Adaptive Dynamic Surface Control Method Research Articles

Neural adaptive dynamic surface control for position tracking of electrohydraulic servo systems based on extended state observer

High-performance motion tracking of electro-hydraulic servo systems plays an important role in developing industrial technology. However, the system itself has parameter uncertainty, uncertain nonlinearity, and measurement noise, significantly decreasing the performance of conventional controllers designed based on nominal models. To improve the tracking performance of electro-hydraulic servo systems, an adaptive dynamic surface control method combining extended state observer and radial basis function neural network is proposed. Firstly, an extended state observer combining neural network output and parameter adaptation technology is designed without the need for speed and pressure feedback to observe the system’s unknown state variables and nonlinear matched disturbance. The design of neural networks is used to approximate mismatched disturbance with significant nonlinearity online. Then, the proposed extended state observer is introduced into the neural adaptive backstepping design, effectively compensating for simultaneous matched and mismatched disturbances, thereby suppressing most of the uncertain nonlinearity of the system. Meanwhile, online update of uncertain parameters further improves the tracking performance of the controller. In addition, the introduction of dynamic surface overcomes the “explosion of complexity” issue in backstepping design. The rigorous stability of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness of the proposed controller is validated through comparative experiments on valve-controlled hydraulic cylinder.

Robust adaptive dynamic surface control of high-order strict feedback systems based on fully actuated system approach

In this study, the authors propose a robust adaptive dynamic surface control method by using the fully actuated system approach for high-order strict-feedback systems (SFSs) with parameter uncertainty and disturbance. Each subsystem of the SFSs is a high-order system with a full actuation structure. In contrast to the traditional first-order state space method, the proposed control method directly treats each high-order subsystem as a whole without transforming it into a first-order system, which is a concise and efficient treatment. By introducing a series of first-order low-pass filters in each step of the design, the high-order derivatives of the virtual control law are obtained, and the complex and multiple derivation operations are transformed into simple algebraic operations. Adaptive control and robust control are combined to address parameter uncertainty and external disturbances in the system. The Lyapunov stability theory is utilised to demonstrate that all signals in the closed-loop system are uniformly ultimately bounded. The system output can effectively track the desired reference signal under specific constraints, and the tracking error can be adjusted by tweaking the parameters to converge to a sufficiently small neighbourhood around zero. Ultimately, the efficiency of the proposed control method is validated through simulations on a flexible joint manipulator system.

Research on Variable-Swept Hybrid Aerial Underwater Vehicle Plunge-Diving Control Based on Adaptive Dynamic Surface Control

The variation in aerodynamic parameters during the process of a variable sweepback hybrid aerial underwater vehicle (HAUV) affects flight stability. During the air–water trans-media locomotion, there are medium mutations and solid–liquid gas coupling phenomena, resulting in the complex dynamic process of HAUV. To ensure stable control during the trans-media process of a variable sweepback vehicle, this study proposes a neural-network-based adaptive dynamic surface control method for aircraft flight-path angle. This method aims to establish an effective control model for the entire process of air to media transition, in response to the characteristics of uncertainty and external disturbances in the process of variable backsweeping in the air and media transition. By utilizing the multibody dynamics method, the dynamic equations for variable-swept vehicles are established and transformed into a rigorous feedback system with model uncertainty. The adaptive dynamic surface method in this paper introduces a first-order filter, which overcomes the “differential explosion” problem in traditional backstepping control design through differential filtering; the unknown parameters present in the model are estimated online through adaptive laws, and the uncertain parts of the system are overcome through nonlinear damping items. By analyzing Lyapunov stability, the semi-global stability of the required closed-loop system can be obtained, and adjusting the controller parameters can make the tracking error infinitely small. Numerical simulations are conducted to illustrate the tracking control of flight-path angles for different plunge-diving angle rates and strategy of ingress. The results show that HAUV with variable-swept configuration with different strategy has a great effect on the stability of plunge-diving locomotion; the designed controller can effectively track the target trajectory and has a certain degree of robustness and adaptability.

Appointed-Time Prescribed Performance Fault Tolerant Control for QUAV With Actuator Fault and Model Parameters Uncertainties

In this paper, an appointed-time prescribed performance fault-tolerant control (ATPPFTC) method for quadrotor unmanned aerial vehicle (QUAV) system is studied in the presence of model parameters uncertainties, actuator faults and external disturbances. For the position loop and the attitude loop, the proposed method overcomes the model parameters uncertainties caused by the changes of rotary inertia, the mass and aerodynamic damping coefficients. Meanwhile, unknown actuator faults and unknown external disturbances are investigated by using adaptive method. Moreover, a new appointed-time prescribed performance function and coordinate transformation are introduced to impose performance characteristics on the tracking errors. Based on the Lyapunov stability theory, an adaptive dynamic surface control method is proposed to ensure that the position and attitude tracking errors of the closed-loop system can achieve the appointed-time convergence and prescribed transient and steady-state performance. Incidentally, the convergence speed and convergence time of the system tracking error can be set flexibly. Finally, the simulation verifies the effectiveness and superiority of the proposed control scheme from both qualitative and quantitative aspects.

Adaptive dynamic surface control using nonlinear disturbance observers for position tracking of electro-hydraulic servo systems

In this article, an adaptive dynamic surface control method with nonlinear disturbance observers is proposed for accurate position tracking of an electro-hydraulic servo system with unknown time-varying inner or external disturbances. The dynamic surface control approach adopted in the proposed controller is used to ameliorate the inherent complexity differentiation explosion of traditional backstepping method, which significantly simplifies the controller design process. The designed nonlinear disturbance observers are exploited to online estimate the inner or external disturbances of electro-hydraulic servo systems, and the performance degradation resulted from unknown time-varying disturbances is effectively suppressed. To further compensate for the system’s time-varying uncertain parameters, parameter adaptive updating laws are designed and combined in the proposed controller for accurate position tracking of electro-hydraulic servo systems. The closed-loop stability of the proposed controller is theoretically guaranteed by rigorous Lyapunov analysis. Comparative experimental results are carried out on a typical single-degree-of-freedom electro-hydraulic servo system, and the feasibility together with the superiority of the proposed controller is experimentally validated.

Indirect Adaptive Robust Control Design for Course Tracking of Ships Subject to Unknown Control Coefficient and Disturbances

For course control of ships with unknown control coefficient and model parameters, an indirect adaptive robust controller, in which the parameter estimation law and the control law are designed separately, is proposed. This design method can achieve not only excellent course control performance but also accurate parameter estimates for secondary purposes such as assisting in ship maneuvering decision. Firstly, a Nussbaum function is combined with the adaptive dynamic surface control method to design a strong robust controller which can ensure the stability of the closed-loop ship course control system in spite of parameter uncertainties, unknown control coefficient and disturbances. Secondly, the nonlinear model for ship steering is converted into linear form by using the X-swapping technique. And a modified least-squares identification algorithm is then proposed to estimate the unknown model parameters. The global uniform ultimate boundedness of all signals of the resulting closed-loop system is guaranteed via Lyapunov stability theory. Lastly, simulation results are executed to demonstrate the effectiveness of the proposed design method.

Neural network controller design for fractional-order systems with input nonlinearities and asymmetric time-varying Pseudo-state constraints

Abstract This article considers the neural adaptive control issues of a category of non-integer-order non-square plants with actuator Nonlinearities and Asymmetric Time-Varying pseudo-State Constraints. First, the original non-square non-affine system with input nonlinearities is transformed into an equivalent affine-in-control square model by defining a set of auxiliary variables and by employing the mean-value theorem. Second, Neural networks and Nussbaum functions are exploited to obviate the requirement of a complete knowledge of the system dynamics and the control directions, respectively. Third, a novel adaptive dynamic surface control method based on Caputo fractional derivative definitions and fractional order filters is developed to overcome the “explosion of complexity” problem in the traditional backstepping design process and to determine the parameter update laws and control signals, concurrently. Then, Asymmetric Barrier Lyapunov Functions with error variables are adopted to ensure the uniform stability of the closed-loop system and to prevent the violation of the full pseudo-State constraints. The novelties and contributions of this article are: (1) through the introduction of new technical Lemmas and corollaries, existing control design and stability theories linked to integer-order square systems are developed and extended to non-square non-integer-order ones. (2) all signals, including variables and errors in the closed-loop system are semi-global practical finite-time stability whereas the the tracking errors are asymptotically driven to zero without transgression of the constraints. Finally, the effectiveness and potential of the proposed control approach are substantiated by two example simulations.

Attitude Tracking Control of Small-Scale Unmanned Helicopters Using Quaternion-Based Adaptive Dynamic Surface Control

In this paper, a quaternion-based adaptive dynamic surface control method is proposed for attitude tracking control for small-scale unmanned helicopters with external disturbance and uncertain dynamics. The quaternion formalism is introduced and a quaternion-based multi-input-multi-output nonlinear model is derived from the attitude dynamics of a small-scale helicopter. The low-complexity controllers are designed by the dynamic surface control method as it eliminates the problem of the explosion of items. The singularity problem is avoided by substituting Euler kinematic equations in the nonlinear model with quaternion expressions and integrating the quaternion expressions into the design process of the dynamic surface control. For improving the robustness of the control system, the radial basis function networks are applied to approximate the uncertain dynamics. The external disturbance is also compensated in the controllers’ design. This paper proves that the proposed method can guarantee the uniformly ultimate boundness of this attitude system. Simulation results are presented finally and show the effectiveness of this control approach.

Controlling uncertain Genesio–Tesi chaotic system using adaptive dynamic surface and nonlinear feedback

An adaptive dynamic surface control method using nonlinear feedback is proposed for controlling the uncertain Genesio-Tesi chaotic system. The feature of the nonlinear feedback technique lies in that the feedback gains self-adjust under different amplitudes of system states. Based on the dynamic surface control technique, the complexity explosion problem existing in the backstepping-based chaotic controllers is circumvented. Moreover, the closed-loop stability is guaranteed with rigorous mathematical proof using Lyapunov stability theorem. Comparative results are given to verify the effectiveness and advantage of the proposed method with comparison to the existing linear feedback control.

A novel disturbances compensating dynamic positioning of dredgers based on adaptive dynamic surface control

In order to deal with the control difficulties of the dredger's dynamic positioning system under large disturbances and severe sea conditions, an adaptive dynamic surface control method is proposed...