scholarly journals Adjustment mechanism with sliding mode for adaptive PD controller applied to unmanned fixed-wing MAV altitude

Author(s):  
Tadeo Espinoza ◽  
A. S ́aenz-Esqued ◽  
F. C ́ortes-Mart ́ınez

<p>This work presents an adjustment mechanism with the sliding modes technique to design a proportional derivative (PD) controller with adaptive gains. The objective and contribution are to design a robust adjustment mechanism in the presence of unknown and not modeled perturbations in the system; this perturbation can be considered wind gusts. The robust adjustment mechanism is designed with the MIT rule and the gradient method with the sliding mode theory. The adaptive PD obtained is applied to regulate unmanned fixed-wing miniature aerial vehicle (MAV’s) altitude.</p>

Author(s):  
Herman Castan˜eda Cuevas ◽  
Jesu´s de Leo´n Morales ◽  
Ernesto Olgui´n-Di´az

In this paper, a robust control algorithm, based on sliding modes techniques, designed for trajectory tracking is applied to a fixed-wing small Autonomous Aerial Vehicle (AAV). Based on a mathematical modeling, parameters identification, and aerodynamics of both the AAV fuselage and its mobile surfaces a full dynamical model is obtained, where the control is proven. However, for control design, simplified versions of the motion models are studied resulting in simplified independent controller for the roll, pitch and yaw trajectories. Due to the nature of such controller, time derivative of control variables are needed but not available. Numerical differentiators also based on sliding modes are used in order to estimate those derivatives. Simulation results are given to illustrate the performance of the proposed tracking controller under parametric and unmodeled dynamics.


Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 54
Author(s):  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim

This article proposes a novel adaptive super-twisting sliding mode control scheme with a time-delay estimation technique (ASTSMC-TDE) to control the yaw angle of a single ducted-fan unmanned aerial vehicle system. Such systems are highly nonlinear; hence, the proposed control scheme is a combination of several control schemes; super-twisting sliding mode, TDE technique to estimate the nonlinear factors of the system, and an adaptive sliding mode. The tracking error of the ASTSMC-TDE is guaranteed to be uniformly ultimately bounded using Lyapunov stability theory. Moreover, to enhance the versatility and the practical feasibility of the proposed control scheme, a comparison study between the proposed controller and a proportional-integral-derivative controller (PID) is conducted. The comparison is achieved through two different scenarios: a normal mode and an abnormal mode. Simulation and experimental tests are carried out to provide an in-depth investigation of the performance of the proposed ASTSMC-TDE control system.


Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 643 ◽  
Author(s):  
Juan Tan ◽  
Yonghua Fan ◽  
Pengpeng Yan ◽  
Chun Wang ◽  
Hao Feng

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
T. Osuna ◽  
O. E. Montano ◽  
Y. Orlov

TheL2-gain analysis is extended towards hybrid mechanical systems, operating under unilateral constraints and admitting both sliding modes and collision phenomena. Sufficient conditions for such a system to be internally asymptotically stable and to possessL2-gain less than ana priorigiven disturbance attenuation level are derived in terms of two independent inequalities which are imposed on continuous-time dynamics and on discrete disturbance factor that occurs at the collision time instants. The former inequality may be viewed as the Hamilton-Jacobi inequality for discontinuous vector fields, and it is separately specified beyond and along sliding modes, which occur in the system between collisions. Thus interpreted, the former inequality should impose the desired integral input-to-state stability (iISS) property on the Filippov dynamics between collisions whereas the latter inequality is invoked to ensure that the impact dynamics (when the state trajectory hits the unilateral constraint) are input-to-state stable (ISS). These inequalities, being coupled together, form the constructive procedure, effectiveness of which is supported by the numerical study made for an impacting double integrator, driven by a sliding mode controller. Desired disturbance attenuation level is shown to satisfactorily be achieved under external disturbances during the collision-free phase and in the presence of uncertainties in the transition phase.


Author(s):  
Seyyed Arash Haghpanah ◽  
Morteza Farrokhnia ◽  
Sajjad Taghvaei ◽  
Mohammad Eghtesad ◽  
Esmaeal Ghavanloo

Functional electrical stimulation (FES) is an effective method to induce muscle contraction and to improve movements in individuals with injured central nervous system. In order to develop the FES systems for an individual with gait impairment, an appropriate control strategy must be designed to accurate tracking performance. The goal of this study is to present a method for designing proportional-derivative (PD) and sliding mode controllers (SMC) for the FES applied to the musculoskeletal model of an ankle joint to track the desired movements obtained by experiments on two healthy individuals during the gait cycle. Simulation results of the developed controller on musculoskeletal model of the ankle joint illustrated that the SMC is able to track the desired movements more accurately than the PD controller and prevents oscillating patterns around the experimentally measured data. Therefore, the sliding mode as the nonlinear method is more robust in face to unmodeled dynamics and model errors and track the desired path smoothly. Also, the required control effort is smoother in SMC with respect to the PD controller because of the nonlinearity.


2013 ◽  
Vol 427-429 ◽  
pp. 1179-1182
Author(s):  
Sheng Bin Hu ◽  
Jin Yuan Xu ◽  
Xuan Wu ◽  
Chi Zhang ◽  
Yi Hao He

A fast terminal fuzzy sliding mode control scheme for the attitude of flapping wing micro aerial vehicle is proposed in this paper. Based on the feedback linearization technique, a fast terminal sliding mode controller is designed. To diminish the chattering in the control input, a fuzzy controller is designed to adjust the generalized gain of fast terminal fuzzy sliding mode controller according to fast terminal sliding mode surface. The stability of the control algorithm is verified by using Lyapunov theory. Simulation results show that the proposed control scheme is effective.


2018 ◽  
Vol 41 (5) ◽  
pp. 1243-1255 ◽  
Author(s):  
Baharnaz Barikbin ◽  
Ahmad Fakharian

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Taimoor ◽  
Xiao Lu ◽  
Hamid Maqsood ◽  
Chunyang Sheng

Purpose The objective of this research is to investigate various neural network (NN) observer techniques for sensors fault identification and diagnosis of nonlinear system in consideration of numerous faults, failures, uncertainties and disturbances. For the importunity of increasing the faults diagnosis and reconstruction preciseness, a new technique is used for modifying the weight parameters of NNs without enhancement of computational complexities. Design/methodology/approach Various techniques such as adaptive radial basis functions (ARBF), conventional radial basis functions, adaptive multi-layer perceptron, conventional multi-layer perceptron and extended state observer are presented. For increasing the fault detection preciseness, a new technique is used for updating the weight parameters of radial basis functions and multi-layer perceptron (MLP) without enhancement of computational complexities. Lyapunov stability theory and sliding-mode surface concepts are used for the weight-updating parameters. Based on the combination of these two concepts, the weight parameters of NNs are updated adaptively. The key purpose of utilization of adaptive weight is to enhance the detection of faults with high accuracy. Because of the online adaptation, the ARBF can detect various kinds of faults and failures such as simultaneous, incipient, intermittent and abrupt faults effectively. Results depict that the suggested algorithm (ARBF) demonstrates more confrontation to unknown disturbances, faults and system dynamics compared with other investigated techniques and techniques used in the literature. The proposed algorithms are investigated by the utilization of quadrotor unmanned aerial vehicle dynamics, which authenticate the efficiency of the suggested algorithm. Findings The proposed Lyapunov function theory and sliding-mode surface-based strategy are studied, which shows more efficiency to unknown faults, failures, uncertainties and disturbances compared with conventional approaches as well as techniques used in the literature. Practical implications For improvement of the system safety and for avoiding failure and damage, the rapid fault detection and isolation has a great significance; the proposed approaches in this research work guarantee the detection and reconstruction of unknown faults, which has a great significance for practical life. Originality/value In this research, two strategies such Lyapunov function theory and sliding-mode surface concept are used in combination for tuning the weight parameters of NNs adaptively. The main purpose of these strategies is the fault diagnosis and reconstruction with high accuracy in terms of shape as well as the magnitude of unknown faults. Results depict that the proposed strategy is more effective compared with techniques used in the literature.


2019 ◽  
pp. 20-66
Author(s):  
Heba Elkholy ◽  
Maki K. Habib

This chapter presents the detailed dynamic model of a Vertical Take-Off and Landing (VTOL) type Unmanned Aerial Vehicle (UAV) known as the quadrotor. The mathematical model is derived based on Newton Euler formalism. This is followed by the development of a simulation environment on which the developed model is verified. Four control algorithms are developed to control the quadrotor's degrees of freedom: a linear PID controller, Gain Scheduling-based PID controller, nonlinear Sliding Mode, and Backstepping controllers. The performances of these controllers are compared through the developed simulation environment in terms of their dynamic performance, stability, and the effect of possible disturbances.


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