Fuzzy sliding mode control design of Markovian jump systems with time-varying delay

This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.     

Disturbance rejection for time-delay systems based on the equivalent-input-disturbance approach

This paper presents a disturbance rejection method for time-delay systems. The configuration of the control system is constructed based on the equivalent-input-disturbance (EID) approach. A modified state observer is applied to reconstruct the state of the time-delay plant. A disturbance estimator is designed to actively compensate for the disturbances. Under such a construction of the system, both matched and unmatched disturbances are rejected effectively without requiring any prior knowledge of the disturbance or inverse dynamics of the plant. The presentation of the closed-loop system is derived for the stability analysis and controller design. Simulation results demonstrate the validity and superiority of the proposed method.     

Disturbance rejections and synchronization of fractional-order fuzzy complex networks

This paper deals with the problem of disturbance rejection and synchronization of fractional-order complex dynamical networks subject to nonlinear coupling strength and discontinuous nonlinear functions. Notably, the nonlinear coupling strength is linearised by using a well-known Takagi-Sugeno fuzzy approach. The considered system is transformed into a nominal form by employing the uncertainty and disturbance estimator-based control approach, which simplifies the control objective and improves the system performance. Second, the uncertainty and disturbance estimator is incorporated into the traditional feedback control scheme to reject the unknown disturbance and uncertainty. Then, the required synchronization conditions for both the discontinuous and continuous fractional-order systems are obtained by using Lyapunov stability and fractional calculus theories. Last, numerical examples are provided to illustrate the efficiency of the proposed control strategy, wherein it is shown that the system yields better satisfactory tracking performance and high robustness against possible disturbance and uncertainties and finite set of jump discontinuous nonlinear functions. Moreover, the selection of appropriate filter design is discussed for various kinds of disturbance signals.     

Anti-disturbance stabilization for a hybrid system of non-uniform elastic string

This paper is concerned with the anti-disturbance boundary feedback stabilization for a hybrid system coupling a non-uniform elastic string with a rigid body at one end by the active disturbance rejection control technology. An infinite-dimensional disturbance estimator and a Luenberger state observer are designed to estimate the disturbance and state of the system, respectively, based on which, a boundary output feedback control is further proposed to stabilize the system. The control consists of two parts: one part is for the stabilization of system without external disturbance, and the other part is for the rejection of the disturbance by virtue of the disturbance estimator. The well-posedness and exponential stability of the closed-loop system are proved by employing the semigroup theories and frequency domain method. Besides, all the signals of the closed-loop system are shown to be uniformly bounded. Finally, some numerical simulations are presented to validate the effectiveness of the proposed control strategy.     

A case study on the universal compensation-improvement mechanism: A robust PID filter-shaped optimal PI tracker for systems with/without disturbances

Many dynamical systems are continuous-time non-square with unknown mismatched input and output disturbances. For such systems, a universal on-line robust optimal tracking control is often desirable. In this paper, the conventional proportional-integral-differential (PID) controller is utilized as a fictitious PID filter to shape the tracking error in the frequency-domain using a quadratic performance index as a weighting function, such that the robust PID-shaped PI tracker integrated with the equivalent input disturbance (EID) estimator is established to carry out the on-line robust optimal tracking control of the general disturbed system. The benefits and discrepancies of the proposed compensation improvement mechanism over the conventional optimal trackers for continuous-time non-square systems with/without unknown mismatched input and output disturbances are listed as follows: (i) It develops a new net EID estimator without any previously established constraints on the dimensions of the system and on the disturbances; (ii) It provides an efficient estimated-state-feedback-based EID estimator in contrast to the conventional output-feedback-based EID estimators; (iii) It is able to carry out on-line EID estimation of the tracking errors for systems with endogenous/exogenous output disturbances; (iv) It is a universal tracker which can be simply implemented as a plug-in EID estimator for most servo systems, to improve the performance of any existing observers/trackers which are not allowed to be removed from the system. The advantages of the proposed method over two existing outstanding approaches reported in the literature are pointed out using illustrative examples.     

Disturbance rejection and control system design based on a high-order equivalent-input-disturbance estimator

This paper presents an improved equivalent-input-disturbance (EID) approach to deal with exogenous disturbances. A high-order filter is newly used to construct an improved EID estimator. The parameters of the filter are selected to improve the disturbance-rejection performance without changing the bandwidth of an EID-based control system. The stability and disturbance-rejection mechanism of the system are analyzed using the transfer function from the EID to the output. The high-order filter is designed using the loop-shaping method. Simulation results of a rotational control system demonstrate the validity of the approach and superiority over other methods.     

Enhanced Finite Spectrum Assignment with disturbance compensation for LTI systems with input delay

This paper presents a Finite Spectrum Assignment (FSA) with a generalized feedforward control for Linear Time-Invariant (LTI) systems with input delay and bounded unmeasured disturbances. A novel two-layer feedforward strategy is proposed in order to deal with matched and unmatched disturbances. The proposed control law is based on a filtered disturbance estimator and a generalized feedforward compensation which can be applied to any Artstein based predictor. An optimization design procedure is presented to improve disturbance attenuation properties in the presence of band-limited disturbances. The conditions to achieve disturbance rejection are also shown to deal with deterministic disturbance models. Furthermore, the proposed solution can be used to define either continuous-time or discrete-time control algorithms. Two case studies are presented to illustrate the benefits of the new approach.     

Application of active disturbance rejection control in tank gun control system

The problem of position tracking for a tank gun control system with inertia uncertainty and external disturbance is investigated in this paper. The tank gun control system, demanding high tracking precision and stabilization precision, is a nonlinear system. Classical control methods are commonly used in the actual system, which is difficult to ensure high precision and high disturbance rejection capability. An active disturbance rejection control (ADRC) scheme is applied to guarantee the state variables of the closed loop system to converge to the reference state with the help of the extended state observer by estimating the inertia uncertainty and external disturbance. The basic theory of the ADRC is introduced here. According to the mathematical model, the parameters of ADRC are designed. Also, simulation results show that ADRC controller has advantages of high precision and high disturbance rejection ability. A comparison between ADRC and PID is also presented to show the effectiveness of the ADRC control strategy.     

Actuator failure compensation and attitude control for rigid satellite by adaptive control using quaternion feedback

The attitude control problem of a rigid satellite with actuator failure uncertainties and external disturbance is addressed using adaptive control method. A discontinuous adaptive failure compensation controller, using unit quaternion and angular velocities feedback, is designed to accommodate the external disturbance and actuator failures which are uncertain in time instants, values and patterns. A common approximate function is used to avoid system chattering caused by such discontinuous control laws. The parameters of external disturbance and failure uncertainties are estimated directly by adaptive laws, and the desired stability and output tracking properties of the adaptive control system are analyzed. Finally, simulation results of a rigid satellite with six reaction wheels are presented to illustrate the performance of the proposed adaptive actuator failure compensation scheme.     

Approximate decoupling and output tracking for MIMO nonlinear systems with mismatched uncertainties via ADRC approach

In this paper, we consider output tracking for a class of MIMO nonlinear systems which are composed of coupled subsystems with vast mismatched uncertainties. First, all uncertainties influencing the performance of controlled outputs, which include internal unmodelled dynamics, external disturbances, and uncertain nonlinear interactions between subsystems, are refined into the total disturbance in the control channels of subsystems. The total disturbance is shown to be sufficiently reflected in the measured output of each subsystem so that it can be estimated in real time by an extended state observer (ESO) in terms of the measured outputs. Second, we decouple approximately the MIMO systems by cancelling the total disturbance based on ESO estimation so that each subsystem becomes approximately independent linear time invariant one without uncertainty and interaction with other subsystems. Finally, we design an ESO based output feedback for each subsystem separately to ensure that the closed-loop state is bounded, and the closed-loop output of each subsystem tracks practically a given reference signal. This is completely in comply with the spirit of active disturbance rejection control (ADRC). Some numerical simulations are presented to demonstrate the effectiveness of the proposed output feedback control scheme.     

Cluster synchronization of fractional-order complex networks via uncertainty and disturbance estimator-based modified repetitive control

The combined problems of cluster synchronization and disturbance rejection for a family of fractional-order complex networks subject to coupling delay, unknown uncertainty and disturbances (UDs) are examined in this study. In particular, the existence of coupling delay is taken into the account with both known and unknown cases. First, a new uncertainty and disturbance estimator (UDE)-based control protocol is formulated for the concerned system to estimate and compensate for the effects of UD. Although the UDE strategy has proven to be a viable tool to deal with slowly changing UDs in control design, the presence of rapidly changing UDs or sinusoidal disturbances is not an effective tool. A well-known modified iterative control (MRC) block is built internally in a closed feedback control loop to solve this problem. After implementing UDE and MRC blocks into the feedback loop, the resulting system becomes almost UD-free. Moreover, a set of sufficient linear matrix inequality constraints are established to ensure the cluster synchronization of the resulting system. Lastly, the benefits, feasibility and robustness of the established UDE-based MRC scheme are confirmed by two illustrative examples.     

Distributed state estimator-based consensus tracking of multi-agent systems with exogenous disturbance

The consensus tacking problem for multi-agent systems with a leader of none control input and unknown control input is studied in this paper. By virtue of the relative state information of neighboring agents, state estimator and disturbance estimator are designed for each follower to estimate the system states and exogenous disturbance, respectively. Meanwhile, a novel control protocol based on two estimators is designed to make tracking error eventually converge to zero. Furthermore, the obtained results are further extended to the leader with unknown control input. A novel state estimator with adaptive time-varying gain is proposed such that consensus tracking condition is independent of the Laplacian matrix with regard to the communication topology. Finally, two examples are presented to verify the feasibility of the proposed control protocol.     

Event-triggered dissipative state estimation for Markov jump neural networks with random uncertainties

This paper is concerned with the problem of event-triggered dissipative state estimation for Markov jump neural networks with random uncertainties. The event-triggered mechanism is introduced to save the limited communication bandwidth resource and preserve the desired system performance. The phenomenon of randomly occurring parameter uncertainties is considered to increase utilizability of the proposed method. To describe such a randomly occurring phenomenon, some mutually independent Bernoulli distributed white sequences are adopted. A mode-dependent state estimator is designed in this paper, which ensures that the estimation error system is extended stochastically dissipative. By using the Lyapunov–Krasovskii functional approach and an optimized decoupling approach, an expected state estimator can be built by solving some sufficient conditions. Two numerical examples are presented to demonstrate the correctness and effectiveness of the proposed method.     

Design of a preview repetitive control with equivalent-input-disturbance system based on a continuous-discrete 2D model

This paper deals with the problem of two-dimensional (2D) system-based preview repetitive control (PRC) with equivalent-input-disturbance (EID) for uncertain continuous-time systems. First, to use the available values of the reference signal, we construct an equality constraint which includes the output of a basic repetitive controller, preview compensation and tracking error. Next, to compensate the unknown external disturbances, we incorporate an EID estimator into the PRC controller. Then, by employing the 2D system theory together with the linear matrix inequality (LMI) approach, we derive a sufficient condition to ensure the robust stability of the closed-loop system. By solving an LMI, the gains of the controller and state observer can be obtained. The results obtained in this paper generalize and include some results in the existings. literature. Finally, a numerical simulation demonstrates the effectiveness and superiority of the proposed method.     

Adaptive neural network control for flexible telerobotic systems with communication constraints

This paper investigates the synchronous control problem for a class of flexible telerobotic systems subject to system uncertainties and communication constraints. In view of the asymmetric time-varying communication delays, an adaptive time-delay estimator is designed to reduce the impacts of delays on the system. Moreover, by combining the neural networks and parameter adaptive method, the uncertainties of system dynamics are estimated and compensated. Based on these efforts, a new adaptive compensation control protocol is proposed. Additionally, input quantization in network control induced chattering phenomenon and unknown parameters is also dealt with by the adaptive compensation method. A useful characteristic of this paper is that the “complexity explosion” problem caused by the backstepping technique is circumvented effectively. Finally, sufficient conditions are derived for the synchronous control of the master-slave flexible telerobotic system under Lyapunov stability theory. A numerical example of flexible-joint robotic system is provided to illustrate the effectiveness of the proposed control schemes.     

Nonlinear model-predictive control with disturbance rejection property using adaptive neural networks

In this paper, a method is proposed to reject disturbances in the model predictive control (MPC) strategy. In addition, uncertainties in the system parameters (i.e., internal disturbances) are considered as well. To achieve these goals, adaptive neural networks are designed as the predictor model and as the nonlinear disturbance observer, respectively. The disturbances are rejected via the optimization problem of the MPC. Stability of the closed-loop system is studied based on the Input-to-State Stability method. The proposed method is applied to the pH neutralization process and CSTR system and its effectiveness in optimal rejection of the disturbances and satisfying the system constrains is compared with the feed-forward control method.     

Partial-state feedback adaptive stabilization for a class of nonlinear systems with uncertainties

This paper studies the adaptive asymptotically stabilizing control problem for a class of uncertain nonlinear systems by the partial-state feedback. The input-to-state stability (ISS) is used to describe the dynamic uncertainties, and a novel Nussbaum function is resorted to counteract the unknown identical control directions. The damping terms with the estimates of unknown disturbance bounds are inserted in control design to handle the nonvanishing external disturbances. It can be seen that all signals in closed-loop are bounded and the system states converge to zero asymptotically in spite of the uncertainties. Finally, a simulation example is introduced to show the effectiveness of the presented control scheme.     

Global fast terminal sliding mode controller for hydraulic turbine regulating system with actuator dead zone

This paper investigates the frequency change problem of hydraulic turbine regulating system based on terminal sliding mode control method. By introducing a novel terminal sliding mode surface, a global fast terminal sliding mode controller is designed for the closed loop. This controller eliminates the slow convergence problem which arises in the terminal sliding mode control when the error signal is not near the equilibrium. Meanwhile, following consideration of the error caused by the actuator dead zone, an adaptive RBF estimator based on sliding mode surface is proposed. Through the dead zone error estimation for feed-forward compensation, the composite terminal sliding mode controller has been verified to possess an excellent performance without sacrificing disturbance rejection robustness and stability. Simulations have been carried out to validate the superiority of our proposed methods in comparison with other two other kinds of sliding mode control methods and the commonly used PID and FOPID controller. It is shown that the simulation results are in good agreement with the theoretical analysis.     

Robust H∞ control of an observer-based repetitive-control system

This paper concerns the problem of designing a robust observer-based modified repetitive-control system with a prescribed H_∞ disturbance rejection level for a class of strictly proper linear plants with unknown aperiodic disturbances and time-varying structural uncertainties. A correction to the amount of the delay in the repetitive controller is introduced that leads to a significant improvement in tracking performance. An integrated performance index is defined to quantify the overall effect of rejecting the aperiodic disturbances and tracking the periodic reference input. A Lyapunov functional with two tuning parameters is used to derive a linear-matrix-inequality based robust stability condition for the system with a prescribed disturbance-rejection bound. Combining the performance indices, an optimization algorithm that searches for the best combination of state-observer gain and the feedback control gains is developed. A numerical example illustrates the design procedure and demonstrates the effectiveness of the method.     

A novel hybrid filter-based fault diagnosis algorithm for switched systems with a dual noise term

This study considers state and fault estimation for a switched system with a dual noise term. A zonotopic and Gaussian Kalman filter for state estimation is designed to obtain state estimation interval in the presence of both stochastic and unknown but bounded (UBB) uncertainties. The switching state and fault state of the system are distinguished by detecting whether the system measurement date is within the bounds of its predicted output. Once the switched time is detected in the system, the filter zonotopic and Gaussian Kalman functions are initialized. Once the fault time is detected, a zonotopic and Gaussian Kalman filter-based fault estimator is constructed to estimate the corresponding faults. Finally, a numerical simulation is presented to demonstrate the accuracy and effectiveness of the proposed algorithm.