Adaptive backstepping sliding mode control design for vibration suppression of earth-quaked building supported by magneto-rheological damper

In this study, the design of adaptive backstepping sliding mode control (ABSMC) has been developed for vibration suppression of earth-quaked building supported by magneto-rheological (MR) damper. The control and adaptive laws developed based on ABSMC methodology has been established according to stability analysis based on Lyupunov theorem. A Single degree of freedom (SDOF) building system has been considered and the earthquake acceleration data used in performance analysis of the proposed controller is based on El Centro Imperial Valley Earthquake. The ABSMC has been compared to classical sliding mode control in terms of vibration suppression in the controlled system subjected to earthquake. The performance of proposed controller has been assessed via computer simulation, which showed its effectiveness to stabilize the building against earthquake vibration and the boundness of estimated stiffness and viscosity coefficients.

Sliding Mode Fault Tolerant Control for a Quadrotor with Varying Load and Actuator Fault

In this paper, an adaptive sliding mode fault-tolerant control scheme based on prescribed performance control and neural networks is developed for an Unmanned Aerial Vehicle (UAV) quadrotor carrying a load to deal with actuator faults. First, a nonsingular fast terminal sliding mode (NFTSM) control strategy is presented. In virtue of the proposed strategy, fast convergence and high robustness can be guaranteed without stimulating chattering. Secondly, to obtain correct fault magnitudes and compensate the failures actively, a radial basis function neural network-based fault estimation scheme is proposed. By combining the proposed fault estimation strategy and the NFTSM controller, an active fault-tolerant control algorithm is established. Then, the uncertainties caused by load variation are explicitly considered and compensated by the presented adaptive laws. Moreover, by synthesizing the proposed sliding mode control and prescribed performance control (PPC), an output error transformation is defined to deal with state constraints and provide better tracking performance. From the Lyapunov stability analysis, the overall system is proven to be uniformly asymptotically stable. Finally, numerical simulation based on a quadrotor helicopter is carried out to validate the effectiveness and superiority of the proposed algorithm.

An observer-based output tracking controller for electrically driven cooperative multiple manipulators with adaptive Bernstein-type approximator

Thisarticle presents an observer-based output tracking control method for electrically actuated cooperative multiple manipulators using Bernstein-type operators as a universal approximator. This efficient mathematical tool represents lumped uncertainty, including external perturbations and unmodeled dynamics. Then, adaptive laws are derived through the stability analysis to tune the polynomial coefficients. It is confirmed that all the position and force tracking errors are uniformly ultimately bounded using the Lyapunov stability theorem. The theoretical achievements are validated by applying the proposed observer-based controller to a cooperative robotic system comprised of two manipulators transporting a rigid object. The outcomes of the introduced method are also compared to RBFNN, which is a powerful state-of-the-art approximator. The results demonstrate the efficacy of the introduced adaptive control approach in controlling the system even in the presence of disturbances and uncertainties.

BLSTM-Based Adaptive Finite-Time Output-Constrained Control for a Class of AUSs with Dynamic Disturbances and Actuator Faults

In this paper, a BLSTM-based adaptive finite-time control structure has been constructed for a class of aerospace unmanned systems (AUSs). Firstly, a novel neural network structure possessing both the time memory characteristics and high learning speed, broad long short-term memory (BLSTM) network, has been constructed. Secondly, several nonlinear functions are utilized to transform the tracking errors into a novel state vector to guarantee the output constraints of the AUSs. Thirdly, the fractional-order control law and the corresponding adaptive laws are designed, and as a result, the adaptive finite-time control scheme has been formed. Moreover, to handle the uncertainties and the faulty elevator outputs, an inequality of the multivariable systems is utilized. Consequently, by fusing the output of the BLSTM, the transformation of the tracking errors, and the adaptive finite-time control law, a novel BLSTM-based intelligent adaptive finite-time control structure has been established for the AUSs under output constraints. The simulation results show that the proposed BLSTM-based adaptive control algorithm can achieve favorable control results for the AUSs with multiple uncertainties.

Demagnetization Fault Diagnosis of Permanent Magnet Synchronous Motor with Inductance Disturbance

To address the problem of demagnetization fault diagnosis of permanent magnet synchronous motor (PMSM) under inductance change, a demagnetization fault detection method based on an adaptive observer is proposed. First, the mathematical model of the demagnetization fault of PMSM in a synchronous rotating coordinate system is established, and the inductance disturbance is analyzed separately. Then, considering the different characteristics of the flux linkage fault and inductance disturbance, a new adaptive observer is proposed. Two adaptive laws are designed to ensure the accuracy of fault diagnosis and to eliminate the influence of inductance disturbance, thus achieving the robust diagnosis of demagnetization fault.

Integrated, Multi-Approach, Adaptive Control of Two-Mass Drive with Nonlinear Damping and Stiffness

In numerous electric drive applications, the mechanical phenomena in the velocity or position control loop determine real difficulties and challenges for the control system. So-called two-mass drive systems with a flexible shaft are the most important example of this situation. The problem becomes even more difficult if the characteristics of torque transmission along the shaft are nonlinear, nonlinear friction is present, and the plant parameters are unknown, as it happens in numerous robotic systems. A novel adaptive controller is derived for such a system. The recurrent design procedure is based on proper modifications of the adaptive backstepping scheme, including non-strict-feedback plant application, tuning functions to exclude controller overparameterization, robust adaptive laws, proper means to avoid controller complexity explosion, and a nonlinear PI controller in the initial loop to minimize quasi-steady-state tracking error. The closed-loop system uniform ultimate boundedness is proven using Lyapunov techniques and the design and tuning procedures are described. The attractive features of the obtained drive, including the robustness against the violation of assumptions, are presented using several examples.

Switched Fractional Order Model Reference Adaptive Control for an Automatic Voltage Regulator

This paper presents the design and implementation of a Switched Fractional Order Model Reference Adaptive Controller (SFOMRAC) for an Automatic Voltage Regulator (AVR). The fractional orders, adaptive gains and switching times of the controller adaptive laws are tuned offline, using Particle Swarm Optimization (PSO). The functional to be optimized contains not only parameters of the AVR response but also the control energy. The obtained controllers are compared to non switched Integer Order Model Reference Adaptive Controller (IOMRAC) and non switched Fractional Order Model Reference Adaptive Controller (FOMRAC) proposed previously for this process, showing that the SFOMRAC can improve both, the system response and the control energy used.

Fixed-Time Disturbance Observer-Based Adaptive Finite-Time Guidance Law Design considering Impact Angle Constraint and Autopilot Dynamics

This paper aims to establish an effective guidance law to accomplish the interception guidance mission for a missile intercepting a target with impact angle constraint and autopilot dynamics. To achieve this purpose, a fixed-time disturbance observer-based adaptive finite-time guidance law is presented. First, a fixed-time disturbance observer (FTDO) is designed to guarantee the fast estimation of the lumped disturbance caused by the target maneuver. Then, the FTDO-based adaptive integral sliding mode backstepping (AISMB) guidance law is constructed for the interception guidance problem. Besides, several adaptive laws are established to estimate the derivative of virtual control inputs, making the “differential explosion problem” of conventional backstepping get avoided. The finite-time convergence characteristic of the closed-loop system is analyzed by utilizing the Lyapunov stability theory. Finally, the simulation examples are conducted to demonstrate the effectiveness of the proposed composite guidance law.

Robust Model Reference Adaptive Control for Tail-Sitter VTOL Aircraft

This study presents a control design of roll motion for a vertical take-off and landing unmanned air vehicle (VTOL-UAV) design based on the Model Reference Adaptive Control (MRAC) scheme in the hovering flight phase. The adaptive laws are developed for the UAV system under nonparametric uncertainty (gust and wind disturbance). Lyapunov-based stability analysis of the adaptive controlled UAV system under roll motion has been conducted and the adaptive laws have been accordingly developed. The Uniform Ultimate Boundness (UUB) of tracking error has been proven and the stability analysis showed that the incorporation of dead-zone modification in adaptive laws could guarantee the uniform boundness of all signals. The computer simulation has been conducted based on a proposed controller for tracking control of the roll motion. The results show that the drift, which appears in estimated gain behaviors due to the application of gust and wind disturbance, could be stopped by introducing dead-zone modification in adaptive laws, which leads to better robustness characteristics of the adaptive controller.