Showing papers on "Supervisory control published in 2016"

Correct-by-Construction Adaptive Cruise Control: Two Approaches

Abstract: Motivated by the challenge of developing control software provably meeting specifications for real-world problems, this paper applies formal methods to adaptive cruise control (ACC). Starting from a linear temporal logic specification for ACC, obtained by interpreting relevant ACC standards, we discuss in this paper two different control software synthesis methods. Each method produces a controller that is correct-by-construction, meaning that trajectories of the closed-loop systems provably meet the specification. Both methods rely on fixed-point computations of certain set-valued mappings. However, one of the methods performs these computations on the continuous state space whereas the other method operates on a finite-state abstraction. While controller synthesis is based on a low-dimensional model, each controller is tested on CarSim, an industry-standard vehicle simulator. Our results demonstrate several advantages over classical control design techniques. First, a formal approach to control design removes potential ambiguity in textual specifications by translating them into precise mathematical requirements. Second, because the resulting closed-loop system is known a priori to satisfy the specification, testing can then focus on the validity of the models used in control design and whether the specification captures the intended requirements. Finally, the set from where the specification (e.g., safety) can be enforced is explicitly computed and thus conditions for passing control to an emergency controller are clearly defined.

A Uniform Approach for Synthesizing Property-Enforcing Supervisors for Partially-Observed Discrete-Event Systems

Abstract: The problem under consideration in this paper is that of enforcement by supervisory control of a given property on a partially-observed discrete-event system. We present a general methodology that is applicable to a large class of properties previously studied (individually) in the literature. These properties include, but are not restricted to, safety, diagnosability, opacity, detectability, anonymity and attractability. When the given system does not satisfy the considered property, the objective is to synthesize a supervisor that restricts the system's behavior and provably enforces the given property; moreover, it is required that this supervisor be maximally permissive. We consider the general case where the system's events are partitioned into observable and unobservable events, and controllable and uncontrollable events, and we do not make any assumptions about these two partitions; in particular, we do not assume that all controllable events are observable. Our uniform approach first maps the considered property to a suitably-defined information state for the partially-observed system and then develops a supervisor synthesis methodology based on a finite bipartite transition system that embeds all reachable information states and all admissible supervisory control strategies. This transition system is called the All Enforcement Structure (or AES). We present an algorithm for the construction of the AES and discuss its properties. Then we use the AES to develop a synthesis algorithm that constructs a supervisor that is provably property enforcing and maximally permissive. We illustrate the application of our uniform approach to the enforcement of the above-mentioned properties.

Analysis of Resonance in Microgrids and Effects of System Frequency Stabilization Using a Virtual Synchronous Generator

Abstract: In order to reduce greenhouse gases, distributed generators such as wind turbines and photovoltaic facilities have been adopted in many parts of the world. These sources are assumed to be connected to an infinite bus. Thus, if the total capacity of the grid-connected inverters is approximately equal to or greater than that of conventional synchronous generators (SGs), conventional methods such as simple current control cannot maintain power grid stability. In particular, this problem becomes conspicuous in isolated islands and small communities where large commercial power systems do not exist. On the other hand, if we use supervisory control, system flexibility and scalability will be reduced. Therefore, nonsupervisory autonomous control methods are desired. For this reason, many researchers have already studied, which enables an inverter to be operated as an SG. Some of them are called virtual SG (VSG) control, and the common point of them is to provide virtual inertia. In this paper, we have derived and analyzed a formula for the dynamic stability of microgrids and shown that the VSG expressed in the first-order equation can realize a stable grid without causing resonance among the generators and the loads. The results were verified in laboratory experiments and through a simulation using electro-magnetic transient program restructured version (EMTP-RV).

Dynamic Multiple-Period Reconfiguration of Real-Time Scheduling Based on Timed DES Supervisory Control

Abstract: Based on the supervisory control theory (SCT) of timed discrete-event systems (TDES), this study presents a dynamic reconfiguration technique for real-time scheduling of real-time systems running on uni-processors. A new formalism is developed to assign periodic tasks with multiple-periods. By implementing SCT, a real-time system (RTS) is dynamically reconfigured when its initial safe execution sequence set is empty. During the reconfiguration process, based on the multiple-periods, the supervisor proposes different safe execution sequences. Two real-world examples illustrate that the presented approach provides an increased number of safe execution sequences as compared with the earliest-deadline-first (EDF) scheduling algorithm.

Interactive Control of Coupled Microgrids for Guaranteed System-Wide Small Signal Stability

Abstract: This paper proposes an interactive control framework for microgrid interconnections to achieve effective load sharing and guaranteed system-wide small signal stability. In the proposed framework, hierarchical control is performed at three levels operating in different time frames. A model reference control-based scheme is implemented for primary level power sharing, through which the interface inverter of each microgrid is controlled to track a designed reference model. At the secondary level, an interactive droop management scheme is proposed to manage the reference model droop gains based on a distributed stability criterion. At the tertiary level, an ac power flow-based supervisory control strategy is utilized to dispatch the nominal setting to each microgrid central controller (MGCC) for the primary level reference tracking, and broadcast an interaction coefficient to each MGCC so that the droop gains can be managed to guarantee system-wide stability. Numerical analysis of a study system designed based on the IEEE 123-node test feeder demonstrates the effectiveness of the proposed interactive control framework.

Multiagent Supervisory Control for Power Management in DC Microgrids

Abstract: This paper proposes multiagent supervisory control for precise power management in isolated dc microgrids. Two power management aspects are considered: 1) equal power sharing, which is realized via a proposed distributed equal power sharing algorithm; and 2) optimal power dispatch, which is achieved through a proposed distributed equal incremental cost (DEIC) algorithm. Both algorithms offer the additional advantage of the ability to restore the average system voltage to its nominal value. The proposed algorithms are based on the application of the average consensus theory along with voltage sensitivity analysis. Each distributed generation (DG) unit exchanges information with its neighbors, thus locally updating its no-load voltage setting to achieve the supervisory control objectives. The incorporation of DG droop-based control renders the proposed algorithms fully distributed with a reduced number of agents. The stability of the proposed algorithms is addressed, as well as the convergence of the proposed DEIC algorithm. Real-time OPAL-RT simulations demonstrate the effectiveness of the proposed algorithms in a hardware-in-the-loop application.

Online Tracking of Transmission-Line Parameters Using SCADA Data

Abstract: Series impedance and shunt admittance parameters of transmission lines are fundamental data for various online and offline power system studies. This paper shows that the active power, reactive power, and voltage magnitude ( $P$ , $Q$ , $V$ ) data measured at the two ends of a transmission line are sufficient to determine the positive-sequence line parameters. The phase-angle information is not essential. Since the $P$ , $Q$ , and $V$ data are readily available from the supervisory control and data-acquisition systems, the proposed method can be easily implemented in existing control centers. Algorithms, characteristics, performances, and potential applications of the proposed method are presented in this paper. Simulation study and field test results show that the proposed technique can be a useful addition to the energy-management systems of utility companies.

Polynomially Complex Synthesis of Distributed Supervisors for Large-Scale AMSs Using Petri Nets

Abstract: Due to the competition for limited resources by many concurrent processes in large-scale automated manufacturing systems (AMSs), one has to resolve any deadlock issue in order to reach their production goals without disruption and downtime. Monolithic resolution is a conventional approach for optimal or acceptable solutions, but may suffer from computational difficulty. Some decentralized methods are more efficient in finding approximate solutions, but most are application dependent. By modeling AMSs as Petri nets, we develop an innovative distributed approach, which can create a trajectory leading to a desired goal and is adaptable to different kinds of applications. Control strategies are applied to processes locally such that they can proceed concurrently and efficiently. Global goals are always reachable through the local observation, control, and execution of processes without knowing external and extra information. Polynomially complex are designed to find distributed controllers.

Detection and prevention of actuator enablement attacks in supervisory control systems

Abstract: The deployment of control systems with network-connected components nowadays has made feedback control systems vulnerable to attacks over the network. This paper considers the problem of intrusion detection and prevention in supervisory control systems, where the attacker has the ability to enable vulnerable actuator events that are disabled by the supervisor. We present a mathematical model for the system under such actuator enablement attacks and propose a defense strategy that detects attacks online and disables all controllable events after an attack is detected. We develop an algorithm for verifying whether the system can prevent damage from attacks with the proposed defense strategy, where damage is modeled as the reachability of a pre-defined set of “unsafe” states. The technical condition of interest that is necessary and sufficient in this context is characterized; it is termed “AE-safe controllability”. Finally, we illustrate the methodology with a traffic system example.

Supervisory control of vehicles

Abstract: Among other things, a command is received expressing an objective for operation of a vehicle within a denominated travel segment of a planned travel route. The objective spans a time series of (for example, is expressed at a higher or more abstract level than) control inputs that are to be delivered to one or more of the brake, accelerator, steering, or other operational actuator of the vehicle. The command is expressed to cause operation of the vehicle along a selected man-made travel structure of the denominated travel segment. A feasible manner of operation of the vehicle is determined to effect the command. A succession of control inputs is generated to one or more of the brake, accelerator, steering or other operational actuator of the vehicle in accordance with the determined feasible manner of operation.

Nonblocking Supervisory Control of Discrete Event Systems Modeled by Mealy Automata With Nondeterministic Output Functions

Abstract: In the conventional supervisory control framework for discrete event systems (DESs) with partial event observation, it is assumed that, for each event, the corresponding output symbol is determined uniquely. However, this assumption does not hold in DESs such as a system with sensor errors and a mobile system, where an output symbol depends on not only an event but also a state at which the event occurs. In this technical note, we model such a DES by a Mealy automaton with a nondeterministic output function. We consider a supervisor, called the anti-permissive supervisor, that assigns its control action based on an anti-permissive policy. We introduce a notion of AP-achievability to characterize a class of languages achievable by the anti-permissive supervisor, and discuss the existence of a nonblocking supervisor.

Multi-terminal HVDC grids with inertia mimicry capability

Abstract: The high-voltage multi-terminal dc (MTDC) systems are foreseen to experience an important development in the next years. Currently, they have appeared to be a prevailing technical and economical solution for harvesting offshore wind energy. In this study, inertia mimicry capability is added to a voltage-source converter-HVDC grid-side station in an MTDC grid connected to a weak ac grid, which can have low inertia or even operate as an islanded grid. The presented inertia mimicry control is integrated in the generalised voltage droop strategy implemented at the primary level of a two-layer hierarchical control structure of the MTDC grid to provide higher flexibility, and thus controllability to the network. Besides, complete control framework from the operational point of view is developed to integrate the low-level control of the converter stations in the supervisory control centre of the MTDC grid. A scaled laboratory test results considering the international council on large electric systems (CIGRE) B4 MTDC grid demonstrate the good performance of the converter station when it is connected to a weak islanded ac grid.

An Online Rolling Optimal Control Strategy for Commuter Hybrid Electric Vehicles Based on Driving Condition Learning and Prediction

Abstract: This paper presents an online supervisory control strategy for commuter hybrid electric vehicles (HEVs) based on driving condition learning and prediction. The aim is to provide an online self-learning-based framework to keep Pontryagin's minimum principle (PMP)-based control adapting to the time-varying driving condition on commuting routes and minimize fuel consumption. There are three steps to realizing this strategy. First, two novel statistical features are proposed to describe the frequency distribution of achievable working points of the hybrid powertrain under a driving condition. Second, based on the characteristic that commuting trips with similar trip start time, direction, and weather condition have similar driving conditions, we develop an instance-based machine learning algorithm to learn the driving condition. A k -nearest neighbor ( k -NN) prediction algorithm is used to predict future driving conditions. Third, we establish an online supervisory control strategy, together with rolling driving condition prediction and optimal costate approximation. The approximation algorithm can approximate the optimal constant costate for the entire prediction horizon just based on the proposed two features. Simulation study and bench tests are conducted on a parallel hybrid powertrain of a city bus using standard driving cycles and real-world sampled commuting trips with different trip start times and weather conditions. The results show that the proposed driving condition learning and prediction method is effective for predicting the upcoming driving conditions. Meanwhile, the proposed strategy shows substantial improvement of fuel economy compared with the rule-based (RB) strategy and the adaptive equivalent consumption minimization strategy (A-ECMS).

Distributed supervisory control of discrete-event systems with communication delay

Abstract: This paper identifies a property of delay-robustness in distributed supervisory control of discrete-event systems (DES) with communication delays. In previous work a distributed supervisory control problem has been investigated on the assumption that inter-agent communications take place with negligible delay. From an applications viewpoint it is desirable to relax this constraint and identify communicating distributed controllers which are delay-robust, namely logically equivalent to their delay-free counterparts. For this we introduce inter-agent channels modeled as 2-state automata, compute the overall system behavior, and present an effective computational test for delay-robustness. From the test it typically results that the given delay-free distributed control is delay-robust with respect to certain communicated events, but not for all, thus distinguishing events which are not delay-critical from those that are. The approach is illustrated by a workcell model with three communicating agents.

Implementation of an Energy Management Strategy for Hybrid Electric Vehicles Including Drivability Constraints

Abstract: The energy management strategy (EMS) of a hybrid electric vehicle is a supervisory control meant to steer power flows among the different energy sources of the powertrain. The EMS is designed for the purpose of reaching the maximum potential of a given powertrain architecture. Fuel consumption is not the only criterion to be considered for evaluating the global performance of an EMS, since the EMS also impacts other features such as drivability, through engine starts/stops and gear shifts. This paper proposes a general approach to include drivability constraints in the EMS of powertrains provided with discrete automated transmissions. As a first step, determinist dynamic programming is used to compute the optimal solution of the resulting optimization problem. This optimal solution is then used to assess the performance of the proposed online strategy, which is based on the equivalent consumption minimization strategy. Finally, simulation results are completed by a discussion of experimental results, as the proposed online strategy has been implemented in a prototype vehicle designed at Renault and tested on a dynamometric bench.

Cooperative exploration based on supervisory control of multi-robot systems

Abstract: When multiple mobile robots cooperatively explore an unknown environment, the advantages of robustness and redundancy are guaranteed. However, available traditional economy approaches for coordination of multi-robot systems (MRS) exploration lack efficient target selection strategy under a few of situations and rely on a perfect communication. In order to overcome the shortages and endow each robot autonomy, a novel coordinated algorithm based on supervisory control of discrete event systems and a variation of the market approach is proposed in this paper. Two kinds of utility and the corresponding calculation schemes which take into account of cooperation between robots and covering the environment in a minimal time, are defined. Different moving target of each robot is determined by maximizing the corresponding utility at the lower level of the proposed hierarchical coordinated architecture. Selection of a moving target assignment strategy, dealing with communication failure, and collision avoidance are modeled as behaviors of each robot at the upper level. The proposed approach distinctly speeds up exploration process and reduces the communication requirement. The validity of our algorithm is verified by computer simulations.

Exclusive Operation Strategy for the Supervisory Control of Series Hybrid Electric Vehicles

Abstract: Supervisory control systems (SCSs) are used to manage the powertrain of hybrid electric vehicles (HEVs). This brief presents a novel SCS called exclusive operation strategy (XOS) that applies simple rules based on the idea that batteries are efficient at lower loads while engines and generators are efficient at higher loads. The XOS is developed based on insights gained from three conventional SCSs for series HEVs: 1) thermostat control strategy (TCS); 2) power follower control strategy (PFCS); and 3) global equivalent consumption minimization strategy. Also, recent technological developments have been considered to make the XOS more suited to modern HEVs than conventional SCSs. The resulting control decisions are shown to emulate the operation of approximate global optimal solutions and thus achieve significant improvement in fuel economy compared with TCS and PFCS. In addition, the generally linear relationship between required power and engine power for the XOS provides auditory cues to the driver that are comparable to conventional vehicles, thus reducing barriers to adopting HEVs. The simplicity and the effectiveness of the XOS make it a practical SCS.

Robot master slave and supervisory control with large time delays of control signals and feedback

Abstract: In this paper the methods of remote control over space robots with large delays of the transmission of control signals from the Earth to the local robot control system are theoretically and experimentally substan-

Optimal Power Management of Hydraulic Hybrid Mobile Machines—Part I: Theoretical Studies, Modeling and Simulation

Abstract: Recent demands on improved system efficiency and reduced system emissions have driven improvements in hydraulic system architectures as well as system supervisory control strategies employed in mobile multi-actuator machinery. Valve-controlled (VC) architectures have been in use for several decades and have seen moderate improvements in terms of system efficiency. Further, throttle-less concepts such as displacement-controlled (DC) actuation have been recently proposed and successfully demonstrated efficiency improvements in numerous prototypes (wheel-loaders, excavators, and skid-steer loaders) of different sizes. The combination of electric or hydraulic hybrid systems for energy recovery (for a single actuator) with VC actuation for the rest of the actuators has also been recently deployed by original equipment manufacturers (OEMs) on some excavator models. The combination of DC actuation together with a series hydraulic hybrid actuator for the swing drive has been previously proposed and implemented as part of this work, on a mini-excavator. This combination of highly efficient DC actuation with hydraulic hybrid configuration allows drastic engine downsizing and efficiency improvements of more than 50% compared to modern-day VC-actuated systems. With a conservative, suboptimal supervisory control, it was previously demonstrated that over 50% energy savings with a 50% downsized engine over the standard load-sensing (LS) architecture for a 5-t excavator application. The problem of achieving maximum system efficiency through near-optimal supervisory control (or system power management) is a theoretically challenging problem, and has been tackled for the first time in this work for DC hydraulic hybrid machines, through a two-part publication. In Part I, the theoretical aspects of this problem are outlined, supported by simulations of the theoretically optimal supervisory control as well as an implementable, near-optimal rule-based supervisory control strategy that included a detailed system model of the DC hybrid hydraulic excavator. In Part II, the world's first prototype DC hydraulic hybrid excavator is detailed, together with machine implementation of the novel supervisory control strategy proposed in Part I. The main contributions of Part I are summarized below. Dynamic programming (DP) was employed to solve the optimal supervisory problem, and benchmark implementable strategies. Importantly, the patterns in optimal state trajectories and control histories obtained from DP were analyzed and identified for different working cycles, and a common pattern was found for engine speed and DC unit displacements across different working cycles. A rule-based strategy was employed to achieve near-optimal system efficiency, with the design of the strategy guided by optimal patterns. It was found that the strategy replicates optimal system behavior with the same rule for controlling engine speed for different cycles, but different rules for the primary unit (of the series-hybrid swing drive) for different cycles. Thus, in terms of practical implementation of a rule-based approach, the operator is to be provided with a family of controllers from which one can be chosen so as to have near-optimal system behavior under all kinds of cyclical operation.

Application of a System-Wide Trust Strategy when Supervising Multiple Autonomous Agents:

Abstract: When interacting with complex systems, the manner in which an operator trusts automation influences system performance. Recent studies have demonstrated that people tend to apply trust broadly rather than exhibiting specific trust in each component of the system in a calibrated manner (e.g. Keller & Rice, 2010). While this System–Wide Trust effect has been established for basic situations such as judging gauges, it has not been studied in realistic settings such as collaboration with autonomous agents in a multi-agent system. This study utilized a multiple UAV control simulation, to explore how people apply trust in multi autonomous agents in a supervisory control setting. Participants interacted with four UAVs that utilized automated target recognition (ATR) systems to identify targets as enemy or friendly. When one of the autonomous agents was inaccurate and performance information was provided, participants were 1) less accurate, 2) more likely to verify the ATR’s determination, 3) spent more time veri...

Concurrent Task Scheduling and Dynamic Voltage and Frequency Scaling in a Real-Time Embedded System With Energy Harvesting

Abstract: Energy harvesting is a promising technique to overcome the limit on energy availability and increase the lifespan of battery-powered embedded systems. In this paper, the question of how one can achieve the prolonged lifespan 1 of a real-time embedded system with energy harvesting capability (RTES-EH) is investigated. The RTES-EH comprises a photovoltaic (PV) panel for energy harvesting, a supercapacitor for energy storage, and a real-time sensor node as the embedded load device. A global controller performs simultaneous optimal operating point tracking for the PV panel, state-of-charge (SoC) management for the supercapacitor, and energy-harvesting-aware real-time task scheduling with dynamic voltage and frequency scaling (DVFS) for the sensor node, while employing a precise solar irradiance prediction method. The controller employs a cascaded feedback control structure, where an outer supervisory control loop performs real-time task scheduling with DVFS in the sensor node while maintaining the optimal supercapacitor SoC for improved system availability, and an inner control loop tracks the optimal operating point of the PV panel on the fly. Experimental results show that the proposed global controller lowers the task instance drop rate by up to 63% compared with the baseline controller within the same service time (i.e., from sunrise to sunset). 1 The lifetime of a battery is usually less than five years, and in this paper we propose to use supercapacitor instead of battery for embedded systems to prolong the lifespan of the whole system to more than 20 years.

Supervisory controller synthesis for product lines using CIF 3

Abstract: Using the CIF 3 toolset, we illustrate the general idea of controller synthesis for product line engineering for a prototypical example of a family of coffee machines. The challenge is to integrate a number of given components into a family of products such that the resulting behaviour is guaranteed to respect an attributed feature model as well as additional behavioural requirements. The proposed correctness-by-construction approach incrementally restricts the composed behaviour by subsequently incorporating feature constraints, attribute constraints and temporal constraints. The procedure as presented focusses on synthesis, but leaves ample opportunity to handle e.g. uncontrollable behaviour, dynamic reconfiguration, and product- and family-based analysis.

General approaches for determining the savings potential of optimal control for cooling in commercial buildings having both energy and demand charges

Abstract: This article presents a general approach for determining maximum monthly energy cost savings associated with optimal supervisory control for cooling in commercial buildings in the presence of utility rates that include both demand and time-of-use energy charges. The resulting tool has a month-long time horizon because of the nature of demand changes and is only useful for benchmarking the performance of simpler and shorter-term demand response and optimal control approaches. Attempts to solve this optimization problem using a centralized formulation failed and, therefore, the benchmarking problem was formulated as a dynamic optimization problem within a multi-agent control framework so that the monthly optimization problem is segmented into several sub-problems where each sub-problem involves system optimization for a shorter period of time, for example, a 1-day period. The daily-scale optimization involves determination of trajectories of zone set-point temperatures that minimize an integral cost functio...