Asymmetric Output Constraints Research Articles

Robust finite-time output feedback stabilisation for a class of uncertain planar systems with asymmetric output constraints

This paper considers the finite-time output feedback stabilisation (FTOFS) problem for a class of uncertain planar systems with asymmetric output constraints. The presence of unknown control coefficients, unknown measurement sensitivity and asymmetric output constraints makes the system under consideration essentially different from those in the existing related works. By constructing a new barrier Lyapunov function and applying homogeneous system theory, a simple proportional-derivative like finite-time output feedback controller is explicitly constructed, which only utilises the output information. A rigorous proof demonstrates that not only the closed-loop system is finite time stable, but also the requirement of asymmetric output constraint can be achieved. The novelty of the control approach lies in that it is capable to handle the FTOFS problem for uncertain planar systems with or without asymmetric output constraints in a unified manner, without changing the control structure. The efficiency of the proposed theoretical results are confirmed by simulation results.

Predefined-time adaptive fuzzy control for nonlinear output constraint systems with unknown backlash-like hysteresis via command filtering

In this article, the predefined-time adaptive fuzzy control problem for strict-feedback nonlinear systems with asymmetric time-varying output constraint and unknown backlash-like input hysteresis is considered. An innovative predefined-time adaptive control method, in which utilises unified barrier function (UBF) to deal with the output constraint problem and adopts a differential equation to represent the unknown backlash-like hysteresis, is presented by combining a novel command filter with backstepping technology. Fuzzy logic systems (FLSs) are employed to estimate the unknown nonlinearities. Moreover, by designing appropriate parameters, the constructed control strategy ensures that all signals are predefined-time bound and the tracking error stays in a small neighbourhood adjacent zero. Ultimately, two simulation examples are given to prove the effectiveness of the presented control algorithm.

Adaptive SOSM Control for Nonlinear Systems With Parametric Uncertainties and Time-Varying Asymmetric Output Constraints

Adaptive SOSM Control for Nonlinear Systems With Parametric Uncertainties and Time-Varying Asymmetric Output Constraints

Vibration control of 2-D variable-length flexible riser systems with unknown boundary disturbance

The riser system is subject to vibration due to marine environmental loads, which can affect the efficiency of the system or even destroy it. This paper proposes a solution for the vibration control problem of a 2-D variable-length flexible riser based on PDE model. Firstly, a disturbance observer is developed to estimate and offset the unknown disturbance in the feedback loop. Based on the above method, an effective boundary controller is designed to realize the elastic suppression goal of the 2-D variable-length flexible riser. Secondly, when considering the asymmetric output constraints, a time adjustment function is introduced to develop a new controller based on the barrier Lyapunov function, which realizes the control objective of suppressing the boundary vibration of the flexible riser within specified constraints in a finite time. Finally, the effectiveness of the controller is verified by simulation examples.

Adaptive Event-Triggered Prescribed-Time Stabilization of Uncertain Nonlinear Systems With Asymmetric Time-Varying Output Constraint

Adaptive Event-Triggered Prescribed-Time Stabilization of Uncertain Nonlinear Systems With Asymmetric Time-Varying Output Constraint

Event-triggered adaptive tracking control of a class of nonlinear systems with asymmetric time-varying output constraints

Event-triggered adaptive tracking control of a class of nonlinear systems with asymmetric time-varying output constraints

Adaptive fixed‐time fault‐tolerant fuzzy control of AUVs with asymmetric output constraints

AbstractThe fast and safe formation tracking problem for multiple autonomous underwater vehicle (AUV) systems (MAUVS) with asymmetric output constraints and actuator faults is studied in this article. Actuator faults are composed of loss of effectiveness and time‐varying unknown bias faults, an adaptive fixed‐time fault‐tolerant controller (AFFTC) is designed by employing fixed‐time stable theory and fuzzy logic systems. Under the designed control algorithm, the MAUVS can be practically fixed‐time stable, the tracking errors among the follower AUVs and the virtual leader AUV can converge to a small area near the origin within the fixed time, and the settling time is unaffected by the initial state of the system. To enhance the safety of MAUVS, a novel asymmetric barrier function is utilized to constrain the trajectory tracking errors within the prescribed range. Finally, the simulation results demonstrate the effectiveness of the proposed control algorithm.

Adaptive fixed-time neural consensus control for a class of uncertain nonlinear multi-agent systems with full state constraints

This paper is concerned with the fixed-time consensus control problem for non-strict feedback multi-agent systems with asymmetric output constraints and full state constraints. Considering the feasibility of controlling execution, a novel practical virtual control signal is developed utilizing both saturation function and hyperbolic tangent function to ensure that this signal can remain within the same restricted range as the corresponding state variable throughout entire operation process. In backstepping steps, the design of ideal virtual control signal also adopts a different form of piecewise function than before, introducing high-order polynomial functions to avoid singularity problems in the derivation process. In addition, function approximation ability of radial basis function neural networks technique is applied to estimate uncertainties derived from the system functions and controller design procedure. Moreover, universal barrier Lyapunov function approach is improved for constructing an adaptive constrained synchronization control scheme. By fixed-time stability theory, it is shown that the tracking errors of the MAS converge to an adjustable region around the origin in a fixed time and the state variables always obey their constraints. And the upper bound of the settling time is merely dependent on design parameters, which is not affected by the initial states of MAS. The effectiveness of the proposed control strategy is shown by a numerical simulation example at last. Two scenarios are provided to demonstrate the advantages of the control protocol proposed in this paper.

Adaptive NNs asymptotic tracking control for high‐order nonlinear systems under prescribed performance and asymmetric output constraints

SummaryThis article studies the adaptive neural networks (NNs) asymptotic tracking control of high‐order nonlinear systems subject to prescribed performance, non‐strict‐feedback structure, and output constraints. To address the output constraint issue while guaranteeing that the tracking error stays within the specified area, a variable fused with the time‐varying constraint functions is introduced. Then, a pivotal form of coordinate transformation is developed, which plays a key role in achieving asymptotic tracking performance. Based on the backstepping and Lyapunov method, the designed control scheme assures that all system variables are semi‐globally uniformly ultimately bounded, the output constraints are never broken, and the tracking error always stays within the predefined function and asymptotically converges to zero. Finally, the effectiveness of theoretical findings is verified via simulation studies.

Adaptive output feedback stabilisation control for cascaded systems with output constraints and disturbance

The system under consideration is a cascaded system composed of integral input-to-state stable inverse dynamics and a non-holonomic system. An adaptive output feedback stabilisation control is proposed for the system with disturbance and output constraints. The dynamic uncertainty is eliminated using the technique that changes the supply rate. An extended state observer is proposed by defining the non-vanishing disturbance as a new state variable of the system. The asymmetric time-varying output constraint is solved by utilising the tan-type barrier Lyapunov function. The result shows that the adaptive output feedback controller guarantees the stability of the closed-loop system without violating the asymmetric time-varying output constraints under the backstepping technique. Simulation results are given to verify the effectiveness of the control method.

Dynamic Self-Triggered Fuzzy Bipartite Time-Varying Formation Tracking for Nonlinear Multiagent Systems With Deferred Asymmetric Output Constraints

Dynamic Self-Triggered Fuzzy Bipartite Time-Varying Formation Tracking for Nonlinear Multiagent Systems With Deferred Asymmetric Output Constraints

Predefined-time stabilization of stochastic nonlinear systems with application to UAVs

The paper presents a new Lyapunov-type predefined-time stabilization control algorithm for stochastic high-order nonlinear systems with asymmetric output constraints. In contrast to stochastic finite-time and fixed-time stabilization, the average value of the settling-time function for stochastic predefined-time stabilization control is independent of both the initial value and the control factors. To mitigate the significant uncertainties arising from the asymmetric output constraint, a tan-type barrier Lyapunov function is formulated. Furthermore, by harnessing the previously mentioned barrier Lyapunov function and integrating the power integrator technique, a controller design strategy is formulated based on the backstepping method. The rigorous analysis in this study proves that the designed controller ensures both the attainment of predefined-time convergence of the system states to the origin in probability and the satisfaction of the output constraint. Finally, an example of a roll angle subsystem for quadrotor UAVs and a numerical illustration are presented to corroborate the theoretical analysis.

Non-smooth finite-time adaptive stabilisation of cascade switched systems with asymmetric output constraints

In this article, the problem of non-smooth finite-time (FT) adaptive state feedback stabilisation is investigated for asymmetric output-constrained cascade switched nonlinear systems (AOCCSNSs) with mixed powers, parametric uncertainties and zero dynamics. To better address the uncertain parameters and the asymmetric output constraints, a new type of common Lyapunov function (CLF) including a quadratic squared term of the estimated error and a tangent-type barrier Lyapunov function ( T t -BLF) is constructed. Then, with some mild assumptions, such as input-to-state stability (ISS) property of zero dynamics, upper boundedness of subsystems' nonlinear terms and some well-known small signal conditions, state feedback controllers (SFCs) constructed by adding a power integrator (AAPI) technique and the update law to estimate the unknown parameter are proposed to guarantee resultant closed-loop switched systems FT stable. The proposed method for switched systems is presented in a unified manner, capable of addressing FT stabilisation by effectively handling situations with or without output constraints. This is achieved through the construction of T t -BLF, which degenerates into a quadratic form when the output constraint disappears or approaches infinity. At last, the method is verified by a switched RLC circuit system (RLC-CS) and a numerical simulation.

Event-triggered adaptive NN tracking control for nonlinear systems with asymmetric time-varying output constraints and application to an AUVs

Event-triggered adaptive NN tracking control for nonlinear systems with asymmetric time-varying output constraints and application to an AUVs

Event-triggered control for [formula omitted]-normal switched stochastic nonlinear systems with asymmetric output constraints

This article focuses on the event-triggered control design for a class of p-normal switched stochastic nonlinear systems(SNS) with asymmetric output constraints. Firstly, in order to handle the pre-specified output constraints, a modified asymmetric tan-type common barrier Lyapunov function(CBLF) is put forward through the idea of piece-wise function. Combining the proposed CBLF with adding a power integrator technique, an event-triggered state-feedback controller is designed to ensure the switched SNS states asymptotically converge to zero in probability. Simultaneously, it is proved that the output will be constrained in the pre-specified bound and Zeno-behavior will not happen. Finally, a simulation of two-tank liquid-level system is given to indicate the effectiveness of the proposed method.

Cooperative grid frequency control under asymmetric V2G capacity via switched integral reinforcement learning

In recent years, V2G techniques have been successfully implemented to stabilize frequency deviations in the grid caused by intermittent renewable energy sources. However, the battery capacity constraints and real-time dynamic driving demands of electric vehicles (EVs) in V2G systems hinder the coordination between V2G control and power plant frequency control strategies. It leads to the dynamic asymmetry of regulation up (RU) and regulation down (RD) frequency regulation (FR) capacity of V2G system, which can affect the performance of V2G FR. To cope with this problem, this paper proposes a switched integral reinforcement learning (SIRL) scheme for cooperative grid frequency control. The proposed scheme integrates V2G control with the power plant frequency control, which are cooperated with each other to complete FR tasks. A novel switched neural network (NN) structure is constructed for the training process of the SIRL algorithm to solve the problem of dynamic asymmetric FR capacity. A switched V2G utility function and a global cost function are constructed for RU and RD. Two independent subnetworks with the same structure are adopted for RU and RD learning to optimized V2G control parameters respectively under dynamic asymmetric output constraints. Two case studies of the IEEE 14-bus test system demonstrate the effectiveness and advantages of the proposed scheme.

Backstepping Technology-Based Adaptive Boundary ILC for an Input-Output-Constrained Flexible Beam.

This article focuses on vibration suppression of an Euler-Bernoulli beam which is subject to external disturbance. By integrating backstepping technique, an adaptive boundary iterative learning control (ABILC) is put forward to suppressing vibration. The adaptive law is proposed for handing the parameter uncertainty and the iterative learning term is designed to deal with periodic disturbance. An auxiliary system is utilized to compensate the effect of input nonlinearity. In addition, a barrier Lyapunov function is adopted to deal with asymmetric output constraint. With the proposed control strategy, the stability of the closed-loop system is proven based on rigorous Lyapunov analysis. In the end, the effectiveness of the proposed control is illustrated through numerical simulation results.

Adaptive neural network control of multiple‐sectioned flexible riser with time‐varying output constraint and input nonlinearity

AbstractIn this paper, an adaptive neural network controller is proposed for vibration suppression of a multisectional riser system with unknown boundary disturbance, time‐varying asymmetric output constraint, and input nonlinearity. The considered riser system is composed of a continuous connection of several different pipes, and its dynamic models are represented by a set of multiple continuously connected partial differential equations (PDEs) and an ordinary differential equation (ODE) at the top boundary. Considering input nonlinearity, external disturbance, and system uncertainty, radial basis function (RBF) neural networks are adopted to eliminate the effect of these uncertain terms. Besides, a barrier Lyapunov function is employed to guarantee the restrictions. With the proposed boundary control, the stability of the closed‐loop system is proved and simulations are given to illustrate the well performance of the proposed control strategy.

Design of Adaptive Fuzzy Fixed-Time HOSM Controller Subject to Asymmetric Output Constraints

This paper is concerned with the control design of adaptive fuzzy fixed-time high-order sliding mode (HOSM) under asymmetric output constraints. The main objective of the paper is to construct a control scheme to build the HOSM in a fixed time and fulfill the pre-set constraint condition. For this purpose, initially to conquer this obstacle regarding the output constraint, a barrier Lyapunov function is developed to keep the output variable within the predefined constraint during operation. Then, the unknown functional bounds of uncertainties in the considered system are modeled by invoking fuzzy logic systems. With the integrated use of adaptive fuzzy control and backstepping-like techniques, a novel protocol for the fixed-time HOSM control with asymmetric output constraints is developed. Through the strictly theoretical clarification, the HOSM is fixed-time established under the suggested control strategy. The effectiveness of the derived results is eventually testified by some comparative simulation results.

Adaptive stabilisation of output-constrained high-order nonlinear systems with high-order and low-order nonlinearities

This paper investigates the adaptive stabilisation of output-constrained high-order nonlinear systems with more general high-order and low-order nonlinearities. By skilfully introducing nonlinear mappings, a key coordinate transformation, integral Lyapunov functions and the sign function into the adding a power integrator technique, and combining a novel analysis method, a continuous adaptive state-feedback controller is constructed. When the initial value of system states lies in the constrained set, it is rigorously proved that all the closed-loop signals are uniformly bounded, the asymmetric output constraint isn't transgressed, and the equilibrium point of the closed-loop system is uniformly asymptotically stable. A simulation example shows the effectiveness of this control scheme.