Transient Constraints Research Articles

On topological conditions for enabling transient control in leader–follower networks

We derive necessary and sufficient conditions for leader–follower multi-agent systems such that we can further apply prescribed performance control to achieve the desired formation while satisfying certain transient constraints. A leader–follower framework is considered in the sense that a group of agents with external inputs are selected as leaders in order to drive the group of followers in a way that the entire system can achieve target formation within certain prescribed performance transient bounds. We first derive necessary conditions on the leader–follower graph topology under which the target formation together with the prescribed performance guarantees can be fulfilled. Afterwards, the derived necessary conditions are extended to necessary and sufficient conditions for leader–follower formation control under transient constraints. Finally, the proposed results are illustrated with simulation examples.

Under-frequency load shedding setting method of new energy sending-end system based on improved IMQ-GWO algorithm

Aiming at the problems of low qualification rate, poor stability, and insufficient timeliness of the existing under-frequency load shedding implementation scheme at the new energy sending end, this paper proposes an under-frequency load shedding setting method for the new energy sending end system based on the improved IMQ-GWO algorithm. Firstly, considering the fluctuation of the trend of the line of the sending end system relative to the load curve of the whole network, the index system of the implementation scheme based on the under-frequency load shedding is established. Secondly, the objective function is established for the index system of the under-frequency load shedding scheme, and the under-frequency load shedding setting model is established considering the static constraints and transient constraints of the system. Then, the grey wolf optimization algorithm (GWO) is updated by using the characteristics of the IMQ function. At the same time, the individual position is adaptively updated based on the Sigmoid exponential function to better search and optimize the solution space of the problem. Finally, based on the modified IEEE39 node, the empirical analysis is carried out, and the improved IMQ-GWO algorithm proposed in this paper is used to solve the under-frequency load shedding setting model. It is proved that the proposed method is superior to other methods in terms of execution qualification rate, stability, and application timeliness.

A Simulation-Assisted Proactive Scheduling Method for Secure Microgrid Formation Under Static and Transient Islanding Constraints

Microgrids (MGs) provide a promising solution to ensure the constant power supply under extreme conditions due to their islanding ability. However, unintentional islanding caused by emergencies may trigger significant a power imbalance in MGs, leading to unsuccessful MG formation in the event that static or transient operational constraints are violated. To address this challenge, we propose a proactive distribution system scheduling method to continue serving critical loads in emergencies by forming reliable MGs. The power flow on the lines is restricted prior to interruption to mitigate the power imbalance in MGs when equipment failures occur. Both static and transient constraints are incorporated into the proposed model to ensure the adequacy of MGs in supplying demands and transient security during the islanding transition. Note that the inclusion of nonlinear transient constraints makes it difficult to solve the model directly. Thus, a two-level simulation-assisted solution approach is presented, where simulation level sends the maximum allowable power imbalance in the MGs to optimization level to determine optimal scheduling schemes. By interfacing with a transient simulation of MGs, the frequency dynamics are exactly incorporated into the constraints. Numerical results validate the effectiveness of the proposed method in secure islanding transition and MG survivability improvement.

Cooperative Enclosing Control With Modified Guaranteed Performance and Aperiodic Communication for Unmanned Vehicles: A Path-Following Solution

Existing cooperative enclosing outcomes are primarily conducted relying on continuous transmission flow among agents, and transient specifications are not explicitly incorporated into the design, which may consume a large amount of communication resources and violate the preset transient constraints. To address abovementioned issues, by resorting to a path-following framework, this paper proposes a novel cooperative enclosing control with aperiodic communication and modified guaranteed performance for unmanned vehicles, consisting of communication and guidance levels. At communication level, by constructing an event-triggered rule and a continuous-time state predictor, an aperiodic communication tactic is established to mitigate the real-time transmission cost of network medium and obviate unnecessary resource wastage. At guidance level, a modified guaranteed performance control (MGPC) with the deployment of novel unsymmetrical envelopes is proposed to prescribe path-following errors within user-defined constraints while excluding any overshoots. The striking innovation includes two aspects, one is that by utilizing the aperiodic communication tactic, transmission data amount among multiple vehicles in experimental results can be reduced by approximately 54.7% compared with the time-triggered alternative, another is that the performance guarantees (e.g., overshoot-free property and preassigned convergence rate) can be retained by resorting to suggested MGPC. All deviations of the entire system are analyzed to be constrained without triggering Zeno behaviors. The effectiveness is further validated by simulation and experimental outcomes.

Optimal Power Control for a Variable-Speed Generator Integrated in Series Hybrid Vehicle

In series hybrid electric vehicles, the fossil energy source is composed of an electrical generator driven by an internal combustion engine. Compared to constant speed control, variable speed control of the electrical generator improves the vehicle’s energetic efficiency and releases the battery load. Such control is extremely sensitive because of the nonlinearities. In a plug-in hybrid vehicle, in addition to the obvious inherent variable speed nonlinearity, the large range of battery voltage variation increases the complexity of the controller design. Moreover, in our case, to take advantage of the variable speed feature, the generator load has transient constraints because it must follow the vehicle load. In equivalent applications, for the electrical side, usually, there is a use of high-frequency control strategies based on the generator’s three phases current and voltage acquirement. This article investigates a low-frequency power control strategy through a model-based method for a specific power electronics vehicle architecture. Starting with an adaptive proportional, integrator, and derivative (PID)-based controller to tackle the nonlinearity issues, this article explains progressively the reasons and choices that lead to design a sliding hybrid fuzzy logic controller. The designed controller demonstrates good performance in power tracking and permits to reduce fuel consumption.

The Voltage Security Region Calculation Method of Receiving-End Power System Based on the Equivalence of Transient Process

In order to ensure the voltage security of the receiving-end power grid under both steady state and N-1 faults, it is necessary to conduct an accurate dynamic reactive power reserve assessment to ensure its normal voltage operation range at steady state. In other words, it’s to determine the power grid voltage security region which is a transient stability constrained optimal power flow (TSCOPF) problem essentially. However, it needs to consider a large amount operational snapshots and corresponding transient constraints under each snapshot, which increases the computational burden heavily. To overcome this issue, this paper proposes a calculation method for the voltage security region of receiving-end power grid through the equivalence of the transient process. Firstly, based on the power grid partition and the matrix of graph theory, the different snapshots are selected to obtain typical snapshots, and then for the typical snapshots sought, the transient stability constraints under the fault are transformed into steady-state constraints. In other words, the form is consistent with the steady-state equation but the impedance matrix parameters are equivalently adjusted. In essence, it is equally to replace the constraints of the optimization problem under the premise of ensuring that the consistency of the boundary conditions, so as to greatly accelerate the solution speed under the premise of ensuring the accuracy of the solution, and the calculation cases made in the modified IEEE9 system and the modified IEEE39 system prove the effectiveness and reliability of the proposed method in this paper.

On Asymptotic Stability of Leader–Follower Multiagent Systems Under Transient Constraints

On Asymptotic Stability of Leader–Follower Multiagent Systems Under Transient Constraints

Dynamics of dormancy regulation in \u2018Sonata\u2019 strawberry and its relation to flowering and runnering

BackgroundDormancy regulation in strawberry is a dynamic process that is causally interrelated with regulation of flowering. Interference between the two processes is therefore possible.MethodsWe studied dormancy control and its relation to flowering and runner formation in ‘Sonata’ strawberry under daylight phytotron conditions. Growth and flowering were observed in plants pretreated for 5 or 10 weeks at 10-h SD and 18-h LD at 6 and 18 ℃ and subsequently forced in a greenhouse in LD at 20 ℃ with and without previous chilling for 6 weeks at 2 ℃ in darkness.ResultsSD induced constrained leaf and inflorescence growth at both 6 and 18 ℃, while the typical strawberry semi-dormant condition was attained only by exposure to SD at 18 ℃ for 10 weeks, which also completely blocked runner formation. The constrained leaf and inflorescence growth observed in plants grown in SD at 18 ℃ were partially reversed by 6 weeks of chilling and gradually overcome in successively emerging leaves. While plants grown in LD at 18 ℃ for 10 weeks remained vegetative under subsequent forcing, they unexpectedly initiated flowers when subjected to chilling in darkness for 6 weeks before the forcing.ConclusionsSD exposure at 18 ℃ constrained leaf and inflorescence growth in ‘Sonata’ strawberry, and when applied for 10 weeks, it induced the persistent semi-dormant state that is typical for strawberry. Transient growth constraints were also induced at 6 ℃ in both SD and LD, while the semi-dormant state was only attained by SD at the higher temperature. Flowering in complete darkness, which is known in both SD and LD plants, did also take place in ‘Sonata’ strawberry in response to chilling in the dark at 2 ℃ for 6 weeks. While the potential impact of the phenomenon seems limited for regulation of flowering in strawberry, we conclude that chilling in the dark at near-freezing temperature may substantially enhance flowering in marginally induced strawberry plants.

Scalable time-constrained planning of multi-robot systems

This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The main goal is to design decentralized and robust control laws so that each robot meets an individual high-level specification given as a metric interval temporal logic (MITL), while using only local information based on a limited sensing radius. Furthermore, the robots need to fulfill certain desired transient constraints such as collision avoidance between them. The controllers, which guarantee the transition between regions, consist of two terms: a nominal control input, which is computed online and is the solution of a decentralized finite-horizon optimal control problem (DFHOCP); and an additive state feedback law which is computed offline and guarantees that the real trajectories of the system will belong to a hyper-tube centered along the nominal trajectory. The controllers serve as actions for the individual weighted transition system (WTS) of each robot, and the time duration required for the transition between regions is modeled by a weight. The DFHOCP is solved at every sampling time by each robot and then necessary information is exchanged between neighboring robots. The proposed approach is scalable since it does not require a product computation among the WTS of the robots. The proposed framework is experimentally tested and the results show that the proposed framework is promising for solving real-life robotic as well as industrial applications.

Adaptive singularity-free controller design of constrained nonlinear systems with prescribed performance

This paper investigates the controller design for the tracking problem of uncertain nonlinear systems with constraints on input and output. First, to avoid the full-state measurement, the high-gain observer is designed to estimate the unmeasured state. Compared to existing observer design for nonlinear systems, the high-gain observer design only requires a modified version of the Lipschitz condition. The output feedback controller is further presented on this basis. Second, to consider the transient constraints on the tracking performance, a barrier Lyapunov function with the user-defined time-varying performance is developed. In addition, the proposed controller design is shown to be free of control direction singularity. The convergence of the learning scheme and the boundedness of all the closed-loop signals during the learning phase are discussed theoretically. Finally, two simulation examples are conducted to verify the advantage of the proposed adaptive output feedback controller design.

Improving security and economy of interconnected power network through explicit feasible region of tie-line power transfer

With the increasing power demand and renewables, the efficient utilization of power resources in each regional network relies on the tie-line power exchanges in interconnected power networks. Consequently, an accurate characterization of the feasible region of tie-line power transfer is crucial for scheduling tie-line power to achieve a secure and efficient utilization of power resources. This paper proposes a characterization method to explicitly capture a feasible region of tie-line power transfer considering steady-state constraints with reactive power and voltage limits and transient constraints. The steady-state and transient constraints are explicitly derived: 1) a power transfer distribution factor matrix with reactive power and voltage magnitude is derived to equivalently reflect the steady-state operational region with fewer variables and constraints; 2) the transient constraints of the tie-line power are derived based on the swing and current injection equations and a constraint transcription technology is adopted to convert transient constraints from continuous-time domain to a vector space, which makes it possible to identify the feasible region of tie-line power transfer. The steady-state and transient constraints are explicitly projected to the tie-line power space via a vertex search method. Finally, this paper utilizes the feasible region of tie-line power transfer to perform the tie-line scheduling via the proposed linear programming model. The proposed tie-line scheduling model can promote the optimal utilization of generation dispatches, which guarantees security and improve economics in the interconnected power network. The numerical results based on the IEEE 9-bus and IEEE 118-bus test systems verify the effectiveness of the proposed methods.

Study on Optimization of Active Control Schemes for Considering Transient Processes in the Case of Pipeline Leakage

Pipeline leakage of crude oil, refined oil or other petroleum derivatives can cause serious damage to the environment, soil, and more importantly, pose a serious threat to personal safety. The losses can be minimized to a degree by active control. Therefore, timely and effective control measures should be taken to minimize the leak volume whenever a pipeline leaks. However, the complexity of pipeline hydraulic systems makes it difficult to optimize control schemes for pipeline hydraulic devices under leak conditions, and existing studies rarely consider complex transient processes. This paper aims to establish a mixed integer linear programming model considering transient processes, hydraulic constraints, equipment constraints and flow constraints, and develop a detailed control scheme of the devices by the branch and bound algorithm. Moreover, it is the objective of the model to figure out the most optimal control plan to minimize the leakage. Experiments on a real-world liquid pipeline have proved the practicability and high reliability of the model.

Sliding Mode Control with Model-Based Switching Functions applied on a 7-DOF Exoskeleton Arm

This article features a novel sliding mode controller for robotic arms using nonlinear model-based switching functions. The new controller is experimentally validated on a 7-DOF exoskeleton arm used for upper-limb rehabilitation applications. The proposed approach features a novel concept using model-based switching functions in the sliding mode controller, which leads to considerable simplifications on the torque control inputs. Compared to conventional linear switching functions, model-based switching functions show substantial control performance improvements on the torque inputs, such as transient constraints reduction and enhanced robustness, while maintaining a very good tracking performance. Moreover, model-based switching functions design ensures a complete decoupling of chattering effect between joint axes. Furthermore, this approach can be combined with existing chattering reduction techniques to ensure proper control of chattering levels on the torque inputs. These advantages make the practical implementation of the model-based switching functions approach particularly desirable for wearable robotics, where smooth movements and high accuracy are important requirements for patients’ comfort and security.

Security-Constrained Unit Commitment With Natural Gas Pipeline Transient Constraints

The interdependencies of power systems and natural gas networks have increased due to the additional installations of more environmental-friendly and fast-ramping natural gas power plants. The natural gas transmission network constraints and the use of natural gas for other types of loads can affect the delivery of natural gas to generation units. These interdependencies will affect the power system security and economics in day-ahead and real-time operations. Hence, it is imperative to analyze the impact of natural gas network constraints on the security-constrained unit commitment (SCUC) problem. In particular, it is important to include natural gas and electricity network transients in the integrated system security because the impacts of any disturbances propagate at two distinctly different speeds in natural gas and electricity networks. Thus, analyzing the transient behavior of the natural gas network on the security of natural gas power plants would be essential as these plants are considered to be very flexible in electricity networks. This paper presents a method for solving the SCUC problem considering the transient behavior of the natural gas transmission network. The applicability of the presented method and the accuracy of the proposed solution are demonstrated for the IEEE 118-bus power system, which is linked with the natural gas transmission system and the results are discussed in this paper.

Optimal regulation of flow networks with transient constraints

This paper investigates the control of flow networks, where the control objective is to regulate the measured output (e.g. storage levels) towards a desired value. We present a distributed controller that dynamically adjusts the inputs and flows, to achieve output regulation in the presence of unknown constant disturbances, while satisfying given input and flow constraints. Optimal coordination among the controllers minimizing a suitable cost function of the inputs at the nodes, is achieved by exchanging information over a communication network. Exploiting an incremental passivity property, the desired steady state is proven to be globally asymptotically attractive under the closed loop dynamics. Two case studies (a district heating system and a super-conducting DC network) show the effectiveness of the proposed solution.

Use of SQP optimization algorithm to size a multiphysical system

PurposeStatic converters generate current harmonics in power grids. For numerous studies, analytical frequency modeling is preferred to carry out their harmonic modeling in the context of sizing by optimization. However, a design by optimization has to consider other constraints, e.g. modeling constraints and operating constraints. In this way, this paper aims to focus on applying an analytical frequency modeling on the sizing by optimization of an aircraft electrical power channel.Design/methodology/approachThe paper aims to size a multiphysical system by optimization. In this way, the sizing of an aircraft electrical power channel by optimization has been carried out. The models of all the channel components are analytical. Specifically, the frequency model of the power electronics is based on Tran et al. (2016) and is made of equalities and inequalities. Due to this modeling choice, the optimization satisfies hundreds of constraints, such as modeling constraints and static converter operating constraints. Furthermore, transient constraints are only verified after optimization.FindingsThe difficulty is the modeling of the system by taking into account nonlinear implicit equations having several solutions. A solution is the addition of inequality constraints to the model to guide the implicit solving. Furthermore, this greatly helps the optimization algorithm to find the good operating mode of the static converter, at steady state. This aspect is indispensable to validate the sizing model.Research limitations/implicationsThe number of the configurations per operating period of the static converters is defined a priori and limited.Originality/valueThe analytical model for the sizing is formulated as a constrained optimization problem. Its solving and the sizing by optimization are carried out by the same optimization algorithm.

Model-based sliding functions design for sliding mode robot control

This paper introduces a novel manifold design for sliding mode control, applicable to second-order mechanical systems in which nonlinear dynamics can be formalised into that of robotic manipulators. The new approach shows that model-based sliding manifold design substantially simplifies the torque control law, which ultimately becomes linear in terms of joint angles and rates. Additionally, this approach allows the decoupling of the chattering effect on the torque inputs on each axis. A new property related to the gravity term is introduced and is used for stability analysis and model validation. Simulation results compare the introduced approach to the conventional linear manifold design and demonstrate that the new approach reduces transient constraints on torque input and is more robust to matched uncertainties for low inertia robots.

Effect of Integral Feedback on a Class of Uncertain Nonlinear Systems: Stability and Induced Limit Cycles

The theoretical problem addressed in the present work involves the effect of integral feedback on a class of uncertain nonlinear systems. The intriguing aspects of the problem arise as a result of transient constraints combined with the presence of parametric uncertainty and an unknown nonlinearity. The motivational problem was the state-of-charge (SOC) control strategy for load-following in solid oxide fuel cells (SOFCs) hybridized with an ultracapacitor. In the absence of parametric uncertainty, our prior work established asymptotic stability of the equilibrium if the unknown nonlinearity is a passive memoryless function. In contrast, this paper addresses the realistic scenario with parametric uncertainty. Here, an integral feedback/parameter adaption approach is taken to incorporate robustness. The integral action, which results in a higher-order system, imposes further restriction on the nonlinearity for guaranteeing asymptotic stability. Furthermore, it induces a limit cycle behavior under additional conditions. The system is studied as a Lure problem, which yields a stability criterion. Subsequently, the describing function method yields a necessary condition for half-wave symmetric periodic solution (induced limit cycle).

Absolute Stability Analysis Using the Liénard Equation: A Study Derived From Control of Fuel Cell Ultracapacitor Hybrids

Load-following in solid oxide fuel cells (SOFCs), hybridized with an ultracapacitor for energy storage, refers to an operating mode where the fuel cell's generated power follows the variable power demand, delivering the total demanded power at steady-state. Implementing this operating mode presents a rich set of problems in dynamical systems and control. This paper focuses on state-of-charge (SOC) control of the ultracapacitor during load-following, under transient constraints, and in the presence of an unknown nonlinearity. The problem is generalized to stabilization of a plant containing a cascaded connection of a driver and a driven dynamics, where the former is nonlinear and largely unknown. Closed-loop stability of the system is studied as a Lur'e problem and via energy-based Lyapunov equations, but both impose conservative conditions on the nonlinearity. An alternate approach is developed, where the closed-loop dynamics are formulated as a class of Liénard equations. The corresponding analysis, which is based on the nonlinear characteristics of the Liénard equation, yields more definitive and less conservative stability criteria. Additional conditions that lead to limit cycles are also derived, and a bifurcation pattern is revealed. The generality of the proposed approach indicates applicability to a variety of nonlinear systems.

Optimal Operation of a Combined Heat and Power System Considering Real-time Energy Prices

The combined heat and power (CHP) systems can provide heat and electricity simultaneously. They are promising in the future energy landscape because of high efficiency and low emissions. This paper proposes a new operation optimization model of CHPs in deregulated energy markets. Both CHPs’ overall efficiency and heat to electricity ratio are closely linked with the loading level, which are dynamically determined in this paper. A discrete optimization model is then proposed to determine the optimal real-time operation strategies for the CHPs. The optimization problem is solved by the interior point method with discrete time intervals, in which the discrete optimal operation points can be identified effectively. This step projects the potential operation strategies that could produce maximum benefits. Finally, a dynamic programming algorithm is developed to maximize the profits of CHPs through dynamically modifying the operation strategies projected in the previous step considering transient constraints. The proposed new methodology is demonstrated on a 1-MW CHP system with real-time data.