Reduced-Order GPIO Based Dynamic Event-Triggered Tracking Control of a Networked One-DOF Link Manipulator Without Velocity Measurement

In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Backstepping Based Global Exponential Stabilization of a Tracked Mobile Robot with Slipping Perturbation

While the nonholonomic robots with no-slipping constraints are studied extensively nowadays, the slipping effect is inevitable in many practical applications and should be considered necessarily to achieve autonomous navigation and control purposes especially in outdoor environments. In this paper the robust point stabilization problem of a tracked mobile robot is discussed in the presence of track slipping, which can be treated as model perturbation that violates the pure nonholonomic constraints. The kinematic model of the tracked vehicle is created, in which the slipping is assumed to be a time-varying pa- rameter under certain assumptions of track-soil interaction. By transforming the original system to the special chained form of nonholonomic system, the integrator backstepping procedure with a state-scaling technique is used to construct the controller to stabilize the system at the kinematic level. The global exponential stability of the final system can be guaranteed by Lyapunov theory. Simulation results with different initial states and slipping parameters demonstrate the fast convergence, robustness and insensitivity to the initial state of the proposed method.

Admissibility analysis and control synthesis for switched linear singular systems

The problem of admissibility analysis and control synthesis of discrete-time switched linear singular （SLS） systems for arbitrary switching laws is solved. By using the switched Lyapunov function approach, some new sufficient conditions under which the SLS system is admissible for arbitrary switching laws are derived in terms of linear matrix inequalities （LMIs）. Based on the admissibility results, control synthesis is then to design switched state feedback and static output feedback controllers, guaranteeing that the resulting closed-loop system is admissible. The presented results can be viewed as the extensions of previous works on switched Lyapunov function approach from the regular switched systems to singular switched cases. Examples are provided to demonstrate the reduced conservatism and effectiveness of the proposed conditions.

Dynamic optimization of 1,3-propanediol fermentation process:A switched dynamical system approach

This paper considers a dynamic optimization problem(DOP)of 1,3-propanediol fermentation process(1,3-PFP).Our main contributions are as follows.Firstly,the DOP of 1,3-PFP is modeled as an optimal control problem of switched dynamical systems.Unlike the existing switched dynamical system optimal control problem,the state-dependent switching method is applied to design the switching rule.Then,in order to obtain the numerical solution,by introducing a discrete-valued function and using a relaxation technique,this problem is transformed into a nonlinear parameter optimization problem(NPOP).Although the gradient-based algorithm is very efficient for solving NPOPs,the existing algorithm is always trapped in a local minimum for such problems with multiple local minima.Next,in order to overcome this challenge,a gradient-based random search algorithm(GRSA)is proposed based on an improved gradient-based algorithm(IGA)and a novel random search algorithm(NRSA),which cannot usually be trapped in a local minimum.The convergence results are also established,and show that the GRSA is globally convergent.Finally,a DOP of 1,3-PFP is provided to illustrate the effectiveness of the GRSA proposed by this paper.

Robust stability and stabilization for uncertain discrete-time switched singular systems with time-varying delays

The problems of robust stability and stabilization via memoryless state feedback for a class of discrete-time switched singular systems with time-varying delays and linear fractional uncertainties are investigated.By constructing a novel switched Lyapunov-Krasovskii functional,a delay-dependent criterion for the unforced system to be regular,causal and uniformly asymptotically stable is established in terms of linear matrix inequalities（LMIs）.An explicit expression for the desired memoryless state feedback stabilization controller is also given.The merits of the proposed criteria lie in their less conservativeness and relative simplicity,which are achieved by considering additionally useful terms（ignored in previous methods） when estimating the upper bound of the forward difference of the Lyapunov-Krasovskii functional and by avoiding utilizing any model augmentation transformation.Some numerical examples are provided to illustrate the validity of the proposed methods.

Optimal guaranteed cost control for an uncertain discrete T-S fuzzy system with time-delay

This paper considers the guaranteed cost control problem for a class of uncertain discrete T-S fuzzy systems with time delay and a given quadratic cost function. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequalities （LMI） approach by constructing a specific nonquadratic Lyapunov-Krasovskii functional and a nonlinear PDC-like control law. A convex optimization problem is also formulated to select the optimal guaranteed cost controller that minimizes the upper bound of the closed-loop cost function. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed approaches.

Composite control method for stabilizing spacecraft attitude in terms of Rodrigues parameters

In this paper, the attitude stabilization problem of a rigid spacecraft described by Rodrigues parameters is investigated via a composite control strategy, which combines a feedback control law designed by a finite time control technique with a feedforward compensator based on a linear disturbance observer （DOB） method. By choosing a suitable coordinate transformation, the spacecraft dynamics can be divided into three second-order subsystems. Each subsystem includes a certain part and an uncertain part. By using the finite time control technique, a continuous finite time controller is designed for the certain part. The uncertain part is considered to be a lumped disturbance, which is estimated by a DOB, and a corresponding feedforward design is then implemented to compensate the disturbance. Simulation results are employed to confirm the effectiveness of the proposed approach.

Stochastic coordinated operation of wind and battery energy storage system considering battery degradation

Grid-scale battery energy storage systems(BESSs)are promising to solve multiple problems for future power systems.Due to the limited lifespan and high cost of BESS,there is a cost-benefit trade-off between battery effort and operational performance.Thus,we develop a battery degradation model to accurately represent the battery degradation and related cost during battery operation and cycling.A linearization method is proposed to transform the developed battery degradation model into the mixed integer linear programming(MILP)optimization problems.The battery degradation model is incorporated with a hybrid deterministic/stochastic look-ahead rolling optimization model of windBESS bidding and operation in the real-time electricity market.Simulation results show that the developed battery degradation model is able to effectively help to extend the battery cycle life and make more profits for wind-BESS.Moreover,the proposed rolling look-ahead operational optimization strategy can utilize the updated wind power forecast,thereby also increase the wind-BESS profit.

Adaptive Numerical Approach for Optimal Control of a Single Train

This paper considers the optimal control problem of a single train,which is formulated as an optimal control problem of nonlinear systems with switching controller.The switching sequence and the switching time are decision variables to be chosen optimally.Generally speaking,it is very difficult to solve this problem analytically due to its nonlinear nature,the complexity of the controller,and the existence of system state and control input constraints.To obtain the numerical solution,by introducing binary functions for every value of the control input,relaxing the binary functions,and imposing a penalty function on the relaxation,the problem is transformed into a parameter optimization problem,which can be efficiently solved by using any gradient-based numerical approach.Then,the authors propose an adaptive numerical approach to solve this problem.Convergence results indicate that any optimal solution of the parameter optimization problem is also an optimal solution of the original problem.Finally,an optimal control problem of a single train illustrates that the adaptive numerical approach proposed by us is less time-consuming and obtains a better cost function value than the existing approaches.

Output Feedback Tracking Control for a Class of Switched Nonlinear Systems with Time-varying Delay

This paper studies the problem of tracking control for a class of switched nonlinear systems with time-varying delay. Based on the average dwell-time and piecewise Lyapunov functional methods, a new exponential stability criterion is obtained for the switched nonlinear systems. The designed output feedback H∞controller can be obtained by solving a set of linear matrix inequalities(LMIs).Moreover, the proposed method does not need that a common Lyapunov function exists for the switched systems, and the switching signal just depends on time. A simulation example is provided to demonstrate the effectiveness of the proposed design scheme.

Leader Selection for Strong Structural Controllability of Single-Integrator Multi-Agent Systems

This paper addresses the leader selection problem for strong structural controllability(SSC)of multi-agent systems(MASs). For a path-bud graph, it is proved that only one leader is required to guarantee the SSC of MASs. For a special type of topologies, based on the partition of the topology into disjoint pathes and path-buds, it is proved that the MASs is strongly structurally controllable if the root nodes of the pathes are selected as leaders. For general topologies, an algorithm is provided to determine the agents that can behave as leaders. For some special topologies, the minimum number of leaders guaranteeing the robust strong structural controllability(RSSC) of MASs is also obtained.Two examples are given to verify the effectiveness of the results.

Global sampled-data output feedback control for a class of feedforward nonlinear systems

This paper investigates the problem of global output feedback stabilization for a class of feedforward nonlinear systems via linear sampled-data control. To solve the problem, we first construct a linear sampled-data observer and controller. Then, a scaling gain is introduced into the proposed observer and controller. Finally, we use the sampled-data output feedback domination approach to find the explicit formula for choosing the scaling gain and the sampling period which renders the closed-loop system globally asymptotically stable. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.

Irregular distribution of wind power prediction

Wind power is volatile and uncertain, which makes it difficult to establish an accurate prediction model.How to quantitatively describe the distribution of wind power output is the focus of this paper. First, it is assumed that wind speed is a random variable that satisfies the normal distribution. Secondly, based on the nonlinear relationship between wind speed and wind power, the distribution model of wind power prediction is established from the viewpoint of the physical mechanism. The proposed model successfully shows the complex characteristics of the wind power prediction distribution. The results show that the distribution of wind power prediction varies significantly with the point forecast of the wind speed.

Combination of Qualitative Information with 2-Tuple Linguistic Representation in DSmT

Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models （i.e., a distribution function model （DFM） and an improved Herrera-Martinez＇s model） jointly with the fusion rules developed in Dezert-Smarandache Theory （DSmT）, in order to combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve the precision and improve the efficiency of the fusion of linguistic information expressing the global expert＇s opinion. However, DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.

A clustering based method to complete frame of discernment

When the existing information does not contain all categories,the Generalized Evidence Theory(GET)can deal with information fusion.However,the question of how to determine the number of categories through GET is still intriguing.To address this question,a modified k-means clustering,named centers initialized clustering is proposed,filling the gap of identification and complement of the frame of discernment.Based on this clustering method,the number of cat-egories is determined.The initialized centers selected by center density keep the cluster results con-stant,enhancing the stability of clustering results.Besides,constructing Generalized basic Probability Assignment(GBPA)modules in a conservative way improves the reliability of the results.The mass of empty set in combined GBPAs is the indicator of the number of categories.Experiments on real and artificial data sets are conducted to show the effectiveness.

Stability of Time-delay System with Time-varying Uncertainties via Homogeneous Polynomial Lyapunov-Krasovskii Functions

This paper deals with the robust stability of time-delay system with time-varying uncertainties via homogeneous polynomial Lyapunov-Krasovskii functions(HPLKF). We give a sufficient condition to demonstrate that the system is asymptotically stable.A new class of Lyapunov-Krasovskii function is introduced, whose main feature is that the conservativeness due to uncertainties is reduced. Numerical examples illustrate the effectiveness of our method.

Multi-source information fusion:Progress and future

Multi-Source Information Fusion(MSIF),as a comprehensive interdisciplinary field based on modern information technology,has gained significant research value and extensive application prospects in various domains,attracting high attention and interest from scholars,engineering experts,and practitioners worldwide.Despite achieving fruitful results in both theoretical and applied aspects over the past five decades,there remains a lack of comprehensive and systematic review articles that provide an overview of recent development in MSIF.In light of this,this paper aims to assist researchers and individuals interested in gaining a quick understanding of the relevant theoretical techniques and development trends in MSIF,which conducts a statistical analysis of academic reports and related application achievements in the field of MSIF over the past two decades,and provides a brief overview of the relevant theories,methodologies,and application domains,as well as key issues and challenges currently faced.Finally,an analysis and outlook on the future development directions of MSIF are presented.

A new multisensor fusion SLAM approach for mobile robots

This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.

Simplifying ADRC design with error-based framework: case study of a DC-DC buck power converter

In this work,the problem of designing a robust control algor ithm for a DC-DC buck power converter is investigated.The applied solution is based on a recenly proposed eror-based version of the active disturbance rejection control(ADRC)scheme,in which the unknown higher-order lerms of the reference signal are treated as additional components of the system"total disturbance".The motivation here is to provide a prac tical following of a reference voltage trajectory for the buck converler in specific cases where neither the analytical form of the desired signal nor its future values are known a priori,hence cannot be directly used for control synthesis.In this work.the application of the error-based ADRC results in a prac-tically appealing control technique,with compact struc ture.simplified control rule,and intwitive tuning(inherited from the conventional output-based ADRC scheme).Theoretical.numerical,and experimental results are shown to validate the efficacy of the error-based ADRC in buck converter control,followed by a discussion about the revealed theoretical and practical limitations of this approach.