International Journal of Robust and Nonlinear Control最新文献

This paper investigates the function of the artificial pancreas, which is devised based on a dynamical backstepping approach. The Bergman's minimal model, used to describe the glucose-insulin system, has been extended to encompass the dynamics of the insulin pump and external disturbances to closely simulate real-world scenarios. Three techniques, namely feedback linearization, conventional backstepping, and super-twisting sliding-mode control, are evaluated in comparison to dynamical backstepping in the context of regulating blood glucose levels in individuals with type-1 diabetes. In order to enhance the comparison of the controllers, we have taken into account the measurement noise and faults in the insulin pump as well. Additionally, Monte-Carlo analysis is utilized as a practical tool to experimentally evaluate the robustness of the nonlinear controllers against measurement errors and variations in model parameters for different individuals, as would be encountered in a clinical trial. The extensive numerical simulations confirm that the dynamical backstepping method closely emulates the functionality of the natural pancreas and surpasses the super-twisting sliding-mode control method, the feedback linearization method, and the conventional backstepping method when faced with measurement noise, insulin pump faults, and parameter variations.

This paper proposes a robust discrete-time integral fast terminal sliding mode predictive control (DIFTSMPC) scheme for DP ship trajectory tracking under the consideration of unmodeled dynamics, environmental disturbance, and input constraints. An improved single closed-loop control strategy is designed by adopting the earth-fixed reference velocity as the virtual velocity. The improved nonlinear PID discrete-time integral fast terminal sliding mode is designed to achieve faster convergence. The unknown nonlinear dynamics and the environmental disturbance are combined as a lumped uncertainty term and estimated using the one-step delay observation method. Then the corrected sliding model state is optimized to track the reference sliding reaching law in the prediction horizon. The lumped uncertainty estimation is integrated into the sliding mode prediction to guarantee the robustness of the control scheme. The stability of the proposed scheme has been verified. Comparison results demonstrate the effectiveness and superiority in chattering suppressing and constraint handling of the proposed scheme.

The focus of this paper is to discuss the asymptotic stability and exponential stability problems of Markovian jump bidirectional associative memory neural networks with Lévy noise based on the discrete observation. Compared with the existing literature, this paper gives a weaker assumption regarding Lévy noise intensity functions. Furthermore, for the sake of solving difficulties caused by the discrete observation and Lévy noise, this paper designs a new Lyapunov-Krasovskii functional which not only depends on the discrete observation interval, but also intensity measures. In virtue of the M-matrix theory, three theorems are obtained ensuring the mean-square asymptotic stability and mean-square exponential stability of the trivial solution. Our theorems can not only deal with the discrete observation, but also with constant delays and variable time delays. Ultimately, two numerical examples are presented to illustrate the correctness of our theory findings.

Obstacle avoidance, as an indispensable part of the autonomous driving process, plays an essential role in safeguarding vehicular safety. The intricacies of the driving environment coupled with the uncertainties in vehicle dynamics render the formulation of an obstacle avoidance strategy a formidable challenge. In this study, a novel obstacle avoidance control is proposed for autonomous vehicles that eschews local trajectory replanning based on the principle of constraint-following. Initially, trajectory tracking is achieved by formulating equality constraints on the vehicle's states, which are based on kinematic relationships between the desired trajectory and the controlled vehicle. By analyzing the geometric relationships between obstacles and the vehicle, the obstacle avoidance inequality constraints of the vehicle position are established. Based on a potential function, we transform the inequality constraints into equality constraints, thereby recasting the obstacle avoidance as a constraint-following control problem. Subsequently, a closed-form constraint force based on the Udwadia-Kalaba (U-K) approach and an adaptive law are put forward. Through Lyapunov minimax analysis, it has been demonstrated that the derived control ensures the constraint-following performance. Finally, the Simulink-CarSim co-simulations are implemented. The results indicate that the proposed control guarantees the vehicle trajectory tracking and collision-free performance.

To improve tracking control performance in the task space of the Stewart parallel mechanism (SPM) with uncertainties of modeling errors and external disturbances in our developed rust removal sandblasting robot for the surface roughness processing of a bridge's steel box girder, a fixed-time composite control with variable exponent coefficients (VEC-FxTCC) approach for multi-input multi-output (MIMO) nonlinear robotic systems is developed. Firstly, by devising only one regulation term with a variable exponent coefficient (VEC) function in the system's Lyapunov differential inclusion, a novel VEC fixed-time stability theorem for the MIMO nonlinear dynamic system is proposed and proven. Secondly, based on the proposed theorem, VEC-FxTCC is formed by designing and combining a VEC fixed-time disturbance observer (VEC-FxTDOB) and a VEC fixed-time super-twisting control (VEC-FxTSTC), in order to achieve fast, steady, and uniformly bounded-time convergence for SPM's end-effector tracking, while avoiding singularity. Finally, the effectiveness of the proposed VEC-FxTCC approach is validated through the simulations and the rust removal sandblasting robot prototype experiments.

This paper is dealing with the problem of adaptive event-triggered leader-follower consensus for multi-agents systems with output constraints and dead-zone inputs. By introducing an advanced nonlinear mapping technique to obtain the unconstrained auxiliary variables of constrained system states, a new systems model without output constraints is constructed. Unlike existing schemes, the proposed strategy can be used in both constrained and unconstrained situations without requiring changes to the control structure. Moreover, a state estimator is constructed to observe the unavailable states. To conserve communication resources, an event-triggered rule with a dynamic threshold is designed to decrease superfluous information transmissions from the controller to the actuator. It is proven that all signals in closed-loop systems are ultimately bounded, and the system output does not violate the given constraint range. At last, a numerical simulation example is provided to confirm the correctness and efficiency of the proposed method.

This article investigates a satellite sun-safe controller based on a super-twisting disturbance observer (STDO) with interval analysis. First, a variable gain sliding mode control (SMC) algorithm is proposed to ensure that the satellite can achieve a fixed-axis rotation and sun-pointing attitude. The controller gains are adjusted according to the disturbance estimation value and the interval of the disturbance estimation error. The important feature of the adaptation algorithm is in non overestimating the values of the control gains. To achieve the purpose of non-overestimating, a STDO is constructed to estimate the unknown disturbance. Additionally, the interval of the disturbance estimation error is obtained by interval analysis to update the controller gain in real time. Then, the stability and convergence of the closed-loop system, including the variable gain sliding mode controller and the super-twisting observer, are verified by using the Lyapunov theory. Finally, hardware-in-the-loop (HIL) experimental results demonstrate that the proposed method not only performs better in terms of convergence and accuracy than the state-of-the-art sun-safe controller design method but also achieves more negligible chattering in the presence of disturbance torque compared to the fixed gain SMC method.

This paper proposes an enhanced safety-critical control scheme for hypersonic vehicles (HSVs) with multiple constraints, where both safety constraints (e.g., actuator saturations and time-varying angle-of-attack [AOA] limitation) and transient performance constraints are considered. In this scheme, the extended exponential control barrier function (EECBF) is constructed by incorporating extended states and robust terms to deal with time-varying constraint boundaries and uncertainties simultaneously. An adaptive programming for optimal transient performance envelopes is conducted to make a trade-off between safety and transient performance constraints. It is shown that the proposed scheme for HSVs can confine AOA to time-varying safety boundaries in the presence of uncertainties while the velocity and height tracking errors can always maintain within the desired transient performance envelopes. Simulations and comparisons are provided to verify the effectiveness of our scheme.

This paper focuses on the $��H_{\infty }�$ synchronization issue for delayed semi-Markovian switching complex-valued networks via the delay-dependent event-triggered mechanism. For the first time, in order to reduce the redundant information transmission and the number of false triggers, a novel event-triggered mechanism is proposed, which involves the network-induced time delay and the latest triggered signal. Second, based on the proposed delay-dependent event-triggered control scheme, the desired results can be realized. Specifically, by utilizing the stochastic analysis technique and Lyapunov stability theory as well as mixed reciprocally convex inequalities, some sufficient less conservative criteria are achieved to ensure the synchronization error system realize the globally asymptotically mean-square stability with a pre-established $��H_{\infty }�$ disturbance performance. Furthermore, the expected controller gain matrices can be explicitly designed by solving some solvable matrix inequalities. At the end of paper, an illustrative example with simulations is presented to demonstrate the feasibility and effectiveness of the proposed delay-dependent event-triggered scheme.

This paper presents a nonsingular fast terminal sliding mode control for the PAR 4 parallel robot, focusing on workspace optimization and trajectory planning. First, an analytical inverse kinematic model is derived to calculate the workspace, which is then extended using parameter optimization techniques. Next, a trajectory planning method based on the S-curve approach is proposed to generate the desired path, with special attention to reducing the cycle time of pick-and-place operations using sequential quadratic programming method. Finally, a nonsingular fast terminal sliding mode control strategy is suggested to enable the robot to accurately track the generated trajectory. The stability of the closed-loop system is analyzed using Lyapunov theory, and the effectiveness of the controller is validated through simulation results.