Adaptive Prescribed Performance Control Research Articles

Improved finite-time prescribed performance based adaptive neural control for nonlinear systems with sensor faults

In this article, based on a novel finite-time prescribed performance function, we consider the issue of the adaptive neural fault-tolerant tracking control problem for a type of nonlinear system with sensor faults. The control performance of the system may be affected when sensor faults occur. For the controlled system with sensor faults, an improved finite-time performance function is proposed so that its initial conditions do not need to be set in advance. Compared with existing performance functions, the performance functions in this paper can ensure that the system is always controllable, even if the sensor faults occur suddenly during the steady operation. Moreover, Radial basis function (RBF) neural networks (NNs) are employed to estimate the uncertain smooth nonlinear functions. With the help of the adaptive backstepping control technique, an improved adaptive prescribed performance control technique is developed, which can realize the boundedness of every signal in the closed-loop system, and the tracking error can be limited within the neighborhood near the origin. Simulation results demonstrate the effectiveness of the proposed control scheme.

PDE-based prescribed performance adaptive attitude and vibration control of flexible spacecraft

This article presents a prescribed performance adaptive control scheme for the attitude tracking and vibration reduction of flexible spacecraft modeled by partial differential equations (PDEs). First, the original constrained problem is converted to an equivalent unconstrained one by adopting a prescribed error transformation. Then, a boundary control torque law and a boundary control force law are developed to track the desired attitude and reduce the vibration, respectively. Moreover, the parametric adaptation technique is integrated with the boundary control laws to estimate the disturbances. The closed-loop system is evaluated to be asymptotically stable through the Lyapunov stability theorem and LaSalle's invariance principle. The developed controller has two distinctive features as follows. One is the controller can guarantee the attitude tracking error and tip deformation always satisfy the prescribed performance constraints. Another is the controller can acquire the strong robustness owing to the feedforward disturbance compensation. Lastly, the derived results are demonstrated by simulated studies.

Adaptive Prescribed Performance Control of Unmanned Aerial Manipulator With Disturbances

This article presents the problem of autonomous control of an unmanned aerial manipulator (UAM) developed for operation with unknown disturbances, wherein the disturbances from the coupling effect between the UAM and the external environment need to be considered. Regarding the coupling force as a disturbance to the entire UAM system, an adaptive prescribed performance control (APPC) scheme utilizing the knowledge of prescribed performance is proposed to guarantee the transient and steady-state performance responses. Also, an adaptive law is designed to estimate the upper boundary parameters of the UAM system uncertainties and disturbances, wherein the restrictive constant boundary assumptions and the prior information of the upper bound are not required in the controller design. Furthermore, to enable safe manipulation in a realistic situation, an end-effector trajectory generation method is presented satisfying the joint angle limitation. For the validation of the proposed method, the simulation results of numerical simulation comparisons are shown. Moreover, experimental scenarios including stable flight and simulated co-work with humans in complex environments are designed to verify the proposed method. <i>Note to Practitioners</i>&#x2014;This article is motivated by the problem of aerial manipulation under unknown disturbances, which may be caused by the wide movement of the manipulator and the sudden loading or unloading of an object. Existing approaches for aerial manipulation often require the assumption of a constant or slowly varying external disturbance. However, a priori bounded disturbance might impose a priori bound on the system state before obtaining closed-loop stability. In this article, the proposed controller with an adaptive law is designed to estimate the upper boundary parameters of the overall disturbances and ensure the predefined performance, so that the prior information of the upper bound of disturbances is not required. The performance of the proposed control strategy is demonstrated via numerical simulation comparisons and experiments, including stale flight and simulated co-work with humans in a complex environment.

Robust Trajectory Tracking Control for Constrained Small Fixed-Wing Aerial Vehicles with Adaptive Prescribed Performance

A novel approximation-free adaptive prescribed performance control scheme for the longitudinal motion tracking of input and state constrained small fixed-wing UAVs is designed in this work. The proposed controller employs the adaptive prescribed performance technique to impose output performance specifications in accordance with actuation limitations regarding the amplitude and the rate of the control signal. Furthermore, state constraints are introduced to ensure the proper operation of the closed-loop system. The adoption of PPC methodology results in a low complexity control algorithm with easy gain selection which facilitates its practical implementation. Finally, a comprehensive simulation study as well as comparative simulation paradigms on an Aerosonde model clarifies and verifies the superiority and the effectiveness of the proposed controller to control the longitudinal motion of UAVs in the presence of wind gusts.

A neural adaptive prescribed performance controller for the chaotic PMSM stochastic system

A neural adaptive prescribed performance controller for the chaotic PMSM stochastic system

Sampled‐data‐based event‐triggered adaptive prescribed performance control of uncertain strict‐feedback nonlinear systems

AbstractThis article studies the problem of global adaptive prescribed performance control (PPC) for a class of uncertain strict‐feedback nonlinear systems based on the sampled‐data‐based event‐triggering mechanism. A novel time‐varying scaling function, whose reciprocal plays the role of a prescribed performance function, is constructed and utilized to remove the range restriction on the initial tracking error and achieve the global PPC. Meanwhile, to reduce the communication frequency and avoid the Zeno behavior in mechanism, a sampled‐data‐based event‐triggering mechanism is introduced, and an event‐triggered global adaptive prescribed performance controller is designed by employing the error transformation technique and the adaptive backstepping method. It is proved that all signals of the closed‐loop system are bounded and the tracking error is confined within the prescribed performance boundary for arbitrary initial values. Since there is no need to continuously monitor whether the triggering condition is satisfied, the obtained result is conducive to physical implementation. Finally, a network‐based robotic manipulator system is employed to verify the effectiveness of the proposed method.

Time-varying formation prescribed performance control with collision avoidance for multi-agent systems subject to mismatched disturbances

The time-varying formation problem is addressed for second-order multi-agent systems with matched and mismatched disturbances. A time-varying formation prescribed performance control method is presented with improved collision avoidance and connectivity maintenance scheme. Specifically, more accurate judgment mechanisms of collision risks and connectivity interruption risks are proposed to reduce conservatism of the existing results, by making use of the velocity information and analyzing the maneuvering process of agents. Then, a nonlinear disturbance observer is adopted to estimate those disturbances, and an adaptive prescribed performance controller based on a novel performance function is developed to obtain the predesigned transient performance and steady-state performance. Finally, theoretical analysis, numerical simulation, and actual experiments are given to verify the proposed method.

Adaptive non‐singular fast terminal sliding mode based on prescribed performance for robot manipulators

AbstractA fast convergent non‐singular terminal sliding mode adaptive control law based on prescribed performance is formulated to solve the uncertainties and external disturbances of robot manipulators. First, the tracking error of robot manipulators is transformed by using the prescribed performance function, which improves the transient behaviors and steady‐state accuracy of robot manipulators. Then, a novel fast convergent non‐singular terminal sliding mode surface is brought up according to the transformed error, and the control law is derived to meet the stability requirements of robot manipulators. In practice, the upper boundary of the lumped disturbances cannot be accurately obtained. Therefore, an adaptive prescribed performance control (PPC) controller to lumped disturbances is brought up to ensure the stability and finite‐time convergence of robot manipulators. Finally, the system stability of robot manipulators is proved by the Lyapunov theorem. Simulation results and comparative analysis demonstrate the superiority and robustness of the raised strategy.

Finite-Time Fuzzy Adaptive PPC for Nonstrict-Feedback Nonlinear MIMO Systems.

This article addresses the issue of the fuzzy adaptive prescribed performance control (PPC) design for nonstrict feedback multiple input multiple output (MIMO) nonlinear systems in finite time. Unknown nonlinear functions are handled via fuzzy-logic systems (FLSs). By combining the adaptive backstepping control algorithm and the nonlinear filters, a novel dynamic surface control (DSC) method is proposed, which can not only avoid the computational complexity issue but also improve the control performance in contrast to the traditional DSC control methods. Furthermore, to make the tracking errors have the prescribed performance in finite time, a new Lyapunov function is constructed by considering the transform error constraint. Based on the designed Lyapunov functions, it is proved that all the signals of the controlled systems are semiglobal practical finite-time stability (SGPFS). Finally, a simulation example is provided to illustrate the feasibility and validity of the put forward control scheme.

Research on Adaptive Prescribed Performance Control Method Based on Online Aerodynamics Identification

Wide-speed-range vehicles are characterized by high flight altitude and high speed, with significant changes in the flight environment. Due to the strong uncertainty of its aerodynamic characteristics, higher requirements are imposed on attitude control. In this paper, an adaptive prescribed performance control method based on online aerodynamic identification is proposed, which consists of two parts: an online aerodynamic parameter identification method and an adaptive attitude control method based on the pre-defined parameters of the control system. The aerodynamic parameter identification is divided into offline design and online design. In the offline design, neural networks are used to fit nonlinear aerodynamic characteristics. In the online design, a nonlinear recursive identification method is used to correct the errors of the offline fitted model. The adaptive attitude control is based on the conventional control method and updates the control gain in real time according to the desired system parameters to enhance the robustness of the controller. Finally, the effectiveness of the offline neural network and online discrimination correction is verified by mathematical simulations, and the effectiveness and robustness of the adaptive control proposed in this paper are verified by comparative simulation.

Robust Adaptive Prescribed Performance Control for Unknown Nonlinear Systems With Input Amplitude and Rate Constraints

A novel approximation-free prescribed performance control scheme for unknown nonlinear systems with amplitude and rate saturation on the control input signal is designed in this letter. The proposed control strategy employs nested smooth saturation functions and introduces a reconciling relaxation of the performance constraints based on the actuator limitations. The straightforward gain selection along with the low complexity of the control scheme, simplifies the practical implementation of our algorithm. The adoption of the adaptive prescribed performance control technique ensures the desired trade-off between input and output constraints for any input-to-state stable (ISS) system. Inevitably, for generic systems, the boundedness properties are guaranteed only locally; thus, we provide a sufficient boundedness condition for all closed-loop signals. Finally, an illustrative simulation study is conducted to demonstrate the efficacy of the proposed approach.

Command filtered adaptive tracking control of nonlinear systems with prescribed performance under time‐variant parameters and input delay

AbstractIn this article, a command filtered asymptotic adaptive prescribed performance control method is presented for nonlinear systems with time‐variant parameters, input delay, and external disturbances. The feature of the concerned system is more general and practical, which makes the controller development more complicated. By exquisitely constructing a set of auxiliary systems, both the command filtered errors and input delay are actively compensated simultaneously. Then a smooth nonlinear term with an updated gain is introduced into the controller design to concurrently compensate for time‐variant parameters and external disturbances. With the integration of the command filtered technique, the adaptive control and the prescribed performance function, a command filter‐based adaptive prescribed performance control framework is skillfully exploited, in which tracking errors of all the states are restricted into the preset regions. Based on the Lyapunov theory, both the transient and zero‐error asymptotic convergence performance can be guaranteed with the developed control method. Finally, simulation results demonstrate the preponderance of the exploited approach.

Extended-State-Observer-Based Adaptive Prescribed Performance Control for Hydraulic Systems With Full-State Constraints

In this article, an innovative backstepping controller for hydraulic systems is proposed to handle system uncertainties and accomplish specified performance tracking without violating the full-state constraints. To deal with uncertainties, extended state observers ESOsand an adaptive law are integrated. ESOs are structured to estimate disturbances, whereas adaptive law is applied to approximate unknown parameters. The estimated uncertainties are then incorporated into a constrained controller, ensuring that both the prescribed transient tracking performance and the nonviolation of full-state constraints can be guaranteed. A prescribed performance function (PPF) and the barrier Lyapunov function (BLF) are synthesized to guarantee the transient behavior of the tracking error and all state errors within desirable boundaries. Then, an adaptive prescribed performance controller with uncertainty compensation is constructed by merging the BLF and PPF through back-stepping design to stabilize the closed-loop system. Finally, abundant comparative experimental results validate the proposed controller's tracking performance.

Adaptive Prescribed Performance Control of A Flexible-Joint Robotic Manipulator With Dynamic Uncertainties.

An adaptive fuzzy control strategy is proposed for a single-link flexible-joint robotic manipulator (SFRM) with prescribed performance, in which the unknown nonlinearity is identified by adopting the fuzzy-logic system. By designing a performance function, the transient performance of the control system is guaranteed. To stabilize the SFRM, a dynamic signal is applied to handle the unmodeled dynamics. To cut down the communication load of the channel, the event-triggered control law is developed based on the switching threshold strategy. The Lyapunov stability theory and backstepping technique are applied coordinately to design the control strategy. The semiglobally ultimately uniformly boundedness can be ensured for all signals in the closed-loop system. The designed control method can also guarantee that the tracking error can converge to a small neighborhood of zero within the prescribed performance boundaries. At the end of the article, two illustrative examples are shown to validate the designed event-triggered controller.

Adaptive neural prescribed performance control for switched pure-feedback non-linear systems with input quantization

Purpose This paper aims to investigate an adaptive prescribed performance control problem for switched pure-feedback non-linear systems with input quantization. Design/methodology/approach By using the semi-bounded continuous condition of non-affine functions, the controllability of the system can be guaranteed. Then, a constraint variable method is introduced to ensure that the tracking error satisfies the prescribed performance requirements. Meanwhile, to avoid the design difficulties caused by the input quantization, a non-linear decomposition method is adopted. Finally, the feasibility of the proposed control scheme is verified by a numerical simulation example. Findings Based on neural networks and prescribed performance control method, an adaptive neural control strategy for switched pure-feedback non-linear systems is proposed. Originality/value The complex deduction and non-differentiable problems of traditional prescribed performance control methods can be solved by using the proposed error transformation approach. Besides, to obtain more general results, the restrictive differentiability assumption on non-affine functions is removed.

Prescribed Performance Adaptive Balance Control for Reaction Wheel-Based Inverted Pendulum-Type Cubli Rovers in Asteroid

This paper investigates the issue of balance control for reaction-wheeled inverted pendulum-type Cubli Rovers on asteroids, and an adaptive control scheme is proposed via the prescribed performance control technique. The main feature lies in the fact that the transient behavior is satisfied which is required critically in the environment of asteroids. The attitude model of reaction-wheeled inverted pendulum-type Cubli Rovers is first constructed by virtue of the momentum moment theorem and Eulerian kinematics. Based on that, the gravitational field in the asteroid is described and the avoiding jumping condition is analyzed. Then, an adaptive prescribed performance control (APPC) method is proposed to obtain the fine tracking performance of the equilibrium error such that the inverted pendulum-type Cubli Rovers achieve the self-balancing motion. The proposed method is capable of ensuring the tracking errors inside the preset boundary functions, and the asymptotic stability of all states in the closed-loop system is guaranteed via the Lyapunov stability theory. The simulation and comparison results on the environment of asteroids verify the effectiveness and superiority of the presented control law.

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.

Data-driven prescribed performance control for satellite with large rotational component

In this paper, the high precision attitude control for satellite with large misaligned rotational component is investigated, proposing a novel model-free prescribed performance adaptive control (MF-PPAC) method. Based on the model-free adaptive control (MFAC) strategy, high-precision attitude control is achieved depending on the system measurement rather than the spacecraft mathematical model, which demonstrates the superiority in handling nonlinearity and uncertainty of the spacecraft system, especially for those with unbalance of the rotational component. Furthermore, the transient and the stable-state behavior of the tracking error using MFAC is constrained in the prescribed performance bounds and converges to zero gradually with the utilization of prescribed performance function (PPF) and error transformation method. Finally, the convergence and boundedness of the system error, the bounded-input bounded-output (BIBO) stability of the proposed MF-PPAC is demonstrated by the contraction mapping theory. Simulation and comparison with disturbance-observer-based PD control and MFAC illustrate the effectiveness of the proposed method.

Singularity-Free Continuous Adaptive Control of Uncertain Underactuated Surface Vessels With Prescribed Performance

This article is dealt with the problem of trajectory tracking with prescribed performance for a family of underactuated surface vessels (USVs) under model uncertainties and disturbances. The prescribed performance means that the USV tracks a given trajectory with the arbitrarily predefined speed of response and accuracy. The existing prescribed performance control (PPC) solutions and the traditional robust control approaches for USVs may have the singularity issue or cause a discontinuous control signal. Thereby, a new-type adaptive PPC strategy is put forward in this article. The adaptive technique is devoted to tackling model imperfections as usual, whereas the constraint-handling technique is adopted in a novel way. Herein, we first construct an auxiliary variable instead of using the approach angle or azimuth angle. Then, we impose constraints on the position error, not the tracking error, and the auxiliary variable, simultaneously. In this way, the predefined performance is achieved by moreover a singularity-free continuous control action. These theoretical findings are illustrated via a comparative simulation study.

Prescribed performance adaptive control of dual-arm robots with guaranteed motion precision

Prescribed performance adaptive control of dual-arm robots with guaranteed motion precision