A Model Predictive Scheduling Algorithm inReal-Time Control Systems

Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems

With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

Validation concurrency control protocol in parallel real-time database systems

In parallel real-time database systems, concurrency control protocols must satisfy time constraints as well as the integrity constraints. The authors present a validation concurrency control(VCC) protocol, which can enhance the performance of real-time concurrency control mechanism by reducing the number of transactions that might miss their deadlines, and compare the performance of validation concurrency control protocol with that of HP2PL(High priority two phase locking) protocol and OCC-TI-WAIT-50(Optimistic concurrency control-time interval-wait-50) protocol under shared-disk architecture by simulation. The simulation results reveal that the protocol the author presented can effectively reduce the number of transactions restarting which might miss their deadlines and performs better than HP2PL and OCC-TI-WAIT-50. It works well when arrival rate of transaction is lesser than threshold. However, due to resource contention the percentage of missing deadline increases sharply when arrival rate is greater than the threshold.

Computation Method for the Real-Time Control Problems in Differential-Algebraic Systems

In this paper, a real-time computation method for the control problems in differential-algebraic systems is presented. The errors of the method are estimated, and the relation between the sampling stepsize and the controlled errors is analyzed. The stability analysis is done for a model problem, and the stability region is ploted which gives the range of the sampling stepsizes with which the stability of control process is guaranteed.

Quasi Serializable Concurrency Control in Distributed Real-Time Database Systems

This paper formally defines and analyses the new notion of correctness called quasi serializability, and then outlines corresponding concurrency control protocol QDHP for distributed real-time databases. Finally, through a series of simulation studies, it shows that using the new concurrency control protocol the performance of distributed real-time databases can be much improved.

Asymptotic stability analysis of nonlinear real-time networked control systems

The paper deals with the problem of the asymptotic stability for general continuous nonlinear networked control systems （NCSs）. Based on Lyapunov stability theorem combined with improved Razumikhin technique, the sufficient conditions of asymptotic stability for the system are derived. With the proposed method, the estimate of maximum allowable delay bound （MADB） for linear networked control system is also given. Compared to the other methods, the proposed method gives a much less conservative MADB and more general results. Numerical examples and some simulations are worked out to demonstrate the effectiveness and performance of the proposed method.

Weak Serializable Concurrency Control in Distributed Real-Time Database Systems

Most of the proposed concurrency control protocols for real time database systems are based on serializability theorem. Owing to the unique characteristics of real time database applications and the importance of satisfying the timing constraints of transactions, serializability is too strong as a correctness criterion and not suitable for real time databases in most cases. On the other hand, relaxed serializability including epsilon serializability and similarity serializability can allow more real time transactions to satisfy their timing constraints, but database consistency may be sacrificed to some extent. We thus propose the use of weak serializability(WSR) that is more relaxed than conflicting serializability while database consistency is maintained. In this paper, we first formally define the new notion of correctness called weak serializability. After the necessary and sufficient conditions for weak serializability are shown, corresponding concurrency control protocol WDHP(weak serializable distributed high priority protocol) is outlined for distributed real time databases, where a new lock mode called mask lock mode is proposed for simplifying the condition of global consistency. Finally, through a series of simulation studies, it is shown that using the new concurrency control protocol the performance of distributed real time databases can be greatly improved.

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

这份报纸用预兆的控制策略涉及设计，分析和联网的控制系统的即时实现。联网的控制系统的特征的分析被详细说明，它证明一个联网的控制系统与常规控制系统不同。完成靠近环的联网的控制系统的需要的性能，联网的预兆的控制计划被介绍。设计，稳定性分析和联网的预兆的控制系统的即时实现被学习。它被联网的预兆的控制计划能补偿随机的网络通讯延期和数据退学学生的模拟和实际实验说明，完成需要的控制性能并且有好靠近环的稳定性。

Automotive Lighting Systems Based on Luminance/Intensity Grids: A Proposal Based on Real-Time Monitoring and Control for Safer Driving

The requirements for automotive lighting systems,especially the light patterns ensuring driver perception,are based on criteria related to the headlamps,rather than the light perceived by drivers and road users.Consequently,important factors such as pavement reflectance,driver age,or time of night,are largely ignored.Other factors such as presence of other vehicles,vehicle speed and weather conditions are considered by the Adaptive Driving Beam(ADB)and Adaptive Front-lighting System(AFS)respectively,though with no information regarding the visual perception of drivers and other road users.Evidently,it is simpler to simulate and measure the light emitted by the lamps than the light reflected by the pavement or emitted by other vehicles.However the current technology in cameras and light sensors,communication protocols,and control of Light Emitting Diodes(LED),combined with decision-making techniques applied to large amounts of data,can open a new era in the operation of headlamps and thus ensure the visual needs of drivers in real time and under actual road conditions.The solution lies in an interaction road-sensor-headlamp,which is not based on the light emitted by headlamps,but rather on the light perceived by the drivers.This study thus proposes a dual grid based on luminance and luminous intensity,which would manage the headlamps by optimizing driver perception and the safety of all road users.

Discrete Event Net Based Modeling and Control System Design for Real-Time Concurrent Control of Multiple Robot Systems

This paper deals with control system design and implementation problems encountered in multiple robot systems. The methodology developed is depicted by a set of coordination mechanisms using hierarchical net structures and their accompanying rules. With the net models, the hierarchical and distributed control system is designed for an assembly task. Synchronization commands allow coordination of the movements of the robots. The net models make concurrency of the movements of the robots transparent to users. The net based machine controller executes robot motion control through the communication with the external robot controller using the command/response concept. Sensory signals indicating the change of state of robots are used to trigger or initiate tasks. Simultaneous movement of the robots is obtained by creating different background threads running in parallel under Windows OS. The multilevel hierarchical control system can be consistently constructed using net models.

Development of a Simulation-Based Intelligent Decision Support System for the Adaptive Real-Time Control of Flexible Manufacturing Systems

This paper describes a simulation-based intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS) with machine and tool flexibility. The manufacturing processes involved in FMS are complicated since each operation may be done by several machining centers. The system design approach is built around the theory of dynamic supervisory control based on a rule-based expert system. The paper considers flexibility in operation assignment and scheduling of multi-purpose machining centers which have different tools with their own efficiency. The architecture of the proposed controller consists of a simulator module coordinated with an IDSS via a real time event handler for implementing inter-process synchronization. The controller’s performance is validated by benchmark test problem.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Risk-Informed Model-Free Safe Control of Linear Parameter-Varying Systems

This paper presents a risk-informed data-driven safe control design approach for a class of stochastic uncertain nonlinear discrete-time systems.The nonlinear system is modeled using linear parameter-varying(LPV)systems.A model-based probabilistic safe controller is first designed to guarantee probabilisticλ-contractivity(i.e.,stability and invariance)of the LPV system with respect to a given polyhedral safe set.To obviate the requirement of knowing the LPV system model and to bypass identifying its open-loop model,its closed-loop data-based representation is provided in terms of state and scheduling data as well as a decision variable.It is shown that the variance of the closedloop system,as well as the probability of safety satisfaction,depends on the decision variable and the noise covariance.A minimum-variance direct data-driven gain-scheduling safe control design approach is presented next by designing the decision variable such that all possible closed-loop system realizations satisfy safety with the highest confidence level.This minimum-variance approach is a control-oriented learning method since it minimizes the variance of the state of the closed-loop system with respect to the safe set,and thus minimizes the risk of safety violation.Unlike the certainty-equivalent approach that results in a risk-neutral control design,the minimum-variance method leads to a risk-averse control design.It is shown that the presented direct risk-averse learning approach requires weaker data richness conditions than existing indirect learning methods based on system identification and can lead to a lower risk of safety violation.Two simulation examples along with an experimental validation on an autonomous vehicle are provided to show the effectiveness of the presented approach.

Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

Control Strategies for Digital Twin Systems

With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.

Dynamic Constraint-Driven Event-Triggered Control of Strict-Feedback Systems Without Max/Min Values on Irregular Constraints

This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints.Unlike the constraints considered in most existing papers,here the external irregular constraints are considered and a constraints switching mechanism(CSM)is introduced to circumvent the difficulties arising from irregular output constraints.Based on the CSM,a new class of generalized barrier functions are constructed,which allows the control results to be independent of the maximum and minimum values(MMVs)of constraints and thus extends the existing results.Finally,we proposed a novel dynamic constraint-driven event-triggered strategy(DCDETS),under which the stress on signal transmission is reduced greatly and no constraints are violated by making a dynamic trade-off among system state,external constraints,and inter-execution intervals.It is proved that the system output is driven to close to the reference trajectory and the semi-global stability is guaranteed under the proposed control scheme,regardless of the external irregular output constraints.Simulation also verifies the effectiveness and benefits of the proposed method.

A Survey on Type-3 Fuzzy Logic Systems and Their Control Applications

In this paper,we offer a review of type-3 fuzzy logic systems and their applications in control.The main objective of this work is to observe and analyze in detail the applications in the control area using type-3 fuzzy logic systems.In this case,we review their most important applications in control and other related topics with type-3 fuzzy systems.Intelligent algorithms have been receiving increasing attention in control and for this reason a review in this area is important.This paper reviews the main applications that make use of Intelligent Computing methods.Specifically,type-3 fuzzy logic systems.The aim of this research is to be able to appreciate,in detail,the applications in control systems and to point out the scientific trends in the use of Intelligent Computing techniques.This is done with the construction and visualization of bibliometric networks,developed with VosViewer Software,which it is a free Java-based program,mainly intended to be used for analyzing and visualizing bibliometric networks.With this tool,we can create maps of publications,authors,or journals based on a co-citation network or construct maps of keywords,countries based on a co-occurrence networks,research groups,etc.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Interpolated Bumpless Transfer Control for Asynchronously Switched Linear Systems

This paper revisits the problem of bumpless transfer control(BTC) for discrete-time nondeterministic switched linear systems. The general case of asynchronous switching is considered for the first time in the field of BTC for switched systems. A new approach called interpolated bumpless transfer control(IBTC) is proposed, where the bumpless transfer controllers are formulated with the combination of the two adjacent modedependent controller gains, and are interpolated for finite steps once the switching is detected. In contrast with the existing approaches, IBTC does not necessarily run through the full interval of subsystems, as well as possesses the time-varying controller gains(with more flexibility and less conservatism) achieved from a control synthesis allowing for the stability and other performance of the whole switched system. Sufficient conditions ensuring stability and H_(∞) performance of the underlying system by IBTC are developed, and numerical examples verify the theoretical findings.