptive supervisory TSK-FCMAC is derived using the Lyapunov approach and guarantees the learning error convergence. This study experimentally investigates three intelligent control schemes (adaptive supervisory TSK-FCMAC, adaptive TSK-FCMAC, and adaptive CMAC) and uses the root mean square error performance index to evaluate each scheme. Results show that the proposed adaptive supervisory TSK-FCMAC provides substantially improved performance over other schemes. [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]

Systematic synthesis of untimed operating procedures has always been considered as an important design issue for batch chemical processes. An automaton-based method is developed in the present study to perform this task automatically. On the basis of the proposed methodical model-building principles, two distinct types of automata can be constructed to characterize the plant behaviors and control specifications, respectively. An admissible supervisor can be produced by applying the parallel composition operation with these models. For the purpose of identifying the most efficient operation procedures, the supervisor can then be integrated with a set of auxiliary automata to set the operation target(s) and, also, to impose upper limits on the total numbers of actuator actions and operation steps. Three examples are presented to demonstrate the feasibility and correctness of the proposed approach. [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]

The recently introduced method, which was called ldquostretching,rdquo is extended to timed Petri nets which may have both controllable and uncontrollable transitions. Using this method, a new Petri net, called ldquostretched Petri net,rdquo which has only unit firing durations, is obtained to represent a timed-transition Petri net. Using this net, the state of the original timed Petri net can be represented easily. This representation also makes it easy to design a supervisory controller for a timed Petri net for any purpose. In this paper, supervisory controller design to avoid deadlock is considered in particular. Using this method, a controller is first designed for the stretched Petri net. Then, using this controller, a controller for the original timed Petri net is obtained. Algorithms to construct the reachability sets of the stretched and original timed Petri nets, as well as algorithms to obtain the controller for the original timed Petri net are presented. These algorithms are implemented using Matlab. Examples are also presented to illustrate the introduced approach. [ABSTRACT FROM PUBLISHER]

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]

A fault adaptive control methodology for mobile robots is presented. The robot is modeled as a continuous system with a supervisory controller. The physical processes of the robot are modeled using bond graphs, and this forms the basis of a combined qualitative reasoning and quantitative model-based estimation scheme for online fault detection and isolation during robot operation. A hierarchical-control accommodation framework is developed for the supervisory controller that determines a suitable control strategy to accommodate the isolated fault. It is shown that for small degradations in actuation effort, a robust controller achieves fault accommodation without significant loss of performance. However, for larger faults, the supervisor needs to switch among several controllers to maintain acceptable performance. The switching stability among a set of trajectory tracking controllers is presented. Simulation results verify the proposed fault adaptive control technique for a mobile robot. [ABSTRACT FROM PUBLISHER]

Recently, many passenger cars have adopted automatic transmissions for shifting gears, and thus the smooth and precise control of gear shifts of passenger car automatic transmissions has become more and more essential for the riding comfort of vehicles equipped with automatic transmissions. In this article, a neural network-based supervisor for an automotive shift controller considering the throttle opening, variations in throttle opening, and the driving load is presented. For using the driving load information, an, observer-based driving load estimation algorithm is proposed. A proportional-integral-derivative controller along with an open loop controller is used as a low level controller for controlling the gear shifts, and a supervisory controller for properly adapting the shift control parameters of the low level shift controller is designed using ANFIS. To evaluate the control performance of the proposed supervisor-based shift controller, both simulation studies and experimental studies are performed for various shifting situations. [ABSTRACT FROM AUTHOR]