Fuzzy adaptive event-triggered control for uncertain nonlinear system with prescribed performance: A combinational measurement approach

This paper addresses the adaptive fuzzy event-triggered control (ETC) problem for a class of nonlinear uncertain systems with unknown nonlinear functions. A novel ETC approach that exhibits a combinational triggering (CT) behavior is proposed to update the controller and fuzzy weight vectors, achieving the non-periodic control input signals for nonlinear systems. A CT-based fuzzy adaptive observer is firstly constructed to estimate the unmeasurable states. Based on this, an output feedback ETC is proposed following the backstepping and error transformation methods, which ensures the prescribed dynamic tracking (PDT) performance. The PDT performance indicates that the transient bounds, over-shooting and ultimate values of tracking errors are fully determined by the control parameters and functions chosen by users. The closed-loop stability is guaranteed under the framework of impulsive dynamic system. Besides, the Zeno phenomenon is circumvented. The theoretical analysis indicates that the proposed scheme guarantees control performance while considerably reducing the communication resource utilization and controller updating frequency. Finally, the numerical simulations are conducted to verify the theoretical findings.     

Event-driven NN adaptive fixed-time control for nonlinear systems with guaranteed performance

This article investigates the adaptive neural network fixed-time tracking control issue for a class of strict-feedback nonlinear systems with prescribed performance demands, in which the radial basis function neural networks (RBFNNs) are utilized to approximate the unknown items. First, an modified fractional-order command filtered backstepping (FOCFB) control technique is incorporated to address the issue of the iterative derivation and remove the impact of filtering errors, where a fractional-order filter is adopted to improve the filter performance. Furthermore, an event-driven-based fixed-time adaptive controller is constructed to reduce the communication burden while excluding the Zeno-behavior. Stability results prove that the designed controller not only guarantees all the signals of the closed-loop system (CLS) are practically fixed-time bounded, but also the tracking error can be regulated to the predefined boundary. Finally, the feasibility and superiority of the proposed control algorithm are verified by two simulation examples.     

Finite-time performance guaranteed event-triggered adaptive control for nonlinear systems with unknown control direction

This paper studies the issue of finite-time performance guaranteed event-triggered (ET) adaptive neural tracking control for strict-feedback nonlinear systems with unknown control direction. A novel finite-time performance function is first constructed to describe the prescribed tracking performance, and then a new lemma is given to show the differentiability and boundedness of the performance function, which is important for the verification of the closed-loop system stability. Furthermore, with the help of the error transformation technique, the origin constrained tracking error is transformed into an equivalent unconstrained one. By utilizing the first-order sliding mode differentiator, the issue of “explosion of complexity” caused by the backstepping design is adequately addressed. Subsequently, an ingenious adaptive updated law is given to co-design the controller and the ET mechanism by the combination of the Nussbaum-type function, thus effectively handling the influences of the measurement error resulted from the ET mechanism and the challenge of the controller design caused by the unknown control direction. The presented event-triggered control scheme can not only guarantee the prescribed tracking performance, but also alleviate the communication burden simultaneously. Finally, numerical and practical examples are provided to demonstrate the validity of the proposed control strategy.     

Barrier function-based nonsingular prescribed performance terminal sliding mode tracker for under-actuated nonlinear systems: Experimental study

In this paper, an adaptive concave barrier function scheme coupled with the non-singular terminal sliding mode control technique is proposed for finite-time tracking control of the under-actuated nonlinear system in the existence of model uncertainty, external disturbance and input saturation. Firstly, the dynamical equation of under-actuated nonlinear n-order system is expressed under model uncertainty, external disturbance and input saturation. Secondly, for the improvement of stability performance of the system in the existence of input saturation, a compensation system is designed to overcome the constraint on the control input. Afterward, the tracking errors between actual states of the system and differentiable reference signals are defined and the sliding surface based on the defined tracking errors is presented. Then, for gaining the better transient and steady-state performance of the closed-loop system, the prescribed performance control scheme is adopted. Based on this method, the transformed prescribed form of the previous determined sliding surface is obtained to ensure that the sliding surface can reach to a predefined region. Afterward, for assurance of the finite-time reachability of transformed sliding surface, the nonsingular terminal sliding surface is recommended. In addition, for the compensation of the model uncertainty and external disturbance existed in the system, the adaptive-based concave barrier function technique is used to estimate the unknown bounds of uncertainty and exterior disturbance. Finally, for demonstration of the proposed control method, the simulations and experimental implementation are done on the air levitation system.     

Adaptive prescribed performance control for nonlinear robotic systems

This paper investigates the problem of asymptotic tracking control of nonlinear robotic systems with prescribed performance. The control strategy is developed based on a modified prescribed performance function (PPF) to guarantee the transient behavior, while the requirements on the accurate initial tracking error in the classical PPF can be remedied. The fuzzy logic system (FLS) is used to approximate the unknown dynamics. In the existing PPF based adaptive control schemes with FLSs, the tracking error does not achieve asymptotic convergence. To address this issue, a robust integral of the sign of the error (RISE) term is incorporated into the control design to reject the FLS approximation errors and external disturbances, such that the asymptotic convergence is achieved. Finally, numerical simulation and experimental results validate the effectiveness of the proposed control scheme.     

Prescribed-time containment control with prescribed performance for uncertain nonlinear multi-agent systems

The existing studies on prescribed-time control cannot directly deal with nonlinear functions which don’t satisfy Lipschitz growth conditions. No results are available for prescribed-time containment control of pure-feedback UNMASs with prescribed performance. Therefore, completely unknown nonlinear function, prescribed-time tracking of system states and prescribed performance of containment errors are simultaneously considered in this paper. Fuzzy logic systems are utilized to approximate completely unknown nonlinear function. Prescribed-performance function is introduced and further incorporated into a novel speed function. Combining the proposed speed function and barrier Lyapunov function, this article presents a novel adaptive fuzzy prescribed-time containment control method which can guarantee, under prescribed performance, all followers converge to a convex formed by dynamic leaders in a prescribed time. Moreover, all tracking errors converge to predefined regions in a prescribed time. The effectiveness of the proposed prescribed-time containment control method are confirmed by strict proof and simulation.     

Adaptive fault-tolerant control with prescribed performance for switched nonlinear pure-feedback systems

In this paper, the problem of adaptive fuzzy fault-tolerant control is investigated for a class of switched uncertain pure-feedback nonlinear systems under arbitrary switching. The considered actuator failures are modeled as both lock-in-place and loss of effectiveness. By utilizing mean value theorem, the considered pure-feedback systems are transformed into a class of switched nonlinear strict-feedback systems. Under the framework of backstepping design technique and common Lyapunov function (CLF), an adaptive fuzzy fault-tolerant control (FTC) method with predefined performance bounds is developed. It is proved that under the proposed controller, all the signals of the close-loop systems are bounded and the state tracking error for each step remains within the prescribed performance bound (PPB) regardless of actuator faults and the system switchings. In addition, the tracking errors and magnitudes of control inputs can be reduced by adjusting the PPB parameters of errors in the first and last steps. The simulation results are provided to show the effectiveness of the proposed control scheme.     

Control of connected vehicles with event-triggered transmission and prescribed energy budget

This paper is concerned with event-triggered cooperative control of a platoon of connected vehicles via vehicular ad hoc networks (VANETs). To reduce communications among vehicles, we introduce a hybrid event-triggered transmission mechanism based on both time elapsed and state error. The effect of time-varying transmission delay and communication energy constraint can be also taken into account in the system modeling and design procedures. The on-board sensors use different power levels to transmit information resulting in different packet loss rates. The vehicular platoon system is proved to be exponentially mean-square stable under the hybrid event-triggering scheme and a constant time headway spacing policy. A framework for co-design of the hybrid event triggering scheme and the output feedback controller is given to guarantee platoon stability and spacing-error convergence along the stream. Numerical simulations are given to demonstrate the effectiveness of proposed method.     

Distributed event-triggered control for networked control systems with stochastic cyber-attacks

This paper is concerned with the problem of distributed event-triggered controller design for networked control systems (NCSs) with stochastic cyber-attacks. A decentralized event-triggered scheme is introduced to save the energy consumption and alleviate the transmission load of the network. Each sensor can make its own decision to determine whether the sampled data is delivered to the network or not. By taking two kinds of random cyber-attacks into consideration, a novel mathematical model is constructed for distributed event-triggered NCSs. Sufficient conditions which can guarantee the stability of the control system are obtained by applying Lyapunov stability theory, and the design method of the controller gain is presented in an exact expression. Finally, an example is given to demonstrate the effectiveness of the proposed method.     

Improved decentralized prescribed performance control for non-affine large-scale systems with uncertain actuator nonlinearity

This work considers a decentralized control problem for non-affine large-scale systems with non-affine functions possibly being discontinuous. A semi-bounded condition for non-affine functions is presented to guarantee the controllability, and the non-affine system is transformed to an equivalent pseudo-affine one based on the mild condition. Different from conventional control schemes on specific actuator nonlinearity, the controller proposed in this paper can deal with a series of actuator nonlinearities such as backlash and deadzone nonlinearity. A time-varying stable manifold involving the tracking error and its high-order derivatives is utilized to handle the high-order dynamics of each subsystem. Besides an improved prescribed performance controller independent of the initial condition is constructed to ensure the finite-time convergence of the error manifold to a predefined region. The boundedness and convergence of the closed-loop system are proved by Lyapunov theory and the counter-evidence method. Two examples are performed to verify the theoretical findings.     

Global output feedback tracking control for switched nonlinear systems with deferred prescribed performance

In this paper, the global output feedback tracking control is investigated for a class of switched nonlinear systems with time-varying system fault and deferred prescribed performance. The shifting function is introduced to improve the traditional prescribed performance control technique, remove the constraint condition on the initial value, and make the constraint bounds have more alternative forms. To estimate the unmeasured state variables and compensate the system fault, the switched dynamic gain extended state observer is constructed, which relaxes the traditional Lipschitz conditions on the nonlinear functions. Based on the proposed observer, by constructing the new Lyapunov function and using the backstepping method, the global robust output feedback controller is designed to make the output track the reference signal successfully, and after the adjustment time, the tracking error enters into the prescribed set. The stability of the system is analyzed by the average dwell time method. Finally, simulation results are given to illustrate the effectiveness of the proposed method.     

Coordinated path following control for multi-unmanned surface vehicles with specified performance and periodic event-triggered mechanism

This paper addresses coordinated path following for underactuated multi-unmanned surface vehicles (MUSVs) with specified performance (SP) under the lumped disturbances, proposes a novel adaptive periodic event-triggered path following control strategy via relative threshold event-triggered mechanism. First, the MUSVs communicates through the directed topology cooperative control structure, and maintains a safe distance between each USV along one curve. Meanwhile, the transformed error function is applied to establish the position errors constraint, guaranteeing that the position error of each USV is confined within the specified performance in guidance system. Then, RBF neural network and adaptive parameter method are applied to estimate the lumped disturbances and its error boundary, which makes MUSVs’ coordinated system have strong anti-disturbance ability. Besides, periodic event-triggered control base on relative threshold is introduced, which not only reduces the update frequency of controller and energy consumption, also avoids Zeno behavior phenomenon. Stability analysis proves that coordinated path following control system is uniformly ultimately bounded. Comparative simulations reveal the effectiveness of the coordinated path following control scheme.     

Distributed event-triggered control for non-reliable networks

This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system. Two network protocols are proposed to deal with these communication effects. The stability of the system is analyzed for constant and time-dependent trigger functions, showing that asymptotic stability can be achieved with the latter design, and this also guarantees a lower bound for the inter-event times. Analytical expressions for the delay bound and the maximum number of consecutive packet losses are derived for different scenarios. Finally, the results are illustrated through a simulation example.     

Three-dimensional event-triggered fixed-time cooperative guidance law against maneuvering target with the constraint of relative impact angles

In order to improve the flexibility and reduce the energy consumption of cooperative guidance laws considering the impact angle constraint, this paper proposes a three-dimensional event-triggered fixed-time cooperative guidance law with the constraint of relative impact angles. First, for the purpose of avoiding the precision degradation due to the estimation error of time-to-go especially facing a maneuvering target, the range-to-go and velocity along the line-of-sight (LOS) are taken as the coordination variables for achieving time-cooperative guidance. Secondly, instead of assigning specific desired impact angles for each missile, only the consensus errors of relative impact angles are utilized as the coordination variables for achieving space-cooperative guidance, which can avoid continually maneuvering for maintaining the constant desired impact angles, thus reducing the fuel consumption. Next, the guidance laws along the LOS and perpendicular to the LOS are developed, and the event-triggering mechanisms are designed to reduce the update frequency of cooperative guidance commands, thus further reducing the energy consumption. To guarantee the convergence rate, the fixed-time control theory is adopted and the stability of proposed event-triggered cooperative guidance laws are rigorously proved. In addition, it is also proved that there is no Zeno behavior when implementing the proposed event-triggered cooperative guidance laws. Finally, numerical simulations indicate that the strictly simultaneous attack is achieved and the constraint of relative impact angles is satisfied. Comparative studies demonstrate that the computation burden of cooperative guidance commands is relaxed and the fuel consumption is reduced by the proposed event-triggered cooperative guidance laws with the constraint of relative impact angles.     

Data-driven discrete terminal sliding mode decoupling control method with prescribed performance

This paper proposes a data-driven terminal sliding mode decoupling controller with prescribed performance for a class of discrete-time multi-input multi-output systems in the presence of external disturbances and uncertainties. First, utilizing a discrete-time extended state observer and a compact form dynamic linearization data model, we derive a new data-driven mothod and establish the relationship between the input and output signals of controlled plant. Moreover, the disturbances, uncertainties, and couplings are suppressed owing to the application of the terminal sliding mode technique. Combined with the principle of prescribed performance control, the terminal sliding mode law with prescribed performance is derived. With the proposed data-driven method, the tracking error is lower, and the decoupling ability is improved. Furthermore, the stability of the control system is proven. Finally, a simulation is conducted on a three-tank system to demonstrate the effectiveness of the proposed scheme.     

Intelligent control for robotic manipulator with adaptive learning rate and variable prescribed performance boundaries

The purpose of this study is to enhance the transient performance and mitigate the possible boundary-crossing issue during the design of a neural network-based intelligent prescribed performance control for robotic manipulators that suffer from input saturation. Initially, an auxiliary system is created utilizing the saturation signal, which is then used to modify the prescribed performance boundaries when saturation takes place. This ensures that the tracking errors adhere to the performance constraints even if the available control effort is limited. To further enhance the transient performance of the closed-loop system, a composite learning-based online identification scheme employing a Gaussian function to adaptively adjust the learning rate is utilized instead of a fixed-learning-rate weight updating law to train the neural network. This approach facilitates the reduction of the undesired weight oscillations at the beginning of the control process when the neural network is not sufficiently trained. Lastly, the stability of the closed-loop system is demonstrated by applying the Lyapunov approach, and simulation results support the effectiveness of the identification and control schemes proposed in this study.     

Fuzzy event-triggered control for nonlinear networked control systems

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated.     

Integral predictor based prescribed performance control for multi-motor driving servo systems

An integral predictor-based dynamic surface control scheme is developed with prescribed performance (IPPDSC) for multi-motor driving servo systems in this paper. By employing a novel finite-time performance function and an improved error transformation, the tracking error is limited within a prescribed zone in any preset time without having the overrun and the singularity problem. Furthermore, integral state predictors are designed to update neural network weights to handle high-frequency oscillations under large adaptive gains. Different from the existing approaches, an integral term of prediction error is introduced to eliminate the steady-state error and avoid chattering. In addition, a synchronization controller based on the mean relative coupling structure is proposed to solve the coupling problem between synchronization and tracking. Finally, simulation and experimental results are presented to demonstrate the effectiveness of the designed approach.     

Barrier function-based prescribed-performance adaptive attitude tracking control for spacecraft with uncertainties

This paper addresses the problem of robust adaptive attitude tracking control for spacecraft with mismatched and matched uncertainties. The idea of disturbance estimation and compensation is introduced into the control design. First, finite-time disturbance observers are developed for different channels of spacecraft based on barrier functions for achieving finite-time asymptotic estimates of unknown bounded uncertainties in the system. Second, a class of prescribed performance functions is considered in the design of the barrier function. The spacecraft attitude adaptive tracking control strategy with finite-time convergence capability and prescribed performance is proposed based on the designed finite-time disturbance observers and barrier function. Finally, the theoretical findings are verified by numerical simulations and compared with the simulation results of existing methods.