A note on diagnosis and performance degradation detection in automatic control systems towards functional safety and cyber security

This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention on three aspects:(i)application of control and detection uni ed framework to enhancing the diagnosis capability of feedback control systems,(ii)projection-based fault detection,and complementary and explainable applications of projection-and machine learning-based techniques,and(iii)system performance degradation detection that is of elemental importance for today's automatic control systems.Some ideas and conceptual schemes are presented and illustrated by means of examples,serving as convincing arguments for research e orts in these aspects.They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.

THE MECHANISM OF AUTOMATIC CONTROL WITH VARIABLE STRUCTURE-PARAMETERS

The general form of the dynamic response of a controlled process is shown in Fig. 1, where E is the deviation of the controlled variable U from its set-point value U0 （i. e. E= U0-U）. For convenience in discussing, we transform the curve in Fig. 1 into that in Fig. 2 a t-domain curve of |E|. Now, we discuss a certain period of variation of the curve in Fig. 2, e.g. a time interval between to and t4.We partition this period of variation into four subintervals: t0—t1, t1—t2, t2—t3 and t3—t4. It is easily seen that, in the first and the third subintervals, the rate of change

MECHANISM OF IMPLICIT DIFFERENTIATION AND IMPLICIT INTEGRATION IN AUTOMATIC CONTROL

PID control is widely used in various process control systems with a differentiation function aimed at acquiring a good transient response of the systems and with an integration function aimed at improving the static characteristics of the systems so as to mini-

Data-Driven Control of Distributed Event-Triggered Network Systems

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(a.k.a.network systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional approach.Marrying the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is established.Meanwhile,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data.Finally,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

ON THE STABILITY OF NON-AUTONOMOUS MOTION OF NON-LINEAR AUTOMATIC CONTROL SYSTEMS WITH TIME-LAGS

A. K. Begelbahyev investigated problems of determination of stability limit for autonomous motion and non-autonomous motion of non-linear automatic control systems; as well as problems of determination of stability limit for autonomous motion of non-linear automatic control systems with time-lags. Recently, the author used the method introduced in [4] to improve the results of [2].

Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph.It is of two-degree-of-freedom nature.Specifically,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances.The condition for asymptotic disturbance rejection is derived.Moreover,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection performance.Then,a robust stabilization condition with less conservativeness is derived for the whole multi-agent system.Further,a design algorithm is given.Finally,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.

Tool Condition Monitoring Based on Nonlinear Output Frequency Response Functions and Multivariate Control Chart

Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.

Control and Treatment of Bone Cancer: A Novel Theoretical Study

The human body has symmetric bones.This paper uses control engineering concepts to design a suitable controller to synchronize two symmetric bones of the human body to control and treat bone cancer.A Nonsingular Terminal Sliding Mode Control(NTSMC)method will be employed to design the proposed control inputs.The control inputs can be the chemical drugs that can be used to treat bone cancer.The dynamical equations of bone cancer will be used to apply the designed control method and test it.For testing the designed controller,Simulink/MATLAB software will be used.The proposed controller is chattering-free,robust against uncertainties and external disturbances,and finite-time stable in the control engineering view.Bone cancer will be treated for almost one year using the proposed control method.

Real-time UAV path planning based on LSTM network

To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on long shortterm memory(RPP-LSTM)network is proposed,which combines the memory characteristics of recurrent neural network(RNN)and the deep reinforcement learning algorithm.LSTM networks are used in this algorithm as Q-value networks for the deep Q network(DQN)algorithm,which makes the decision of the Q-value network has some memory.Thanks to LSTM network,the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment.Besides,the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning,so that the UAV can more reasonably perform path planning.Simulation verification shows that compared with the traditional feed-forward neural network(FNN)based UAV autonomous path planning algorithm,the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.

Control System Design for an Unmanned Helicopter to Track a Ground Target

Due to potential wide applications,the problem of utilizing an unmanned helicopter to track a ground target has become one of the most active research directions in related areas.However,in most cases,it is possible for a dynamic target to implement evasive actions with strong maneuverability,such as a sudden turn during high-speed movement,to flee from the tracker,which then brings much difficulty for the design of tracking control systems.Currently,most research on this field focuses on utilizing a ground mobile robot to track a high-speed target.Unfortunately,it is very difficult to extend those developed methods to airborne applications due to much more complex dynamices of UAV-target relative motion.This study investiages thoroughly for the problem of using an unmanned helicopter to track a ground target,with particular emphasis on the avoidance of tracking failure caused by the evasive maneuvers of dynamic targets.Specifically,a novel control scheme,which consists of an innovative target tracking controller and a classical flight controller,is proposed for the helicopter-target tracking problem.Wherein,the tracking controller,whose design is the focus of the paper,aims to utilize the motion information of the helicopter and the dynamic target to construct a suitable trajectory for the helicopter,so that when it flies along this trajectory,the relative pose between the helicopter and the dynamic target will be kept consant.When designing the target tracking controller,a novel coordinate transformation is firstly introduced to convert the tracking system into a more compact form convenient for control law design,the desired velocities for the helicopter is then proposed with consideration of the dynamic constraint.The stability of the closed-loop system is finally analyzed by Lyapunov techniques.Based on Matlab/Simulink environment,two groups of simulation are conducted for the helicopter-target tracking control system where the target moves along a linear path and takes a sudden turn during high-speed movement,respectively.As shown by the simulation results,both the distance error and the pointing error are bounded during the tracking process,and they are convergent to zero when the target moves straightly.Moreover,the tracking performance can be adjusted properly to avoid tracking failure due to evasive maneuvers of the target,so as to guarantee superior tracking performance for all kinds of dynamic targets.

Fault Detection of Networked Control Systems Based on Optimal Robust Fault Detection Filter

有可能比一个采样时期大的随机、未知的导致网络的延期的联网的控制系统(NCS ) 的差错察觉在这份报纸被学习。首先，导致网络的延期引起的影响被转变成为错误建模组织，然后存在连续时间域基于引用，模型被扩大到分离时间领域并且适用指责联网的控制系统的察觉的柔韧的差错察觉方法。建议方法能被 Matlab LMI 工具箱容易实现，并且它的表演被一个模拟例子最后评估。

QFT control based on zero phase error compensation for flight simulator

To improve the robustness of high-precision servo systems, quantitative feedback theory (QFT) which aims to achieve a desired robust design over a specified region of plant uncertainty is proposed. The robust design problem can be solved using QFT but it fails to guarantee a high precision tracking. This problem is solved by a robust digital QFT control scheme based on zero phase error (ZPE) feed forward compensation. This scheme consists of two parts: a QFT controller in the closed-loop system and a ZPE feed-forward compensator. Digital QFT controller is designed to overcome the uncertainties in the system. Digital ZPE feed forward controller is used to improve the tracking precision. Simulation and real-time examples for flight simulator servo system indicate that this control scheme can guarantee both high robust performance and high position tracking precision.

Nonlinear decoupling controller design based on least squares support vector regression

Support Vector Machines (SVMs) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on a method of least squares SVM (LS-SVM) for multivariate function estimation, a generalized inverse system is developed for the linearization and decoupling control of a general nonlinear continuous system. The approach of inverse modelling via LS-SVM and parameters optimization using the Bayesian evidence framework is discussed in detail. In this paper, complex high-order nonlinear system is decoupled into a number of pseudo-linear Single Input Single Output (SISO) subsystems with linear dynamic components. The poles of pseudo-linear subsystems can be configured to desired positions. The proposed method provides an effective alternative to the controller design of plants whose accurate mathematical model is un- known or state variables are difficult or impossible to measure. Simulation results showed the efficacy of the method.

Fault detection and optimization for networked control systems with uncertain time-varying delay

The observer-based robust fault detection filter design and optimization for networked control systems(NCSs) with uncertain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new threshold function is established, and the solution of the optimization problem is given by using the singular value decomposition(SVD)of the matrix. A numerical example is provided to illustrate the effectiveness of the proposed approach.

Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight

Aiming at tracking control of a class of innovative control effector(ICE) aircraft with distributed arrays of actuators, this paper proposes a control allocation scheme based on the Lévy flight.Different from the conventional aircraft control allocation problem,the particular characteristic of actuators makes the actuator control command totally subject to integer constraints. In order to tackle this problem, first, the control allocation problem is described as an integer programming problem with two desired objectives. Then considering the requirement of real-time, a metaheuristic algorithm based on the Lévy flight is introduced to tackling this problem. In order to improve the searching efficiency, several targeted and heuristic strategies including variable step length and inherited population initialization according to feedback and so on are designed. Moreover, to prevent the incertitude of the metaheuristic algorithm and ensure the flight stability, a guaranteed control strategy is designed. Finally, a time-varying simulation model is introduced to verifying the effectiveness of the proposed scheme. The contrastive simulation results indicate that the proposed scheme achieves superior tracking performance with appropriate actuator dynamics and computational time, and the improvements for efficiency are active and the parameter settings are reasonable.

A survey on delayed feedback control of chaos

This paper introduces the basic idea and provides the mathematical formulation of the delayed feedback control (DFC) methodology, which has been widely used in chaos control. Stability analysis including the well_known odd number limitation of the DFC is reviewed. Some new developments in characterizing the limitation of the DFC are presented. Various modified DFC methods, which are developed in order to overcome the odd number limitation, are also described. Finally, some open problems in this research field are discussed.

ESO-based robust predictive control of lunar module with fuel sloshing dynamics

An extended-state-observer(ESO) based predictive control scheme is proposed for the autopilot of lunar landing.The slosh fuel masses exert forces and torques on the rigid body of lunar module(LM),such disturbances will dramatically undermine the stability of autopilot system.The fuel sloshing dynamics and uncertainties due to the time-varying parameters are considered as a generalized disturbance which is estimated by an ESO from the measured attitude signals and the control input signals.Then a continuous-time predictive controller driven by the estimated states and disturbances is designed to obtain the virtual control input,which is allocated to the real control actuators according to a deadband logic.The 6-DOF simulation results reveal the effectiveness of the proposed method when dealing with the fuel sloshing dynamics and parameter perturbations.