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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 paper is to develop some interesting results in the field of chaotic synchronization with a new finite-time controller to reduce the time of convergence.

This article proposes a finite-time controller for the synchronization of hyper(chaotic) systems in a given time. The chaotic systems are perturbed by the model uncertainties and external disturbances. The designed controller achieves finite-time synchronization convergence to the steady-state error without oscillation and elimination of the nonlinear terms from the closed-loop system. The finite-time synchronization convergence reduces the hacking duration and recovers the embedded message in chaotic signals within a given preassigned limited time. The free oscillation convergence keeps the energy consumption low and alleviates failure chances of the actuator. The proposed finite-time controller is a combination of linear and nonlinear parts. The linear part keeps the stability of the closed-loop, the nonlinear part increases the rate of convergence to the origin. A generalized form of analytical stability proof is derived for the synchronization of chaotic and hyper-chaotic systems. The simulation results provide the validation of the accomplish synchronization for the Lu chaotic and hyper-chaotic systems.

The designed controller not only reduces the time of convergence without oscillation of the trajectories which can run the system for a given time domain.

This work is originally written by the author.

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 paper aims to present a new concept based on a multi‐agent approach in the area of nonlinear model predictive control (MPC) for fast systems.

A contribution to decentralized implementation of MPC is made. The control of the nonlinear system subject to constraints is achieved via a set of actions taken from different agents. The actions are based on an analytical solution and a neural network is used to monitor the closed system using a supervisory loop concept.

The high online computational need to solve an optimal control actions in nonlinear MPC, which results in a non‐convex optimization, is compared with the new proposed concept. Simulation results show that this approach has very remarkable performances in time computing and target arrival.

In practice, each MPC problem of the individual agent in multi‐agent MPC can run in parallel at the same time, instead of in serial, one agent after another. A parallel processor can be useful for real time implementation. However, it is estimated that how much time can be gained by performing the computations in parallel instead of in serial.

The proposed concept discussed in the paper has the potential to be applied to systems with rapid dynamics.

The multi‐agent MPC compares favorably with respect to a numerical optimization routine and also offers a solution for non‐convex optimization problems in single‐input single‐output systems.

The purpose of this paper is to develop a novel wearable rehabilitation robotic hand driven by Pneumatic Muscle‐Torsion Spring (PM‐TS) for finger therapy. PM has complex nonlinear dynamics, which makes PM modelling difficult. To realize high‐accurate tracking for the robotic hand, an Echo State Network (ESN)‐based PID adaptive controller is proposed, even though the plant model is unknown.

To drive a single joint of rehabilitation robotic hand, the paper proposes a new PM‐TS actuator comprising a Pneumatic Muscle (PM) and a Torsion Spring (TS). Based on the novel actuator, a wearable robotic hand is designed. By employing the model‐free approximation capability of ESN, the RLSESN based PID adaptive controller is presented for improving the trajectory tracking performance of the rehabilitation robotic hand. An ESN together with Recursive Least Square (RLS) is called a RLSESN, where the ESN output weight matrix is updated by the online RLS learning algorithm.

Practical experiments demonstrate the validity of the PM‐TS actuator and indicate that the performance of the RLSESN based PID adaptive controller is better than that of the conventional PID controller. In addition, they also verify the effectiveness of the proposed rehabilitation robotic hand.

A new PM‐TS actuator configuration that uses a PM and a torsion spring for bi‐directional movement of joint is presented. By utilizing the new PM‐TS actuator, a novel wearable rehabilitation robotic hand for finger therapy is designed. Based on the unknown plant model, the RLSESN_PID controller is proposed to attain satisfactory performance.

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well.

A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy.

This is a new innovation for multi-robot formation control method to improve assembly automation.

Omnidirectional mobile robots with a special type of wheel structure can realize flexible motion with all three degrees of freedom in a plane. But the driving method brings large disturbance, which affects motion accuracy and stability. This study aims to improve the motion control accuracy of the omnidirectional mobile platform with MY3 wheels (MY3-OMR), a new fuzzy active disturbance rejection control (FADRC) method with adaptivity is proposed.

Based on the basic mechanical structure and drive characteristics of MY3-OMR, the dynamics model of the system is established. The linear active disturbance rejection control (LADRC) system is designed to reduce the interference of nonlinear factors in this dynamics model. A fuzzy controller is introduced to realize the online adjustment of the parameters of the LADRC, which further improves the anti-disturbance performance of the system.

The control method proposed in this paper is compared and analyzed with other methods by simulation and experiment. Results show that the proposed method has better tracking and robustness, which effectively improves the control accuracy of trajectory tracking of MY3-OMR.

A FADRC method with adaptivity is proposed by combining fuzzy control and LADRC. The motion accuracy and anti-interference ability of the MY3-OMR are improved by this control method, which lays a foundation for the subsequent application of MY3-OMR.

The purpose of the paper is to present modeling and control of a nonlinear mechatronic system. To solve the control problem, the modified state-dependent Riccati equation (SDRE) method is applied. The control problem is designed and analyzed using the nonlinear feedback gain strategy for the infinite time horizon problem.

As a new contribution, this paper deals with state-dependent parametrization as an effective modeling of the mechatronic system and shows how to modify the classical form of the SDRE method to reduce computational effort during feedback gain computation. The numerical example compares described methods and confirms usefulness of the proposed technique.

The proposed control technique can ensure optimal dynamic response, reducing computational effort during control law computation. The effectiveness of the proposed control strategy is verified via numerical simulation.

The authors introduced an innovative approach to the well-known SDRE control methodology and settled their research in the newest literature coverage for this issue.

The purpose of this paper is to present an original design procedure for a flight control system.

An optimization process, based on a genetic algorithm (GA), is used to meet the frequency domain handling qualities requirements in the longitudinal plane for an unconventional platform characterized by nonlinear aerodynamics. The parameters are implemented in the search process as fitness functions related to the expected magnitude of bandwidth and delay for an existing micro aerial vehicle. The bandwidth and the delay of the longitudinal short‐term attitude response are estimated before and after the inclusion of the flight control system in the simulation model, and the parameters are compared with the expected handling qualities levels. A qualitative analysis of handling qualities levels is also performed by implementing the augmented aircraft in a simulator with a realistic visual environment.

The results show that an optimal search process based on a GA can implement the handling qualities requirements with a computational procedure that is straightforward.

Even if the requisites for bandwidth and delay implemented in the search process are general in use as no specific aircraft response type is taken as a reference for the estimation of handling qualities requirements, only future experimental work will provide insight for the definition of specific Level 1 boundaries for micro aerial vehicles in remotely piloted flight.

The virtual environment is useful to test remote piloting with unconventional onboard visual cues. This is important in applications in which technical limitations may preclude complete real time data link during flight tests in the first development phase of the vehicle.

This paper aims to address a new iterative tuning method of PID control for robot manipulators.

This tuning method uses several properties of the robot control, such as any PD control can stabilize a robot in regulation case, the closed-loop system of PID control can be approximated by a linear system, the control torque to the robot manipulator is linearly independent of the robot dynamic.

Compared with the other PID tuning methods, this novel method is simple, systematic, and stable. The transient properties of this PID control are better than the other normal PID controllers.

In this paper, a new systematic tuning method for PID control is proposed. The paper applies this method on an upper limb exoskeleton, and real experiment results give validation of our PID tuning method.