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This paper aims to propose output feedback-based control algorithms for the flight control system of a scaled, un-crewed helicopter in its hover flight mode.

The proposed control schemes are based on H_∞ control and composite nonlinear control. The gains of the output feedback controllers are obtained as the solution of a set of linear matrix inequalities (LMIs).

In the proposed schemes, the finite-time convergence of system states to trim condition is achieved with minimum deviation from the steady-state. As the proposed composite nonlinear output feedback design improves the transient response, it is well suited for a scaled helicopter flight. The use of measured output vector instead of the state vector or its estimate for feedback provides a simple control structure and eliminates the need for an observer in real-time application. The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints.

The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints. They also have significance in applications where the number of measurement quantities needs to be minimized such as in a fully functional rotor-craft unmanned aerial vehicle.

The developed output feedback control algorithms can be used in small-scale helicopters for numerous civilian and military applications.

This work addresses the LMI-based formulation and solution of an output feedback controller for a hovering un-crewed helicopter. The stability and robustness of the closed-loop system are proved mathematically and the performance of the proposed schemes is compared with an existing strategy via simulation studies.

The purpose of this research paper is to design a disturbance observer-based control based on the robust model reference adaptive backstepping sliding-mode control for attitude quadrotor model subject to uncertainties and disturbances.

To estimate and reject the disturbance, a disturbance observer is designed for the exogenous disturbances with perturbation while a control criterion is developed for the tracking of desired output. To achieve the control performance, backstepping and sliding-mode control techniques are patched together to obtain robust chattering-free controller. Furthermore, a model reference adaptive control criterion is also combined with the design of robust control for the estimation and rejection of uncertainties and unmodeled dynamics of the attitude quadrotor.

The findings of this research work includes the design of a disturbance observer-based control for uncertain attitude quadrotor system with the ability of achieving tracking control objective in the presence of nonlinear exogenous disturbance with and without perturbation.

In practice, the quadrotor flight is opposed by different kinds of the disturbances. In addition, being an underactuated system, it is difficult to obtain an accurate mathematical model of quadrotor for the control design. Thus, a quadrotor model with uncertainties and disturbances is inevitable. Hence, it is necessary to design a control system with the ability to achieve the control objectives in the presence of uncertainties and disturbances.

Designing the control methods for quadrotor control without uncertainties and disturbances is a common practice. However, investigating the uncertain quadrotor plant in the presence of nonlinear disturbances is rarely taken into consideration for the control design. Hence, this paper presents a control algorithm to address the issues of the uncertainties and disturbances as well as investigate a control algorithm to achieve tracking performance.

The purpose of this paper, is to solve the problem of finite-time fault-tolerant attitude synchronization and tracking control of multiple rigid bodies in presence of model uncertainty, external disturbances, actuator faults and saturation. It is assumed that the rigid bodies in the formation may encounter loss of effectiveness and/or bias actuator faults.

For the purpose, adaptive terminal sliding mode control and neural network structure are used, and a new sliding surface is proposed to guarantee known finite-time convergence not only at the reaching phase but also on the sliding surface. The sliding surface is then modified using a proposed auxiliary system to maintain stability under actuator saturation.

Assuming that the communication topology between the rigid bodies is governed by an undirected connected graph and the upper bounds on the actuators’ faults, estimation error of model uncertainty and external disturbance are unknown, not only the attitudes of the rigid bodies in the formation are synchronized but also they track the time-varying attitude of a virtual leader. Using Lyapunov stability approach, finite-time stability of the proposed control algorithms demonstrated on the sliding phase as well as the reaching phase. The effectiveness of the proposed algorithm is also validated by simulation.

The proposed controller has the advantage that the need for any fault detection and diagnosis mechanism and the upper bounds information on estimation error and external disturbance is eliminated.

The purpose of this paper is to present the radial basis function (RBF) networks‐based adaptive robust control for an omni‐directional wheeled mobile manipulator in the presence of uncertainties and disturbances.

First, a dynamic model is obtained based on the practical omni‐directional wheeled mobile manipulator system. Second, the RBF neural network is used to identify the unstructured system dynamics directly due to its ability to approximate a nonlinear continuous function to arbitrary accuracy. Using the learning ability of neural networks, RBFNARC can co‐ordinately control the omni‐directional mobile platform and the mounted manipulator with different dynamics efficiently. The implementation of the control algorithm is dependent on the sliding mode control.

Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

In this paper, an adaptive robust control scheme using neural networks combined with sliding mode control is proposed for crawler‐type mobile manipulators in the presence of uncertainties and disturbances. RBF neural networks approximate the system dynamics directly and overcome the structured uncertainty by learning. Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

This paper aims to propose a multi-agent approach to adaptive control of fixed-wing unmanned aerial vehicles (UAVs) tracking a moving ground target. The approach implies that the UAVs in a single group must maintain preset phase shift angles while rotating around the target so as to evaluate the target’s movement more accurately. Thus, the controls should ensure that the UAV swarm follows a moving circular path whose center is the target while also attaining and maintaining a circular formation of a specific geometric shape; and the formation control system is capable of self-tuning because the UAV dynamics is uncertain.

This paper considers two interaction architectures: an open-chain where each UAV only interacts with its neighbors; and a cooperative leader, where the leading UAV is involved in attaining the formation. The cooperative controllers are self-tuned by fuzzy model reference adaptive control (MRAC).

Using open-chain decentralized architecture allows to have an unlimited number of aircraft in a formation, which is in line with the swarm behavior concept. The approach was tested for efficiency and performance in various scenarios using complete nonlinear flying-wing UAV models equipped with configured standard autopilot models.

Assume the target follows a rectilinear trajectory at a constant speed. The speed is supposed to be known in advance. Another assumption is that the weather is windless.

In contrast to known studies, this one uses Lyapunov guidance vector fields that are direction- and magnitude-nonuniform. The overall cooperative controller structure is based on a decentralized and centralized consensus.

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.

Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.

The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.

Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.

In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.

The purpose of this paper is to propose a novel event-triggered aperiodic intermittent sliding-mode control (ETAI-SMC) algorithm for master–slave bilateral teleoperation robotic systems to further save communication resources while maintaining synchronization precision.

By using the Lyapunov theory, a new event-triggered aperiodic intermittent sliding-mode controller is designed to synchronize master–slave robots in a discontinuous method. Unlike traditional periodic time-triggered continuous control strategy, a new ETAI condition is discussed for less communication pressure. Then, the exponential reaching law is adopted to accelerate sliding-mode variables convergence, which has a significant effect on synchronization performance. In addition, the authors use quantizers to make their algorithm have obvious progress in saving communication resources.

The proposed control algorithm performance is validated by an experiment developed on a practical bilateral teleoperation system with two PHANToM Omni robotic devices. As a result, the synchronization error is limited within a small range and the control frequency is evidently reduced. Compared with a conventional control algorithm, the experimental results illustrate that the proposed control algorithm is more sensitive to system states changes and it can further save communication resources while guaranteeing the system synchronization accuracy, which is more practical for real bilateral teleoperation robotic systems.

A novel ETAI-SMC for bilateral teleoperation robotic systems is proposed to find a balance between reducing the control frequency and synchronization control precision. Combining the traditional sliding-mode control algorithm with the periodic intermittent control strategy and the event-triggered control strategy has produced obvious effect on our control performance. The proposed ETAI-SMC algorithm helps the controller be more sensitive to system states changes, which makes it possible to achieve precise control with lower control frequency. Moreover, we design an environment contact force feedback algorithm for operators to improve the perception of the slave robot working environment. In addition, quantizers and the exponential convergence law are adopted to help the proposed algorithm perform better in saving communication resources and improving synchronization precision.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

The purpose of this paper is to study the nonlinear forced vibration response of delaminated composite shells in hygrothermal environments.

Finite element method using an eight‐noded C⁰ continuity, isoparametric quadrilateral element is employed. The theoretical formulations are based on the first‐order shear deformation theory and von Kármán type nonlinear kinematics. For modeling the delamination, multipoint constraint algorithm is incorporated in the finite element code.

The paper finds that the effect of presence of delaminations on the nonlinear transient response of composite shells is dependent not only on the size, but also on the location of the delaminations and the hygrothermal environments.

The present study is limited to cylindrical and spherical shells having rectangular planform containing single delamination. Studies on different shell forms having non‐rectangular planforms containing multiple delaminations can be taken up for future research.

The value in this paper lies in that nonlinear transient response of delaminated shells in hygrothermal environments is studied for the first time. It will assist researchers of nonlinear dynamic behavior of elastic systems.

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.

The IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.

The composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.

The proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.

The proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.

Based on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.