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.

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.

A Survey on the Control Lyapunov Function and Control Barrier Function for Nonlinear-Affine Control Systems

This survey provides a brief overview on the control Lyapunov function(CLF)and control barrier function(CBF)for general nonlinear-affine control systems.The problem of control is formulated as an optimization problem where the optimal control policy is derived by solving a constrained quadratic programming(QP)problem.The CLF and CBF respectively characterize the stability objective and the safety objective for the nonlinear control systems.These objectives imply important properties including controllability,convergence,and robustness of control problems.Under this framework,optimal control corresponds to the minimal solution to a constrained QP problem.When uncertainties are explicitly considered,the setting of the CLF and CBF is proposed to study the input-to-state stability and input-to-state safety and to analyze the effect of disturbances.The recent theoretic progress and novel applications of CLF and CBF are systematically reviewed and discussed in this paper.Finally,we provide research directions that are significant for the advance of knowledge in this area.

Quantization and Event-Triggered Policy Design for Encrypted Networked Control

This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.

Generalized autoencoder-based fault detection method for traction systems with performance degradation

Fault diagnosis of traction systems is important for the safety operation of high-speed trains.Long-term operation of the trains will degrade the performance of systems,which decreases the fault detection accuracy.To solve this problem,this paper proposes a fault detection method developed by a Generalized Autoencoder(GAE)for systems with performance degradation.The advantage of this method is that it can accurately detect faults when the traction system of high-speed trains is affected by performance degradation.Regardless of the probability distribution,it can handle any data,and the GAE has extremely high sensitivity in anomaly detection.Finally,the effectiveness of this method is verified through the Traction Drive Control System(TDCS)platform.At different performance degradation levels,our method’s experimental results are superior to traditional methods.

On the Motion of Controllable Mechanical Systems Having Variable Mass

The differential equations of motion of a comtlaint system with parameters and variable mass, of a system with variable mass and servo constraints and those for the control problem on the forced motion of constraint systems with variable mass are given respectively. Finally, an example is presented.

Time-stamped predictive functional control for networked control systems with random delays

The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.

Application of Large-Scale Systems Theory in Fire Control Systems

According the to the model of single tank fire control system, this paper makes use of decomposition-coordination theory of large-scale systems to discuss the shooting problem of multiple tank the control systems, and alalyzes specifically the three-tank the control systems and models.the process was imitated in computer, and the optimal shooting element of 3TS system was got. In addition, probability of hitting the target was calculated.

Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information

An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to guarantee an adaptive improvement in tracking performance. A decreasing learning gain is introduced into the algorithm to suppress the effects of stochastic noises and quantization errors. The input sequence is proved to converge strictly to the optimal input under the given index. Illustrative simulations are given to verify the theoretical analysis. © 2014 Chinese Association of Automation.

Identification and PID Control for a Class of Delay Fractional-order Systems

In this paper, a new model identification method is developed for a class of delay fractional-order system based on the process step response. Four characteristic functions are defined to characterize the features of the normalized fractional-order model. Based on the time scaling technology, two identification schemes are proposed for parameters U+02BC estimation. The scheme one utilizes three exact points on the step response of the process to calculate model parameters directly. The other scheme employs optimal searching method to adjust the fractional order for the best model identification. The proposed two identification schemes are both applicable to any stable complex process, such as higher-order, under-damped U+002F over-damped, and minimum-phase U+002F nonminimum-phase processes. Furthermore, an optimal PID tuning method is proposed for the delay fractional-order systems. The requirements on the stability margins and the negative feedback are cast as real part constraints U+0028 RPC U+0029 and imaginary part constraints U+0028 IPC U+0029. The constraints are implemented by trigonometric inequalities on the phase variable, and the optimal PID controller is obtained by the minimization of the integral of time absolute error U+0028 ITAE U+0029 index. Identification and control of a Titanium billet heating process is given for the illustration. © 2014 Chinese Association of Automation.

Fundamental Issues in Networked Control Systems

Abstract--This paper provides a survey on modeling and theories of networked control systems （NCS）. In the first part, modeling of the different types of imperfections that affect NCS is discussed. These imperfections are quantization errors, packet dropouts, variable sampling/transmission intervals, vari- able transmission delays, and communication constraints. Then follows in the second part a presentation of several theories that have been applied for controlling networked systems. These theories include： input delay system approach, Markovian system approach, switched system approach, stochastic system approach, impulsive system approach, and predictive control approach. In the last part, some advanced issues in NCS including decentral- ized and distributed NCS, cloud control system, and co-design of NCS are reviewed. Index Terms--Decentralized networked control systems （NCS）, distributed networked control systems, network constraints, net- worked control system, quantization, time delays.

Networked Control Systems:A Survey of Trends and Techniques

Networked control systems are spatially distributed systems in which the communication between sensors, actuators,and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices,increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems,process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘control over networks’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘control over networks’, providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.

Guaranteed cost control for networked control systems

The guaranteed cost control problem for networked control systems (NCSs) is addressed under communication constraints and varying sampling rate. First of all, a simple information-scheduling scheme is presented to describe the scheduling approach of system signals in NCSs. Then, based on such a scheme and given sampling method, the design procedure in dynamic output feedback manner is also derived which renders the closed loop system to be asymptotically stable and guarantees an upper bound of the LQ performance cost function.

Secure Consensus Control for Multi-Agent Systems With Attacks and Communication Delays

This paper addresses the consensus problem for nonlinear multi-Agent systems suffering from attacks and communication delays. The network studied in this paper consists of two types of agents, namely, loyal agents and attack agents. The loyal agents update their states based on delayed state information exchanged with their neighbors. Meanwhile, the attack agents can strategically send messages with wrong values, or collude with other attack agents to disrupt the correct operation of the system. We design a novel delay robust secure consensus DRSC algorithm according to the neighboring nodes U2BC delayed information. Convergence analysis of the system under the protocol designed is provided by using Lyapunov-Krasovskii stability theory and Barbalat-like argument approach. Finally, an example and simulation results are presented to demonstrate the effectiveness of the algorithm. © 2014 Chinese Association of Automation.

Improved H_∞ control for networked control systems with network-induced delay and packet dropout

The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

Cloud Control Systems

The concept of cloud control systems is discussed in this paper, which is an extension of networked control systems (NCSs). With the development of internet of things (IOT), the technology of NCSs has played a key role in IOT. At the same time, cloud computing is developed rapidly, which provides a perfect platform for big data processing, controller design and performance assessment. The research on cloud control systems will give new contribution to the control theory and applications in the near future. © 2014 Chinese Association of Automation.

Stability of singular networked control systems with control constraint

Based on bounded network-induced time-delay, the networked control system is modeled as a linear time-variant singular system. Using the Lyapunov theory and the linear matrix inequality approach, the criteria for delay-independent stability and delay-dependent stability of singular networked control systems are derived and transformed to a feasibility problem of linear matrix inequality formulation, which can be solved by the Matlab LMI toolbox, and the feasible solutions provide the maximum allowable delay bound that makes the system stable. A numerical example is provided, which shows that the analysis method is valid and the stability criteria are feasible.

Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-Time scales dynamic neural network MTSDNN observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman HJB equation associated with the MTSDNN observer and critic NN. The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input U+002F output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation. Simulation results are presented to confirm the validity of the investigated approach. © 2014 Chinese Association of Automation.

Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems

In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO non-affine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible 'controller singularity' problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of 'explosion of complexity' in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme. © 2014 Chinese Association of Automation.