Novel delay-partitioning stabilization approach for networked control system via Wirtinger-based inequalities

This paper studies the problems of stability analysis and state feedback stabilization for networked control system. By developing a novel delay-partitioning approach, the information on both the range of network-induced delay and the maximum number of consecutive data packet dropouts can be taken into full consideration. Various augmented Lyapunov–Krasovskii functionals (LKFs) with triple-integral terms are constructed for the two delay subintervals. Moreover, the Wirtinger-based inequalities in combination with an improved reciprocal convexity are utilized to estimate the derivatives of LKFs more accurately. The proposed approaches have improved the stability conditions without increasing much computational complexity. Based on the obtained stability criterion, a stabilization controller design approach is also given. Finally, four numerical examples are presented to illustrate the effectiveness and outperformance of the proposed approaches.     

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ‘‘frozen-time' assumption are not able to determine the dynamic stability of LTV systems.Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.     

Inducing sustained oscillations in feedback-linearizable single-input nonlinear systems

The present paper concerns the induction of stable sustained oscillation in feedback-linearizable single-input affine nonlinear dynamical systems via continuous-time state feedback control. The proposed application-oriented control approach is based on the conception of a state feedback controller that ensures the tracking of a limit cycle characterized in terms of the feedback-linearized system. Boundedness and convergence of the closed-loop trajectories are established following the Lyapunov theoretical framework and applying LaSalle׳s stability principle. The proposed approach is demonstrated with computer-simulated control experiments, showing that it ensures the convergence of the state trajectories of the controlled system to a designed limit cycle and that the methodology can, in principle, be applied to any single input feedback linearizable system.     

An unknown input multiobserver based on a discrete uncoupled multimodel for uncertain nonlinear systems: Experimental validation on a transesterification reactor

In the present paper, an unknown input multiobserver (UIMO) is designed for the state estimation of uncertain non-linear systems. A discrete decoupled state multimodel is exploited to describe the behavior of non-linear systems. A particular transformation of uncertainties to unknown inputs is considered. The LMI approach is used to establish the convergence conditions of the state estimation error. The efficiency of the proposed strategy is emphasized through an illustrative example and a real time application on a semi-batch reactor that lead to good performance in terms of robustness, convergence speed and precision.     

Research Methodology for Grinding Systems

A research methodology is proposed for grinding systems, for the example of gear grinding by copying on CNC machine tools. In this approach, the system is characterized in terms of input, state, and output. Methods of modeling, optimization, and control at the production and preproduction stages are described. Analysis is possible on the basis of probabilistic and frequency approaches.     

Finite-time resilient decentralized control for interconnected impulsive switched systems with neutral delay

This paper is concerned with the problem of finite-time control for a class of interconnected impulsive switched systems with neutral delay in which the time-varying delay appears in both the state and the state derivative. The concepts of finite-time boundedness and finite-time stability are respectively extended to interconnected impulsive switched systems with neutral delay for the first time. By applying the average dwell time method, sufficient conditions are first derived to cope with the problem of finite-time boundedness and finite-time stability for interconnected impulsive switched systems with neutral delay. In addition, the purpose of finite-time resilient decentralized control is to construct a resilient decentralized state-feedback controller such that the closed-loop system is finite-time bounded and finite-time stable. All the conditions are formulated in terms of linear matrix inequalities to ensure finite-time boundedness and finite-time stability of the given system. Finally, an example is presented to illustrate the effectiveness of the proposed approach.     

Event-triggered control design of linear networked systems with quantizations

This paper is concerned with the control design problem of event-triggered networked systems with both state and control input quantizations. Firstly, an innovative delay system model is proposed that describes the network conditions, state and control input quantizations, and event-triggering mechanism in a unified framework. Secondly, based on this model, the criteria for the asymptotical stability analysis and control synthesis of event-triggered networked control systems are established in terms of linear matrix inequalities (LMIs). Simulation results are given to illustrate the effectiveness of the proposed method.     

Partial state estimation for linear systems with output and input time delays

This paper deals with the problem of partial state observer design for linear systems that are subject to time delays in the measured output as well as the control input. By choosing a set of appropriate augmented Lyapunov–Krasovskii functionals with a triple-integral term and using the information of both the delayed output and input, a novel approach to design a minimal-order observer is proposed to guarantee that the observer error is ε-convergent with an exponential rate. Existence conditions of such an observer are derived in terms of matrix inequalities for the cases with time delays in both the output and input and with output delay only. Constructive design algorithms are introduced. Numerical examples are provided to illustrate the design procedure, practicality and effectiveness of the proposed observer.     

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.     

Stabilization of systems with interval time-varying delay based on delay decomposing approach

The paper considers the stabilization for systems with interval time-varying delay. By decomposing the delay interval into multiple equidistant subintervals and considering the triple integral terms, a novel Lyapunov-krasovskii functional(LKF) is defined. Then extended integral inequality and convex combination approach are used to estimate the derivative of the constructed functional, and as a result, the new stability criterion with less conservatism and decision variables is obtained. On this basis, the state feedback controller is designed, by using linearization method, the existence condition of controller is obtained in terms of linear matrix inequalities(LMIs), and the specific form of controller is also given, moreover, by selecting the appropriate parameter value, the stabilization time of the system can be reduced. Numerical examples are given to illustrate the effectiveness of the proposed method.     

State space approach to qualitative analysis of FMSs

A new approach, based on state space analysis using projections, is proposed for analysing flexible manufacturing systems (FMS), and used for their qualitative analysis (QA). The concept of the ‘first generation reachability graph’ is introduced, and a methodology for QA developed. The use of this methodology for evaluating specifications in terms of correctness and desirability is shown, the PROjection-based State Space ANalyser, (PRO-SPAN), a software package designed to automate the analysis methods developed in this paper, is presented. A modified Petri net model, consisting of up to 3000 places and 3100 transitions, is used by PRO-SPAN for constructing the state space for an FMS.     

Distributed robust adaptive control of high order nonlinear multi agent systems

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust.     

Robust-optimal active vibration controllers design for the uncertain flexible mechanical systems possessing integrity via genetic algorithm

In this paper, a robust-optimal control approach is proposed to treat the active vibration control (or active vibration suppression) problem of flexible mechanical systems under mode truncation, linear time-varying parameter uncertainties in both the controlled and residual parts, feedback gain perturbations, estimator gain perturbations and partial actuator failures. A sufficient condition is proposed to ensure that the flexible mechanical systems with time-varying structured parameter uncertainties are asymptotically stable against partial actuator failures. Systems which have such a property of keeping stable under partial actuator failures are said to possess integrity, and this is an inherent property of MIMO systems. Based on the robust stability constraint and the minimization of a defined H₂ performance, a hybrid Taguchi-genetic algorithm (HTGA) is applied to solve the optimal state feedback controller and observer design problem of uncertain flexible mechanical systems. A design example of a flexible rotor system is given to demonstrate the applicability of the proposed approach. It is shown that the proposed approach can obtain satisfactory results.     

New stability and stabilization conditions for nonlinear systems with time-varying delay based on delay-partitioning approach

This paper focuses on stability analysis and stabilization of nonlinear systems with interval time-varying delay, modeled by Takagi-Sugeno (T-S) fuzzy approach. To achieve more relaxation in the feasibility region, delay-partitioning approach is used for all integral terms in the Lyapunov-Krasovskii functional (LKF). A fuzzy Lyapunov function is proposed instead of non-integral term in LKF, and moreover, some slack matrices variables are offered to enlarge the design space. By doing this, new delay-dependent stability criteria are obtained. During the derivation of stability conditions, Jensen’s integral inequality is applied to deal with integral terms. Furthermore, in this paper the problem of controller design via the parallel distributed compensation (PDC) scheme is studied. Stability and stabilization conditions with less conservative are achieved in terms of linear matrix inequality (LMI). Finally, two numerical examples are presented to show the effectiveness of the proposed results.     

Analysis and experiments of iterative learning-control system with uncertain dynamics

An iterative error compensation approach is proposed in this article to improve the accuracies of high speed, computer-controlled machining processes. It is well known that the high-speed computer-numerically-controlled (CNC) machines are extremely useful in terms of manufacturing mass-produced parts. The proposed method uses an iterative learning technique that adopts the servo commands and cutting error experienced in previous maneuvers as references to current compensative actions. Moreover, non-repetitive disturbances and nonlinear dynamics of the cutting processes, and servo systems of the CNC machine that greatly affect the convergence of the learning-control systems were also studied in this research. State feedback and output feedback techniques were adopted in the proposed controller design. In addition to the stability analysis, a 1 degree-of-freedom servo positioning system is constructed to evaluate the performance of our proposed learning control approach. Both the simulation and experimental results verify the effectiveness of our approach.     

Robust stability and stabilization of fractional order linear systems with positive real uncertainty

This paper investigates the robust stability and stabilization of fractional order linear systems with positive real uncertainty. Firstly, sufficient conditions for the asymptotical stability of such uncertain fractional order systems are presented. Secondly, the existence conditions and design methods of the state feedback controller, static output feedback controller and observer-based controller for asymptotically stabilizing such uncertain fractional order systems are derived. The results are obtained in terms of linear matrix inequalities. Finally, some numerical examples are given to validate the proposed theoretical results.     

Calculating the reliability of shafts with probability and possibility variables in the limiting-state model

A new approach is proposed in calculating the reliability of shafts in any mechanical systems. In this approach, the basic parameters in the mathematical model of the limiting state are a combination of random and fuzzy variables, when probabilistic and statistical methods cannot be used for reliability calculation.     

Discrete state space modeling and control of nonlinear unknown systems

A novel procedure for integrating neural networks (NNs) with conventional techniques is proposed to design industrial modeling and control systems for nonlinear unknown systems. In the proposed approach, a new recurrent NN with a special architecture is constructed to obtain discrete-time state-space representations of nonlinear dynamical systems. It is referred as the discrete state-space neural network (DSSNN). In the DSSNN, the outputs of the hidden layer neurons of the DSSNN represent the system's (pseudo) state. The inputs are fed to output neurons and the delayed outputs of the hidden layer neurons are fed to their inputs via adjustable weights. The discrete state space model of the actual system is directly obtained by training the DSSNN with the input–output data. A training procedure based on the back-propagation through time (BPTT) algorithm is developed. The Levenberg–Marquardt (LM) method with a trust region approach is used to update the DSSNN weights. Linear state space models enable to use well developed conventional analysis and design techniques. Thus, building a linear model of a system has primary importance in industrial applications. Thus, a suitable linearization procedure is proposed to derive the linear state space model from the nonlinear DSSNN representation. The controllability, observability and stability properties are examined. The state feedback controllers are designed with both the linear quadratic regulator (LQR) and the pole placement techniques. The regulator and servo control problems are both addressed. A full order observer is also designed to estimate the state variables. The performance of the proposed procedure is demonstrated by applying for both single-input single-output (SISO) and multiple-input multiple-output (MIMO) nonlinear control problems.     

Multibody approach for tolerance analysis and optimization of mechanical systems

A multibody approach is suitable for tolerance analysis of mechanical systems since multibody formulation can directly consider part-level tolerance variables. In this study, procedures for performing tolerance analysis and corresponding sensitivity analysis for spatial multibody systems are proposed. First, statistical formulation for performing multibody system tolerance analysis is developed to obtain system level tolerance for given part-level tolerances. One very useful aspect of the proposed formulation is that in the process of computing system tolerance, the sensitivity of system tolerance with respect to part-level tolerances can be additionally obtained. The kinematics of spatial multibody systems has been redefined in terms of both generalized coordinates and part-level tolerance variables. Tolerances in geometry of a body are specified in terms of the variations in relative locations of joint definition points and relative distance between them. Tolerances in the joint kinematics are defined through variations in vector closure equations and orthogonality equations that are two fundamental constraint equations for most kinematic joints. To demonstrate the validity and effectiveness of the proposed tolerance analysis procedure, tolerance analysis of a spatial 4-bar mechanism and tolerance optimization are performed.     

Asymptotic stability and stabilizability of nonlinear systems with delay

This paper is concerned with asymptotic stability and stabilizability of a class of nonlinear dynamical systems with fixed delay in state variable. New sufficient conditions are established in terms of the system parameters such as the eigenvalues of the linear operator, delay parameter, and bounds on the nonlinear parts. Finally, examples are given to testify the effectiveness of the proposed theory.