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This article proposes an output-feedback fixed-time trajectory tracking control methodology for hypersonic flight vehicles subject to asymmetric output constraints. In contrast to the state of the art, the most distinguishing feature of our control design lies in avoiding using conventional recursive design methods (e.g., backstepping technique, dynamic surface control, etc.) and in not relying on full-state availability. In the velocity control loop, an asymmetric integral barrier Lyapunov function is adopted to confine velocity variable within a well-defined compact set all the time. In the altitude control loop, after utilizing its cascaded property and proposing a novel scaling function, the original constrained system is transformed to an unconstrained one, which facilitates the control design and stability analysis. Moreover, the proposed control algorithm only involves one fuzzy logic approximator as well as one fixed-time differentiator in the transformed system and guarantees that the tracking errors of velocity and altitude converge into the user-defined residual sets within fixed time. Several comparative simulations have been conducted to highlight the superiorities of the developed method. [ABSTRACT FROM AUTHOR]

This article proposes a fuzzy adaptive fault-tolerant control strategy solving the fast fixed-time constrained tracking problem for hypersonic flight vehicles. To handle the actuator faults, a two-step design method is first proposed that only needs to estimate the upper and lower bounds of actuator parameters, under which the adverse influences of actuator faults (e.g., lock-in-place, loss of effectiveness, etc.) have been compensated via an adaptive fashion instead of conventional robust ways. In comparison with the state-of-the-art, a new fixed-time corollary that has proved a smaller upper bound of convergence time under the same condition of conventional fixed-time stability is presented. To avoid singularity issues often encountered in fixed-time designs, a piecewise but differentiable switching control laws whose continuity and differentiability are guaranteed everywhere through an appropriate design is introduced. Such a design not only preserves the continuity and differentiability of virtual and actual control laws, but also ensures the continuity of their time derivatives. Fuzzy logic systems are exploited to tackle continuous unknown dynamics and asymmetric time-varying barrier functions are utilized to confine flight states within some predefined compact sets all the time provided their initial conditions remain therein. This property is of great significance in dealing with the challenge that the operating regions of the flight state variables are asymmetric and time-varying in practice, especially when executing various flight missions. Comparative simulations have been performed to validate the effectiveness of the proposed control scheme in terms of fixed-time convergence, smoothness, and time-varying constraints satisfaction. [ABSTRACT FROM AUTHOR]

Responsive and highly controlled autonomous vehicles (AVs) on the road easily form platoons with small inter-vehicle gaps to increase traffic throughput and reduce energy consumption. Unlike human drivers, AVs typically employ discrete quantization signals and only generate finite discrete acceleration. Finite discrete acceleration easily causes unstable inter-vehicle gaps and inter-vehicle collisions, especially when there are inaccurate quantization parameters due to quantizer aging. Based on the backstepping technique, this paper proposes the cooperative constrained control algorithm under unknown quantization parameters for AVs with nonuniform input quantization and motion uncertainties. The control laws of each AV in the platoon only depend on the state information of its consecutive AVs. The position trajectories of consecutive AVs are constructed as inter-vehicle collision-free constraints to avoid emergency braking and inter-vehicle collisions. In addition, the consistent characteristic of two types of nonuniform quantizers (i.e., logarithmic quantizers and hysteresis quantizers) is proposed, and unknown disturbances in vehicle motion are compensated. The Lyapunov based local stability and string stability are proved. Numerical simulation shows that the control algorithm is applicable to AVs with either logarithmic quantizers or hysteresis quantizers. Compared with the previous control algorithms without considering input quantization and inter-vehicle collision avoidance, the control algorithm proposed reduces inter-vehicle spacing errors, avoids high acceleration, and avoids inter-vehicle collisions. [ABSTRACT FROM AUTHOR]

This article aims to realize event-triggered constrained consensus tracking for high-order nonlinear multiagent networks subject to full-state constraints. The main challenge of achieving such goals lies in the fact that the standard designs [e.g., backstepping, event-triggered control, and barrier Lyapunov functions (BLFs)] successfully developed for low-order dynamics fail to work for high-order dynamics. To tackle these issues, a novel high-order event-triggered mechanism is devised to update the actual control input, lowering the communication and computation burden. More precisely, compared with the conventional event-triggered mechanism, not only the amplitudes of control signals and a fixed threshold are considered but a monotonically decreasing function is introduced to allow a relatively big threshold, while guaranteeing consensus tracking error to be small. Then, a high-order tan-type BLF working for both constrained and unconstrained scenarios is incorporated into the distributed adding-one-power-integrator design for the purpose of confining full states within some compact sets all the time. A finite-time convergent differentiator (FTCD) is introduced to circumvent the “explosion of complexity.” The consensus tracking error is shown to eventually converge to a residual set whose size can be adjusted as small as desired through choosing appropriate design parameters. Comparative simulations have been conducted to highlight the superiorities of the developed scheme. [ABSTRACT FROM AUTHOR]

In contrast with most existing results concerning unmanned aerial vehicles (UAVs) wherein material points or only attitude/longitudinal dynamics are considered, this article proposes a distributed fixed-time fault-tolerant control methodology for networked fixed-wing UAVs whose dynamics are six-degree-of-freedom with twelf-state-variables subject to actuator faults and full-state constraints. More precisely, state transformations with the scaling function are devised to keep the involved velocity and attitude within their corresponding constraints. The fixed-time property is obtained in the sense of guaranteeing that the settling time is lower bounded by a positive constant, which is independent of initial states. The actuator faults as well as the network induced errors are handled via the bound estimation approach and well-defined smooth functions. By strict Lyapunov arguments, all closed-loop signals are proved to be semiglobally uniformly ultimately bounded, and the tracking errors of velocity and attitude converge to the residual sets around origin within a fixed time. [ABSTRACT FROM AUTHOR]

This work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed unknown control directions (some being known and some being unknown) requires a piecewise Nussbaum function that exploits the a priori knowledge of the known control directions. The piecewise Nussbaum function technique leaves some open problems, such as Can the technique handle multiagent dynamics beyond the standard backstepping procedure? and Can the technique handle more than one control direction for each agent? In this work, we propose a hybrid Nussbaum technique that can handle uncertain agents with high-power dynamics where the backstepping procedure fails, with nonsmooth behaviors (switching and quantization), and with multiple unknown control directions for each agent. [ABSTRACT FROM AUTHOR]

This article proposes a fuzzy adaptive design solving the finite-time constrained tracking for hypersonic flight vehicles (HFVs). Actuator dynamics and asymmetric time-varying constraints are considered when solving this problem. The main features of the proposed design lie in 1) introducing a novel piecewise but differentiable switching control law, with an appropriate design thought to avoid the singularity issues typical of finite-time control; 2) handling actuator magnitude, bandwidth, and rate constraints, thanks to the introduction of an auxiliary compensating system counteracting the adverse effects caused by actuator physical constraints, while guaranteeing the closed-loop stability; and 3) handling asymmetric time-varying state constraints, thanks to the introduction of tan-type barrier Lyapunov functions working for both constrained and unconstrained scenarios. Comparative simulation results illustrate the effectiveness of the proposed strategy over existing methods for HFVs in terms of convergence, smoothness, actuator performance, and constraints satisfaction. [ABSTRACT FROM AUTHOR]

Compared with most existing results concerning unmanned aerial vehicles (UAVs) wherein two-degree or only attitude/longitudinal dynamics are considered, this paper proposes an event-based fault-tolerant coordinated control (FTC) for multiple fixed-wing UAVs such that the consensus tracking of velocity and attitude is achieved in the presence of actuator faults, external disturbances and modeling uncertainties. More precisely, as opposed to static event-triggered communication mechanisms, a dynamic event-triggered communication mechanism (DECM) is devised to schedule the connected communications while avoiding the unnecessary information exchanges among UAVs, which reduces the communication burden and saves on the network resources. Meanwhile, the Zeno phenomenon is excluded in terms of guaranteeing that the period between two consecutive triggering communication is lower bounded by a positive constant. Moreover, the actuator fault, external disturbance as well as model uncertainty are treated as the lumped disturbances and estimated via the disturbance observer technique. By strict Lyapunov arguments, all closed-loop signals are proved to be uniformly ultimately bounded (UUB) and the tracking errors of velocity and attitude converge to a residual set around origin. Finally, simulation results are presented to illustrate the validity and superiority of proposed event-based control scheme. [ABSTRACT FROM AUTHOR]

In contrast with most existing results concerning unmanned aerial vehicles (UAVs) wherein two-degree or only attitude/longitudinal dynamics are considered, this article proposes an event-triggered cooperative synchronization fault-tolerant control (FTC) methodology for multiple fixed-wing UAVs whose dynamics are six-degree-of-freedom (DOF) with twelf-state-variables subject to actuator faults, modeling uncertainties, and external disturbances. More precisely, an event-triggering mechanism is devised to determine the time instants of updating control signals, which reduces the signal transmission burden, while saving on system resources. The Zeno phenomenon is excluded in the sense of guaranteeing that the time between two consecutive switchings is lower bounded by a positive constant. The actuator faults as well as the network induced errors are handled via the bound estimation approach and some well-defined smooth functions. By strict Lyapunov arguments, all closed-loop signals are proved to be semi-globally uniformly ultimately bounded (SGUUB) and the synchronization tracking errors of speed and attitude converge to a residual set around origin whose size can be made arbitrarily small through selecting appropriate design parameters. [ABSTRACT FROM AUTHOR]

This article addresses and solves the adaptive asymptotic tracking for a class of uncertain switched positive linear dynamics (also known in the literature as compartmental models) subject to dwell-time constraints. Compared to the state-of-the-art, the innovative feature of this method is to attain for the first time asymptotic set-point tracking, while guaranteeing non-negativity of the systems states. To achieve asymptotic tracking, an interpolated Lyapunov function is adopted, which is nonincreasing at the switching instants and decreasing in two consecutive switching instants. Such Lyapunov function results in a novel adaptive law with time-varying adaptive gains, as opposed to state-of-the-art laws with fixed positive adaptive gains. The developed design is applicable to classes of compartmental systems compatible with those proposed in the literature: an example involving the infusion of anesthesia is conducted to show that the proposed method can achieve better performance than existing methods. [ABSTRACT FROM AUTHOR]

This paper proposes a novel set-invariance adaptive dynamic surface control (DSC) design for a larger class of uncertain large-scale nonlinear input-saturated systems. The peculiarity of this class is that no a priori bound on the continuous control gain functions is assumed (i.e., their boundedness cannot be assumed before obtaining system stability). This requires a new design. Differently from the available methods, the proposed design involves the construction of appropriate invariant sets for the closed-loop trajectories, which allows to remove the restrictive assumption of a priori bounds of the control gain functions. Furthermore, we show that such set-invariance design can handle input constraints in the form of input saturation. In line with the DSC methodology, semi-globally uniformly ultimate boundedness is proven: however, differently from the standard methodology, stability analysis requires the combination of Lyapunov and invariant set theories. [ABSTRACT FROM AUTHOR]

This paper proposes a novel adaptive fuzzy dynamic surface control (DSC) method for an extended class of periodically disturbed strict-feedback nonlinear systems. The peculiarity of this extended class is that the control gain functions are not bounded a priori but simply taken to be continuous and with a known sign. In contrast with existing strategies, controllability must be guaranteed by constructing appropriate compact sets ensuring that all trajectories in the closed-loop system never leave these sets. We manage to do this by means of invariant set theory in combination with the Lyapunov theory. In other words, boundedness is achieved a posteriori as a result of stability analysis. The approximator composed of fuzzy logic systems and Fourier series expansion is constructed to deal with the unknown periodic disturbance terms. [ABSTRACT FROM AUTHOR]

This work removes the critical assumptions of continuity, differentiability, and state-independent boundedness, which are typical of compounded disturbances in disturbance observer-based adaptive designs. Crucial in removing such assumptions are a novel observer-based design with state-dependent gain in place of a constant one, and a novel set-invariance design. The designs use different a priori knowledge of the disturbance, but they can both handle state-dependent (e.g., possibly unbounded) disturbances, as well as non-smooth (e.g., non-differentiable and jump discontinuous) disturbances. The tracking error is proven to be as small as desired by appropriately choosing design parameters. For the second design, which uses the least a priori knowledge of the disturbance, stability is proven by enhancing Lyapunov theory with an invariant-set mechanism, so as to construct an appropriate compact set resulting an invariant set for the closed-loop trajectories. [ABSTRACT FROM AUTHOR]