Combined Backstepping Research Articles

Robust Output Feedback Stabilization and Tracking for an Uncertain Nonholonomic Systems with Application to a Mobile Robot.

This paper presents a novel robust output feedback control that simultaneously performs both stabilization and trajectory tracking for a class of underactuated nonholonomic systems despite model uncertainties, external disturbance, and the absence of velocity measurement. To solve this challenging problem, a generalized normal form has been successfully created by employing an input-output feedback linearization approach and a change in coordinates (diffeomorphism). This research mainly focuses on the stabilization problem of nonholonomic systems that can be transformed to a normal form and pose several challenges, including (i) a nontriangular normal form, (ii) the internal dynamics of the system are non-affine in control, and (iii) the zero dynamics of the system are not in minimum phase. The proposed scheme utilizes combined backstepping and sliding mode control (SMC) techniques. Furthermore, the full-order high gain observer (HGO) has been developed to estimate the derivative of output functions and internal dynamics. Then, full-order HGO and the backstepping SMC have been integrated to synthesize a robust output feedback controller. A differential-drive type (2,0) the wheeled mobile robot has been considered as an example to support the theoretical results. The simulation results demonstrate that the backstepping SMC exhibits robustness against bounded uncertainties.

Quadrotor control in complex manoeuvres using a hybrid backstepping and feedback linearisation control strategy

In this article, a novel control algorithm called the combined backstepping and feedback linearisation method, along with an uncertainty estimator, is presented for quadrotors. The objective is to develop a robust control algorithm capable of handling various flight conditions, compensating for uncertainties and disturbances, and effectively controlling high-speed manoeuvres. To accomplish this, the quadrotor dynamics model is first derived using the Newton–Euler method. Subsequently, a backstepping control algorithm is designed for the quadrotor's internal control layer, followed by the application of the feedback linearisation method to the external control layer. An estimator is also designed to mitigate the effects of disturbances and uncertainties. A comparison is made between the proposed combined backstepping and feedback linearisation algorithm and the backstepping method, revealing that the combined backstepping and feedback linearisation algorithm outperforms the backstepping method across different aspects. Notably, the combined backstepping and feedback linearisation algorithm achieves faster trajectory tracking and demonstrates fewer steady-state errors. Additionally, the integration of the uncertainty estimator into the combined backstepping and feedback linearisation algorithm effectively mitigates the detrimental effects of disturbances and uncertainties. Comparative results for tracking control are presented to evaluate the performance of the proposed algorithm across various scenarios and case studies.

A combined backstepping and fractional-order PID controller to trajectory tracking of mobile robots

Trajectory tracking is a critical problem in the field of mobile robotics. In this paper, a control scheme combined with backstepping and fractional-order PID is developed for the trajectory tracking of the differential-drive mobile robot. The kinematic and dynamic models of the mobile robot are described in detail for the trajectory tracking controller design. Then, based on the model of the mobile robot, the design of the trajectory tracking control system is addressed by combining backstepping with fractional-order PID. Moreover, to obtain an optimal control system, an improved beetle swarm optimization algorithm is presented to tune the parameters of the kinematic and dynamic controllers simultaneously. Finally, several simulations are implemented to the trajectory tracking of mobile robots in the cases with and without skidding and sliding, and the results can confirm the effectiveness and superiority of the combined control scheme. Abbreviations: FOPID: fractional-order PID; FOPD: fractional-order PD; DDMR:differential-drive mobile robot; BAS: beetle antennae search; BA: beetle antennae; PSO:particle swarm optimization; BSO: beetle swarm optimization.

A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots

A combined backstepping and adaptive fuzzy PID approach for a nonholonomic autonomous mobile robot to follow the desired path is proposed in this paper. Two adaptive fuzzy PID controllers are adopted at the dynamic control level for velocity tracking and steering control of the robot. The fuzzy PID controller consists of a PID controller which is designed by a trial-and-error approach, optimized using the cross-entropy method, and a fuzzy controller based on relational models with two inputs and three outputs. Adaptive adjustment of the PID controllers is implemented by means of the fuzzy controllers. The pose deviations of the robot when trajectory tracking will be eliminated by the backstepping control technique at the kinematic level using a kinematic model. The simulation validation results demonstrate that the proposed control system can offer good performances for the robot in terms of small distance error, rapid response, high stability, and trajectory tracking more accuracy.

Adaptive Fuzzy Fault-Tolerant Tracking Control of Uncertain Nonlinear Time-Varying Delay Systems

This paper investigates the problem of fuzzy-approximation-based adaptive fault-tolerant (FT) tracking control for uncertain nonlinear time-varying delay systems with nonaffine nonlinear faults. Compared with the existing results, the proposed control scheme avoids the use of the Lyapunov–Krasovskii functional, which relaxes the restriction on the derivative of unknown time-varying delay ( ${\dot \tau (t) ). By utilizing the finite covering lemma and fuzzy logic systems (FLSs), the considered time-varying delay system is transformed into novel switched nonlinear system with known constant delays. In addition, the nonaffine nonlinear faults make the control design more complicated. To overcome the difficulty, the fault function is decoupled by utilizing the mean-value theorem. In the design procedure, the problem of unknown control gain and control direction is produced. To solve this problem, the Nussbaum-type function is introduced. Combined backstepping technique with FLSs, an adaptive approximation FT tracking control scheme is proposed. Finally, the developed control method ensures that all the closed-loop signals are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin. A simulation example is presented to illustrate the effectiveness of the developed control scheme.

Trajectory tracking for quadrotor UAV transporting cable-suspended payload in wind presence

In this paper, trajectory tracking for a quadrotor unmanned aerial vehicle (UAV) is considered in the presence of a cable-suspended payload and wind as unknown disturbances. It is assumed that the wind disturbance is slowly time varying and affects quadrotor position and orientation independently. Nonlinear robust strategies, such as backstepping and sliding mode control could be used for trajectory tracking; however, they fail to stabilize the system in the presence of payload or wind, or both together. We have proposed a combined backstepping and super-twisting integral sliding mode strategy to stabilize the system. Conventional sliding mode control suggests discontinuous control signals and suffers from the chattering phenomenon whereas its super-twisting integral version suggests continuous control signals, which makes it implementable and chattering free.

A combined backstepping and dynamic surface control to adaptive fuzzy state‐feedback control

SummaryThis paper studies an adaptive fuzzy dynamic surface control for a class of nonlinear systems with fuzzy dead zone, unmodeled dynamics, dynamical disturbances, and unknown control gain functions. The unknown system functions are approximated by the Takagi‐Sugeno–type fuzzy logic systems. There are 3 main features for the presented systematic design scheme. First, by adopting an integrated method, a novel adaptive fuzzy controller is constructed for the nonlinear system with fuzzy dead zone. Second, only 3 online learning parameters need to be tuned, which significantly reduces the computation burden. Third, the possible controller singularity problem in some of the existing adaptive control methods with feedback linearization techniques can be avoided. On the basis of the backstepping technique and dynamic surface control, all the signals of the closed‐loop system are guaranteed to be semiglobally uniformly ultimately bounded. Finally, 2 simulation examples are provided to illustrate the effectiveness of the proposed scheme.

Combined backstepping and HOSM control design for a class of nonlinear MIMO systems

Combined backstepping and HOSM control design for a class of nonlinear MIMO systems

Distributed adaptive controller for the output-synchronization of networked systems in semi-strict feedback form

In this paper, we investigate the output synchronization of networked SISO nonlinear systems that can be transformed into semi-strict feedback form. Due to parameter uncertainty, the agents have heterogeneous dynamics. Combined backstepping method together with graph theory, we construct an augmented Laplacian potential function for analysis and a distributed controller is designed recursively for each agent such that its output can be synchronized to its neighbors' outputs. The distributed controller of each agent has three parts: state feedback of itself, neighborhood information transmitted through the network and adaptive parameter updaters both for itself and its neighbors. Moreover, distributed tuning function is designed to minimize the order of the parameter updater. It is proved that when the undirected graph is connected, all agents’ outputs in the network can be synchronized, i.e., cooperative output synchronization of the network is realized. Simulation results are presented to verify the effectiveness of the proposed controllers.

A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems

In this paper, a robust adaptive tracking control problem is discussed for a general class of strict-feedback uncertain nonlinear systems. The systems may possess a wide class of uncertainties referred to as unstructured uncertainties, which are not linearly parameterized and do not have any prior knowledge of the bounding functions. The Takagi-Sugeno type fuzzy logic systems are used to approximate the uncertainties. A unified and systematic procedure is employed to derive two kinds of novel robust adaptive tracking controllers by use of the input-to-state stability (ISS) and by combining the backstepping technique and generalized small gain approach. One is the robust adaptive fuzzy tracking controller (RAFTC) for the system without input gain uncertainty. The other is the robust adaptive fuzzy sliding tracking controller (RAFSTC) for the system with input gain uncertainty. Both algorithms have two advantages, those are, semi-global uniform ultimate boundedness of adaptive control system in the presence of unstructured uncertainties and the adaptive mechanism with minimal learning parameterizations. Four application examples, including a pendulum system with motor, a one-link robot, a ship roll stabilization with actuator and a single-link manipulator with flexible joint, are used to demonstrate the effectiveness and performance of proposed schemes.

A combined backstepping and small-gain approach to adaptive output feedback control

In this brief article, a novel combined backstepping and small-gain approach is presented to the global adaptive output feedback control of a class of uncertain nonlinear systems with unmodeled dynamics. The use of small-gain techniques permits removal of a common restriction, i.e. that the nonlinearities in the system are only dependent on the measured output. The design procedure is divided into two parts. In the first part, based on a partial-state observer, integrator backstepping is used to design an adaptive output-feedback controller which ensures robustness with respect to unknown parameters and uncertain nonlinearities. In the second part, it is shown that the adaptive controller can be made robust against dynamic uncertainties by means of recent nonlinear small-gain results.

A robust control design for a class of uncertain non-linear systems featuring a second-order sliding mode

In this paper, the problem of the stabilization of uncertain non-linear systems expressible in the perturbed-chain-of-integrators form is considered. Under suitable assumptions, the control problem is solved via a combined backstepping/ variable structure control strategy that retains n − 1 steps of a backstepping-like procedure and associates with them a final step aimed at generating a second-order sliding regime on a suitably selected sliding manifold. As a result, the uncertainty terms turn out to be compensated for, thus guaranteeing satisfactory performances, which are compared, in the paper, with those of the original procedure. The proposed approach has also the advantage of a reduced computational load.