Dynamic Surface Control Method Research Articles

Adaptive neural nonsingular terminal sliding mode control for MEMS gyroscope based on dynamic surface controller

A novel adaptive dynamic surface control (DSC) method for the micro-electromechanical systems gyroscope, which combined the approaches of a radial basis function neural networks (RBFNN) and a nonsingular terminal sliding mode (NTSM) controller was proposed in this paper. In the DSC, a first-order filter was introduced to the conventional adaptive backstepping technique, which not only maintains the advantage of original backstepping technique, but also reduces the number of parameters and avoids the problem of parameters expansion. The RBFNN is an approximation to the gyroscope’s dynamic characteristics and external disturbances. By introducing a nonsingular terminal sliding mode controller which ensuring the control system could reach the sliding surface and converge to equilibrium point in a finite period of time from any initial state. Finally, simulation results prove that the proposed approach could reduce the chattering of inputs, improve the timeliness and effectiveness of tracking in the presence of model uncertainties and external disturbances, demonstrating the excellent performance compared to nonsingular terminal sliding mode control (NTSMC).

Adaptive DSC of stochastic non‐linear systems with input unmodelled dynamics

An adaptive dynamic surface control (DSC) method is proposed for a class of stochastic non-linear systems with input and state unmodelled dynamics in this paper. A normalisation signal is introduced to restrict the input unmodelled dynamics. By introducing a non-linear transformation, modified DSC is extended and applied to a class of more general stochastic non-linear systems. By theoretical analysis, it is shown that all the signals in the closed-loop system are bounded in probability. Two simulation examples further demonstrate the effectiveness of the proposed control approach.

Observer-based adaptive fuzzy tracking control of nonlinear systems with time delay and input saturation

This paper studies the problem of adaptive output tracking control for a class of nonlinear systems subject to unknown time delay and input saturation. To address the delay and the input saturation, some reasonable assumptions and an auxiliary system are introduced. The fuzzy logic approach is employed to approximate the unknown functions in the system. An observer is designed to estimate the unavailable system states. The dynamic surface control (DSC) technique is utilized to avoid the problem of “explosion of complexity”. By combining the backstepping and DSC methods, a bounded control input is designed to ensure that all signals of the closed-loop system are bounded and the tracking error can fluctuate around the origin within a small neighborhood. Finally, two examples are presented to demonstrate the effectiveness and potential of the proposed new design techniques.

Adaptive-Fuzzy back stepping control of cable robot vessels

<p>Importance of sea in development, promotion and safety of the related countries make access to data and recognizing the environment become very important. Surface vessels help access to sea easier regarding technological advancement. Controlling surface vessels is considered as an active field of research regarding offshore, military and research uses. The main problem of controlling surface vessels is that these vehicles are often underactuated. Underatuation means that the system has lower number of independent actuators than degrees of freedom. In this study, designing an output feedback controller in the presence of parametric and non-parametric uncertainties independent of speed signal measurement and regarding actuators dynamic for path tracking of underactuated surface vessels, was studied. In designing controller, dynamic surface control method is used in order to reduce complexity of back stepping control.</p>

An adaptive low-dimensional control to compensate for actuator redundancy and FES-induced muscle fatigue in a hybrid neuroprosthesis

To restore walking and standing function in persons with paraplegia, a hybrid walking neuroprosthesis that combines a powered exoskeleton and functional electrical stimulation (FES) can be more advantageous than sole FES or powered exoskeleton technologies. However, the hybrid actuation structure introduces certain control challenges: actuator redundancy, cascaded muscle activation dynamics, FES-induced muscle fatigue, and unmeasurable states. In this paper, a human motor control inspired control scheme is combined with a dynamic surface control method to overcome these challenges. The new controller has an adaptive muscle synergy-based feedforward component which requires a fewer number of control signals to actuate multiple effectors in a hybrid neuroprosthesis. In addition, the feedforward component has an inverse fatigue signal to counteract the effects of the muscle fatigue. A dynamic surface control (DSC) method is used to deal with the cascaded actuation dynamics without the need for acceleration signals. The DSC structure was modified with a delay compensation term to deal with the electromechanical delays due to FES. A model based estimator is used to estimate the unmeasurable fatigue and actuator activation signals. The development of the controller and a Lyapunov stability analysis, which yielded semi-global uniformly ultimately boundedness, are presented in the paper. Computer simulations were performed to test the new controller on a 2 degrees of freedom fixed hip model after which preliminary experiments were conducted on one able-bodied male subject in the fixed hip configuration.

ℒ2 performance control of robot manipulators with kinematics, dynamics and actuator uncertainties

Summary This paper deals with the task-space trajectory tracking control problem of robot manipulators. An improved adaptive backstepping controller is proposed to deal with the uncertainties in kinematics, dynamics, and actuator modeling. To avoid the explosion of computation in conventional backstepping techniques, a modified dynamic surface control algorithm is proposed, which guarantees the asymptotic convergence rather than the uniformly ultimately boundedness of tracking errors in conventional dynamic surface control methods. Furthermore, the expression of the ℒ2 norm of tracking errors is explicitly derived in relation to the controller parameters, which provides instructions on tuning controller parameters to adjust the system performance. Moreover, the passivity structure of the designed adaptation law is thoroughly analyzed. Simulation of a free-floating space robot is used to verify the effectiveness of the proposed control strategy in comparison with the conventional tracking control schemes. Copyright © 2016 John Wiley & Sons, Ltd.

Design, analysis and simulation of a novel 3-DOF translational micromanipulator based on the PRB model

A novel 3-DOF translational compliant mechanism based on flexure hinges is designed, analyzed and simulated in this paper. The mechanism is completely decoupled in XY directions, while there is a very small parasitic motion in Z direction when the XY axes are driven due to the lack of symmetry in Z direction. The pseudo-rigid-body model (PRBM) of the mechanism is established to analyze the relationship between the stiffness of the beam and the input displacement. Considering the flexible characteristics and displacement loss of mechanism, the displacement transformation efficiency from the input-end to the output-end is calculated firstly in the flexure-based micromanipulator field. To obtain the natural frequencies of the mechanism, the Hamilton's principle is successfully used to establish the dynamic model. The analytical results are validated by the finite element model, which indicate that the calculations and designs for the compliant mechanism are feasible. The maximal coupling error is only 1.82% when input displacement is maximal. The dynamic simulation using the backstepping dynamic surface control (BDSC) method is successfully applied in the compliant mechanism to obtain a good tracking performance, the tracking errors gradually decrease along with the input frequency reduction.

Adaptive prescribed performance control of output feedback systems including input unmodeled dynamics

In this paper, an adaptive prescribed performance tracking control scheme is investigated for a class of output feedback nonlinear systems with input unmodeled dynamics based on dynamic surface control method. A transformation with respect to tracking error is introduced to implement prescribed performance tracking control. A novel description based on Lyapunov function for unmodeled dynamics is presented to deal with state unmodeled dynamics. The negative impact of nonlinear input unmodeled dynamics is offset by using a normalization signal. With the aid of Nussbaum function, the unknown control gain sign is effectively handled in the controller design. By the theoretical analysis, not only the signals in the closed-loop system are proved to be semi-globally uniformly ultimately bounded, but also the transient tracking performance can be guaranteed. Two simulation examples are provided to show the effectiveness of the proposed approach.

Output-feedback dynamic surface control for a class of nonlinear non-minimum phase systems

In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems. To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control (DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed output-feedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.

Adaptive robust control for a class of uncertain MIMO non-affine nonlinear systems

In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO non-affine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible controller singularity problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of explosion of complexity in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.

Modeling and Extended State Observer Based Dynamic Surface Control for Cold Rolling Mill System

The modeling and control problems are investigated for cold rolling mill system. Firstly, we establish a monitor automatic gauge control (MAGC) model for a practical cold rolling mill system. The new model is with mismatched uncertainties. Then, an extended state observer (ESO) is developed to estimate uncertainties. In the general high-order systems, the ESO is also used to estimate states. By dynamic surface control method, we design the controller to guarantee stabilization of the cold rolling mill system. Furthermore, we extend proposed method to general high-order systems, in which we analyze the difference from cold rolling mill system. Finally, simulation results for MAGC system are presented to demonstrate the effectiveness of the proposed control strategy.

Compound Control Strategy for MDF Continuous Hot Pressing Electrohydraulic Servo System with Uncertainties and Input Saturation

A compound control strategy is investigated for Medium Density Fiberboard (MDF) continuous hot pressing electrohydraulic servo system (EHSS) with uncertainties and input saturation. Firstly, a hyperbolic tangent function is applied to approximate saturation nonlinearity in the system. And thus the mathematical model is continuous and differentiable. Subsequently, the slab thickness tracking controller is constructed by using a dynamic surface control (DSC) method, which introduces first-order low-pass filters to calculate derivatives of virtual control input in each step. Compared with the conventional backstepping controller, complexity of the design procedure is alleviated obviously. Moreover, a composite disturbance of uncertainties and input saturation is estimated by a nonlinear disturbance observer for compensation of the control law. Finally, an appropriate Lyapunov function is chosen to prove that all signals of the closed-loop system are semiglobally uniformly ultimately bounded and the tracking error converges to zero asymptotically. Numerical simulation results are also exhibited to authenticate and validate the benefits of the proposed control scheme.

Fast Robust Integrated Guidance and Control Design of Interceptors

In this brief, a fast robust integrated guidance and control design approach, considering the 3-D interception of interceptors for hypersonic vehicles, is proposed. The proposed method is designed using the modified fast terminal sliding mode control and dynamic surface control with signal compensation. The fractional integral fast terminal sliding functions are presented independently, and all the sliding phases run parallel to increase the system response speed. Utilizing the dynamic surface control method, the robust compensation signals are constructed to eliminate the influence of uncertainty equivalents thoroughly. Therefore, the proposed approach guarantees the fast convergence of line-of-sight angular rates and the system robustness for uncertainties. The simulation results demonstrate the robustness of the proposed controller, and a variety of comparison studies are also carried out to demonstrate the advantage of the new approach.

Fuzzy Finite-Time Dynamic Surface Control for Nonlinear Large-Scale Systems

In this paper, a new finite-time dynamic surface control (DSC) method is proposed to enhance the convergence rate and robustness of a DSC system on the basis of the traditional infinite-time stability viewpoint for application to nonlinear large-scale systems. By defining a novel recursive finite-time virtual error variable, a virtual controlled stabilizing functions are derived, and the finite-time control performance is ensured by means of the finite-time-based Lyapunov stability theorem. An adaptive fuzzy logic system is adopted to approximate the unknown functions. The applicability of the proposed control strategy is verified by simulation and an experiment for a mobile manipulator and an articulated manipulator.

Impact time control guidance with field-of-view constraint accounting for uncertain system lag

The problem of impact time control guidance with seeker’s field-of-view constraint in the presence of uncertain system lag is addressed. A novel two-step control approach based impact time control guidance law with seeker’s field-of-view constraint is proposed. Specifically, in the first step, a state constrained robust adaptive control law, using the dynamic surface control method combining with the control integral barrier Lyapunov function technique, is synthesized to achieve the required robust tracking performance with respect to the desired trajectory of lead angle in the presence of uncertain system lag and other uncertainties. In the second step, the desired trajectory of lead angle is generated online to guarantee target interception at the designated impact time under the assumption of ideal autopilot dynamics while not violating the seeker’ field-of-view constraint. The proposed guidance law ensures the seeker’s field-of-view constraint does not be violated in the presence of uncertain system lag and other uncertainties. Numerical simulations are provided to illustrate the effectiveness of the proposed guidance law.

Robust Adaptive Neural Control for a Class of Time‐Varying Delay Systems with Backlash‐like Hysteresis Input

AbstractThis paper proposes a robust adaptive dynamic surface control (DSC) scheme for a class of time‐varying delay systems with backlash‐like hysteresis input. The main features of the proposed DSC method are that 1) by using a transformation function, the prescribed transient performance of the tracking error can be guaranteed; 2) by estimating the norm of the unknown weighted vector of the neural network, the computational burden can be greatly reduced; 3) by using the DSC method, the explosion of complexity problem is eliminated. It is proved that the proposed scheme guarantees all the closed‐loop signals being uniformly ultimately bounded. The simulation results show the validity of the proposed control scheme.

Observer-based adaptive neural dynamic surface control for a class of non-strict-feedback stochastic nonlinear systems

The problem of adaptive output feedback stabilisation is addressed for a more general class of non-strict-feedback stochastic nonlinear systems in this paper. The neural network (NN) approximation and the variable separation technique are utilised to deal with the unknown subsystem functions with the whole states. Based on the design of a simple input-driven observer, an adaptive NN output feedback controller which contains only one parameter to be updated is developed for such systems by using the dynamic surface control method. The proposed control scheme ensures that all signals in the closed-loop systems are bounded in probability and the error signals remain semi-globally uniformly ultimately bounded in fourth moment (or mean square). Two simulation examples are given to illustrate the effectiveness of the proposed control design.

Neural Active Disturbance Rejection Output Control of Multimotor Servomechanism

In this brief, the problems of stability and tracking control for multimotor servomechanism with unmodeled dynamics are addressed by neural active disturbance rejection control. For realizing output feedback, an extended state observer based on high-order sliding mode (HOSM) differentiator is designed to estimate the unmeasured velocity. Moreover, HOSM differentiator is introduced to modify the traditional dynamic surface control method. The designed controller solves the contradiction between rapidness and overshoot, which comes from the traditional proportional-integral-derivative that deals with a large number of practical systems with unknown disturbances. In addition, unknown functions, including friction and disturbances, are approximated by Chebyshev neural networks (CNNs), in which adaptive laws are provided by Lyapunov method. Especially, steady state and transient performance of closed-loop system are maintained by performance function in theoretical analysis. Finally, extensive experimental results are provided to illustrate our proposed approach.

Modified neural dynamic surface approach to output feedback of MIMO nonlinear systems.

We report an adaptive output feedback dynamic surface control (DSC), maintaining the prescribed performance, for a class of uncertain nonlinear systems with multiinput and multioutput. Designing neural network observers and modifying the DSC method achieves several control objectives. First, to achieve output feedback control, the finite-time echo state networks (ESN) observer with fast convergence is designed to obtain the online system states. Thus, the immeasurable states in traditional state feedback control are estimated and the unknown functions are approximated by ESN. Then, a modified DSC approach is developed by introducing a high-order sliding mode differentiator to replace the first-order filter in each step. Thus, the effect of filter performance on closed-loop stability is reduced. Furthermore, the input to state stability guarantees that all signals of the whole closed-loop system are semiglobally uniformly ultimately bounded. Specifically, the performance functions make the tracking errors converge to a compact set around equilibrium. Two numerical examples illustrated the proposed control scheme with satisfactory results.

Robust adaptive control of DC motor system fed by Buck converter

For the Buck-fed DC motor system with parameter uncertainties and external disturbances, an adaptive robust controller is proposed based on dynamic surface control and slide mode control method. The derived adaptive robust control guarantees the closedloop errors system is uniform ultimately bounded, and the parameters update laws are designed based on the uncertainty equivalence principle. The theoretical analysis and simulation results all reveal that the developed adaptive nonlinear robust controller is not sensitive to uncertainties of system, and owns simpler configuration and more accurate tracking performance than that of conventional backstepping control or PID control method.