Backstepping Control Technique Research Articles

Rooted Tree Optimization for the Backstepping Power Control of a Doubly Fed Induction Generator Wind Turbine: dSPACE Implementation

With the development of wind power generation in recent years, several studies have dealt with the active and reactive power control of wind power systems, along with the quality of energy produced and the connection to distribution networks. In this context, this research proposes a new contribution to the field. The major objective of this work is the development of a nonlinear adaptive backstepping control technique applied to a DFIG based wind system and an optimization technique that uses the rooted tree optimization (RTO) algorithm. The backstepping control strategy is based on the Lyapunov nonlinear technique to guarantee the stability of the system. It is applied to the two converters (i.e., machine and network sides) and subsequently improved with estimators to make the proposed system robust to parametric variation. The RTO technique is based on monitoring the behavior of the underlying foundation of trees in search of underground water in accordance with the level of underground control. The solution proposed for the control is validated using two methods: (1) a simulation on MATLAB/Simulink to test the continuation of the reference (real wind speed) and the robustness of the system and (2) a real-time implementation on a dSPACE-DS1104 board connected to an experimental bench in a laboratory. Simulation and experimental results highlight the validation of the proposed model with better performance compared with other control techniques, such as sliding mode control, direct power control, and field-oriented control.

DSC-ESO Approach to Robust Sliding Model Control for Ship’s Curve Trajectory Tracking

In order to solve the problem of ship's curve trajectory-tracking control, the Norrbin nonlinear response model which can accurately describe the ship's motion state is selected in this paper. The hyperbolic tangent function is used to design the expected hemispheric angle equation, then the complex track control is transformed into a heading control problem. The fast terminal sliding mode (FTSM) is introduced together with the Backstepping control technique to reduce the system adjustment time, eliminate the chattering. Bying combined with extended states observer (ESO) and dynamic surface control (DSC) technique, the internal and external disturbances in real-time can be estimated and compensated, and the “explosion of complexity” caused by backstepping technique is solved. The state of the control system is bounded and stable, and the system error converges to zero. Matlab simulation proves that the controller can realize the trajectory-tracking control quickly and accurately, and has strong robustness to external disturbances.

Vibration control of a military vehicle weapon platform under the influence of integrated ride and cornering dynamics

The present study is focussed upon vibration control of the weapon elevation and azimuth dynamics mathematical model under influence of the 20 degree of freedom integrated ride and cornering dynamics non-linear mathematical model of a military vehicle with trailing arm suspension. The PID, LQR and Backstepping control techniques are applied in the weapon dynamics model in order to achieve the desired level of gun stabilisation over different manoeuvring situations. The control methods are initially implemented in the weapon elevation dynamics mathematical model which is subjected to vehicle ride response inputs only. In the later section, the control methods are incorporated in the azimuth dynamics mathematical model which is subjected to the integrated ride and cornering dynamic response inputs from different manoeuvres. The control forces are incorporated in the governing equations of motion for the weapon elevation and azimuth dynamics. The equations of motion for the weapon elevation and azimuth dynamics with incorporated control parameters, are transformed into state space matrix domain and solved by using Matlab. The elevation and azimuth dynamic responses are observed over the random terrain and with variable track velocities, respectively and compared with the corresponding passive models. It is observed that adequate attenuation of the vehicle dynamic inputs could be attained with the control techniques which led to desired weapon stabilisation in both elevation and azimuth directions. Compared to other controllers, backstepping control strategy is observed to provide the maximum attenuation in weapon responses by directly considering the Lyapunov stability criterion in its formulation. Therefore, the basic focus is to evaluate the gun muzzle response reduction by implementing different control techniques under the influence of a non-linear vehicle dynamic platform. These studies would provide the motivation and foundation behind design and development of gun control system for the military vehicles with All Electric Drive.

Nonlinear disturbance observer based sliding mode control for a benchmark system with uncertain disturbances

Taking uncertain disturbances into account, the control problem of the translational oscillator with a rotational actuator (TORA) is considered in this paper. Motivated by the desire to attenuate influences from unknown disturbances/uncertainties, the disturbance-observer-based methodology is utilized. Specifically, a system model with a cascade structure for the TORA system is obtained after a series of coordinate transformations. Then, inspired by the backstepping control technique, for the first subsystem, a virtual control variable is introduced and an error-signal-based system is designed. Next, an estimator is presented and used to estimate unknown disturbances, based upon which a sliding mode control approach is devised to ensure the underactuated TORA system is asymptotically stable at the origin. Finally, the applicability and robustness of the designed control method are examined via three group numerical simulation tests.

Sideslip-Compensated Guidance-Based Adaptive Neural Control of Marine Surface Vessels.

This article presents an improved guidance law for underactuated marine vessels that compensates cross-track error caused by external disturbances through its sideslip. The proposed guidance law demonstrates improved path-following performance regardless of disturbances, such as waves, winds, and ocean currents. This article also presents an adaptive neural-network (NN) control law for the partially known vessel dynamics with state constraints. For satisfying the state constraints, this control scheme adopts an integral barrier Lyapunov function (iBLF)-based backstepping control technique. It is shown that the closed-loop system remains bounded, and state constraints are always satisfied. Finally, the efficacy of the improved guidance law and iBLF-based adaptive control strategy was verified in simulation and experiments using an autonomous surface vessel.

Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system

In this study, the control problem of complex robot system with uncertainties and disturbances is addressed. Fuzzy system-fuzzy neural network-backstepping control (FS-FNN-BSC) system is proposed, which can guarantee the accurate, stable and efficient control. First, the general dynamics model of robot is introduced briefly. Then, the design procedure of backstepping control (BSC) technique is presented, to make the best of the advantages of fuzzy system (FS) and fuzzy neural network (FNN) and compromise the accuracy and efficiency, the FS is adopted to approximate the modeling information, and the FNN is utilized to approximate and predict the non-modeling information, and the FS-FNN-BSC system is constructed. Moreover, based on the Lyapunov stability theorem, the stability of the FS-FNN-BSC is proved. To illustrate the correctness, practicality and generality of the proposed control method, the FS-FNN-BSC system is applied to the series robot (KUKA robot) and the parallel robot (Delta robot). And the superiority of the proposed FS-FNN-BSC strategy is highlighted by quantitative comparison with the existing intelligent control methods.

Adaptive Fuzzy Fixed-Time Decentralized Control for Stochastic Nonlinear Systems

This article studies the problem of adaptive fuzzy fixed-time decentralized control for nonlinear interconnected systems with stochastic disturbances and unknown nonlinearities. In control design, fuzzy logic systems are utilized to identify the unknown nonlinear functions. Combining stochastic fixed-time Lyapunov stability theory with adaptive backstepping control technique, a fuzzy adaptive fixed-time decentralized control design algorithm is developed by adopting smooth projection operator. It is proved that all the state variables of the closed-loop system are globally fixed-time stable in probability. Finally, both numerical and practical examples are provided to elucidate the feasibility of the proposed control algorithm.

IBLF-Based Finite-Time Adaptive Fuzzy Output-Feedback Control for Uncertain MIMO Nonlinear State-Constrained Systems

This article considers the problem of finite-time adaptive fuzzy output-feedback control design for multi-input–multioutput uncertain nonlinear systems subject to full state constraints. By employing the finite-time stability theory, a new finite-time adaptive fuzzy output-feedback control approach is proposed. An integral barrier Lyapunov functional is utilized to prevent all states from violating their constraints. Fuzzy logic systems are developed to approximate the uncertainties. A fuzzy state observer is constructed to estimate the unmeasurable states. Moreover, to handle the “explosion of complexity” issue in the backstepping control technique, a finite-time convergent differentiator is introduced to estimate the time derivatives of virtual control signals. The stability analysis showed that the control approach guarantees that all closed-loop signals are bounded, and the tracking errors converge to a small neighborhood of the origin in a finite time. Finally, the effectiveness of the proposed control scheme is confirmed by numerical simulations.

A Composite Nonlinear Controller for Power Systems with STATCOM under External Disturbances

This paper concentrates on the design of a composite nonlinear stabilizing state feedback control for power systems with static synchronous compensator (STATCOM) with the help of a combination of backstepping strategy and a nonlinear disturbance approach. The disturbance observer is used to estimate unavoidably external disturbances. Thus, the obtained control law can be used to successfully stabilize the system stability and reject undesired external disturbances. In order to demonstrate the effectiveness of the developed process design, numerical simulation results are provided to indicate that the presented composite controller can improve dynamic performances, rapidly suppress system oscillations of the overall closed-loop dynamics, and despite having inevitably external disturbances, performs better than a conventional backstepping control technique.

Nonlinear Excitation Control of Diesel Generator: A Command Filter Backstepping Approach

This article proposes an alternate approach following command-filtered backstepping (CFBS) principle to control the terminal voltage and stabilize the speed of a diesel generator through the excitation system. This controller eliminates the errors introduced due to differentiation of input signal and is, therefore, better compared to the conventional backstepping control technique. The global stability conditions of the overall closed-loop system are established using Lyapunov criteria. The parameters of the controller are optimized using a comprehensive learning particle swarm optimization technique. The performance of the proposed controller is compared with two other controllers, which include a classical proportional integral derivative (PID) and ΔΣ-based PID controllers. The performance comparison using percentage overshoot and settling time demonstrate that the proposed controller is superior and could effectively control the terminal voltage and stabilize the speed under various fault conditions.

Decentralized Adaptive Fuzzy Tracking Control for a Class of Nonlinear Uncertain Interconnected Systems With Multiple Faults and Denial-of-Service Attack

This article studies the decentralized adaptive fuzzy tracking control problem for a class of large-scale interconnected uncertain systems while considering faults and denial-of-service attack. It is assumed that nonlinear term, interconnected term, actuator faults coefficients, and sensor faults coefficients are unknown. Thus, fuzzy logic system and adaptive method are utilized to deal with these unknown terms. Backstepping and dynamic surface control technique are used in control design procedure and a new algorithm is proposed to obtain a switching observer gain for tracking problems with faults and cyber-attack. It turns out that the designed controller can compensate the effect of faults and uncertainties, all the signals in close-loop systems are bounded, and the tracking error converges to a small neighborhood of origin. Finally, a simulation example is given to prove the feasibility and effectiveness of the theoretical findings in this article.

Control design of damper mass spring system based on backstepping controller scheme

AbstractThe objective of this paper is to present a proposed control model for the electromechanical damper mass spring system including the backstepping technique in comparison with the conventional proportional–derivative–integral (PID) controller unit to realize the best performance of the control systems. The suggested approach demanded the construction in laboratory arrangement of damper mass spring system which linked with electrical position sensor, and the theoretical work involved the derivation of the required mathematical equations in order to formulate the simulation models in Matlab software package. The obtained results show that the backstepping control technique provides the better performance associated with stable control system especially with increasing the value of selected mechanical load.

Advanced Control Strategies for DC–DC Buck Converters With Parametric Uncertainties via Experimental Evaluation

In this paper, four control strategies for DC-DC buck converters are proposed, compared and analyzed: a single-loop adaptive control strategy (SA), a double-loop adaptive control strategy (DA), a single-loop disturbance observer-based control strategy (SDOB) and a double-loop disturbance observer-based control strategy (DDOB). First, the nominal system without considering the parametric uncertainties of the DC-DC buck converter is built to help develop the SA and DA. The SA is built by adaptive and backstepping control approaches, and the DA is set up by adaptive and sliding mode control approaches. Additionally, a model considering parametric uncertainties is introduced, giving the opportunity to develop the SDOB and DDOB. The SDOB is developed using a designed disturbance observer and backstepping control technique, and the DDOB is synthesized using a designed disturbance observer and sliding mode control method. Finally, the advantages and disadvantages of the four proposed control strategies are compared and analyzed through experiments.

Event-Triggered Output-Feedback Control for Large-Scale Systems With Unknown Hysteresis.

This article focuses on the event-triggered-based adaptive neural-network (NN) control problem for nonlinear large-scale systems (LSSs) in the presence of full-state constraints and unknown hysteresis. The characteristic of radial basis function NNs is utilized to construct a state observer and address the algebraic loop problem. To reduce the communication burden and the signal transmission frequency, the event-triggered mechanism and the encoding-decoding strategy are proposed with the help of a backstepping control technique. To encode and decode the event-triggering control signal, a one-bit signal transmission strategy is adopted to consume less communication bandwidth. Then, by estimating the unknown constants in the differential equation of unknown hysteresis, the effect caused by unknown backlash-like hysteresis is compensated for nonlinear LSSs. Moreover, the violation of full-state constraints is prevented based on the barrier Lyapunov functions and all signals of the closed-loop system are proven to be semiglobally ultimately uniformly bounded. Finally, two simulation examples are given to illustrate the effectiveness of the developed strategy.

Predefined-time adaptive fault-tolerant control of hypersonic flight vehicles without overparameterization

In this paper, the predefined-time adaptive fuzzy tracking control problem of hypersonic flight vehicles (HFVs) without overparameterization is investigated. Novel fuzzy adaptive controllers are derived based on fuzzy approximation and backstepping control techniques. Firstly, a new performance function is introduced to ensure the predefined-time convergence of the output tracking error. Secondly, a novel exact tracking control strategy is proposed by introducing a vanishing time-related function, and the asymptotic tracking performance of the proposed controller is achieved. Thirdly, a bound estimation approach is involved in dealing with the unknown system dynamics as well as time-varying faults, and only two adaptive parameters are required to be estimated for each subsystem. As a result, the computational burden is significantly reduced without accuracy decreasing. The stability of the closed-loop system is proved via Lyapunov method, and the effectiveness of the proposed control scheme is demonstrated with numerical simulations.

Backstepping Control of Rewinding Systems with Flexible Couplings

Roll-to-roll (R2R) system can be found and applied in various fields, such as paper manufacture and printing process. The matter regarding tension control is still a challenge because this tends to rely on elasticity of web materials with its elasticity and roll inertia which change. Additionally, another issue is limited stiffness shafts connecting the web handling system and driving motor. Due to non-rigid nature of the shafts, un-wanted vibration can be released, and this impact to the system. Therefore, the tension control is more complicated. In this paper, a control solution for a roll-to-roll web-transport system with flexible couplings will be performed. The connection of this system coupled with motors through non-rigid driving shaft is formed as a two-mass system. Moreover, the paper shows that the thickness of web material is assumed to be conscious in order to achieve a simple calculation of roll inertia momentum. By using backstepping control technique, control laws for unwinding and rewinding roll are defined. The control schemes ensure a linear velocity and tension tracking performance of the system. Extensive numerical simulations are carried out to verify the feasibility of the proposed control strategy. The simulation results indicate the effectiveness of the proposed control, web tension and position are driven to desired values.

Improved adaptive NN backstepping control design for a perturbed PVTOL aircraft

This paper proposes an improved flight control scheme for a perturbed planar vertical take-off and landing (PVTOL) aircraft based on backstepping and neural networks. In this approach, three neural networks are applied to deal with the external disturbances of the aircraft system. Instead of using σ-modification to design the adaptive laws, gradient descent algorithm is adopted to train the weight parameters of neural networks such that high function approximation precision can be achieved. By resorting to Lyapunov stability criterion, it can be proved that the reference signals are tracked by the aircraft’s outputs with small errors. In the end, simulation results are used to illustrate the superiority of the our approach compared with traditional direct adaptive neural network backstepping control technique.

Control Methods Comparison for the Real Quadrotor on an Innovative Test Stand

This article is a continuation of our previously published work that presented a comparison of nine attitude quaternion-based controllers of the quadrotor in simulation environment. In this article, the best three controllers were implemented into the real quadrotor. Namely proportional derivative (PD), linear quadratic regulator (LQR) and backstepping quaternion-based control techniques were evaluated. As a suitable test stand was not available on the basis of literature analysis, the article also outlines the requirements and the development of a new innovative test stand. In order to provide a comprehensive overview, the hardware and software that was used is also presented in the article. The main contribution of this article is a performance comparison of the controllers, which was based on absolute quaternion (positioning) error and energy consumption.

Composite control of fuel quantity actuator system for diesel engines via backstepping control technique and generalised proportional integral observer

In an electronically controlled VE distributive pump, the fuel quantity actuator (FQA) is a significant component. It is responsible for governing the quantity of fuel being injected into diesel-type engines. There exist non-linearities in the system, and usually, non-linearities are neglected in modelling and control design, which makes the performance of the closed-loop system degrade. Therefore, the authors take the non-linearities of the rotary electromagnet and offsetting spring into consideration and establish the more detailed mathematical model in this study. Besides, the FQA system always confronts disturbances caused by external torque and input voltage variation in the real working condition. Furthermore, to deal with the non-linearities and reject the disturbances, a generalised proportional integral observer (GPIO)-based backstepping control approach is presented. By using a GPIO, the state estimations and disturbances estimation can be obtained at the same time. In addition, a theoretical analysis of the closed-loop system is given, showing its asymptotic stability, even under acting lumped disturbance. The introduced control scheme exhibits satisfactory performance in terms of transient behaviour and disturbance rejection. Finally, a set of simulation and experimental tests are carried out to validate the feasibility as well as efficiency of the proposed control framework.

Adaptive Fuzzy Integral Sliding-Mode Control for Robust Fault-Tolerant Control of Robot Manipulators With Disturbance Observer

This article develops a new strategy for robust fault-tolerant control (FTC) of robot manipulators using an adaptive fuzzy integral sliding-mode control (ISMC) and a disturbance observer (DO). First, an ISMC is developed for the FTC system. The major features of the approach are discussed. Then, to enhance the performance of the system, a fuzzy logic system approximation and a DO are introduced to approximate the unknown nonlinear terms, which include the model uncertainty and fault components, and to estimate the compounded disturbance and then are integrated into the ISMC. Next, a switching term based on an adaptive two-layer supertwisting algorithm is designed to compensate the disturbance estimated error and guarantee stability and convergence of the whole system. The nominal controller of the ISMC is reconstructed using a backstepping control technique to achieve the stability for the nominal system based on the Lyapunov criterion. The computer simulation results demonstrate the effectiveness of the proposed approach.