Nonlinear Robust Adaptive Control Research Articles

Robust Adaptive Control Based on Incremental Nonlinear Dynamic Inversion for a Quadrotor in Presence of Partial Actuator Fault

This paper presents a novel nonlinear robust adaptive trajectory tracking control architecture for stabilizing and controlling a quadrotor in the presence of actuator partial faults. The proposed control strategy utilizes an Incremental Nonlinear Dynamic Inversion (INDI) algorithm as the baseline controller in the inner loop and augments a nonlinear model reference adaptive controller in the outer loop to ensure robustness against unmodeled faults. Additionally, a modified PID controller is introduced in the most outer-loop to track the desired path. The effects of actuator faults are modeled by considering sudden variations in motor thrust and torques. To enhance the control algorithm's robustness, a projection operator is employed in the robust adaptive structure. Comparative performance evaluations with a previous successful algorithm implemented on a quadrotor model demonstrate that the proposed controller achieves full controllability of the faulty quadrotor in pitch, roll, and yaw channels in the presence of actuator partial faults up to 50%.

Adaptive robust control of electromagnetic actuators with friction nonlinearity and uncertainty compensation

Friction nonlinearity and uncertainty are the main factors affecting the highly performance control of electromagnetic actuators. In this paper, a nonlinear adaptive robust control strategy is proposed of electromagnetic actuators with friction nonlinearity and uncertainty compensation. First, the dynamical model of the electromagnetic actuator is established considering nonlinearity and uncertainty. Then, an adaptive robust controller is designed based on the continuously differentiable friction model to ensure that the control input is continuously and bounded. In the design of the controller, the unfavorable effects of unknown parameters in the electromagnetic actuator are eliminated by constructing a parameter adaptive law. Meanwhile, in order to improve the tracking accuracy of the electromagnetic actuator, a nonlinear robust control law is designed to ensure the robustness of the controller. The stability analysis by Lyapunov function shows that the asymptotic tracking effect can be obtained when only parameter uncertainty exists in the closed-loop system of the electromagnetic actuator, and the consistent bounded stability can be ensured when the system also exists uncertain nonlinearity. Extensive comparative results verify the effectiveness of the proposed control method.

Nonlinear Robust Adaptive Control of Electro-hydrostatic Actuators With Continuous Friction Compensation

Nonlinear Robust Adaptive Control of Electro-hydrostatic Actuators With Continuous Friction Compensation

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

The introduction of a dynamic model in robot trajectory tracking control design can significantly improve its trajectory tracking accuracy, but there are many uncertainties in the robot dynamic model which can be dealt with through robust control and adaptive control. The prevailing robust control as well as adaptive control methods require real-time computation of robot dynamics, but the extreme complexity of the robot dynamics equations makes it difficult to apply these methods in real industrial systems. To this end, this article proposes a robust adaptive control method based on the desired trajectory, which uses the desired trajectory to compute most of the control terms offline, including the robot’s nominal dynamics and regression matrices, and substantially reduces the need for real-time computation of the feedback signals. The robust term modifies the perturbation of the inertial parameters of the links, the adaptive term learns the friction coefficients of the joints online, and an additional compensation term is designed to satisfy the Lyapunov stability condition of the system. Finally, taking a universal manipulator as the experimental platform, the control performances of different control methods are compared to show the feasibility of the controller and the effective reduction in real-time computational complexity.

Nonlinear Robust Adaptive Sliding Mode Control Strategies Involve a Fractional Ordered Approach to Reducing Dengue Vectors

This study presents an innovative approach by integrating adaptive sliding mode control strategies with fractional order modeling to address the challenge of reducing Aedes aegypti mosquito populations, the primary vector of Dengue - a widespread and debilitating disease. By employing the Atangana-Baleanu-Caputo fractional operator to model the dynamics of the mosquito population, we achieve a more precise representation of complex and non-linear behaviors. The motivation behind adopting the Adaptive Sliding Mode Control (ASMC) approach lies in the critical need to efficiently control Aedes aegypti mosquito populations, a key step in combating the prevalence of dengue. The ASMC method dynamically adjusts control parameters based on evolving conditions, enhancing its adaptability to the changing dynamics of mosquito populations.The Lyapunov stability theorem ensures the reliability of tracking convergence and control structure. Additionally, we implement the Toufik Atangana method to solve both state and adjoint fractional differential equations using the ABC derivative operator. This incorporation adds a novel dimension to the study, providing a comprehensive framework for addressing the intricate dynamics inherent in the Aedes aegypti mosquito population. To assess the effectiveness of the proposed strategy, a numerical performance index is introduced at the end of the abstract. This index justifies the controller’s efficacy by comparing it to other conventional controllers. The inclusion of this quantitative measure reinforces the significance of the proposed strategy in the context of dengue prevention and control efforts.

Robust adaptive control of underwater glider for bottom sitting-oriented soft landing

This paper deals with the formalization, design, theorization, and implementation of a robust adaptive nonlinear control scheme to solve the bottom sitting-oriented soft landing control problem for an underwater glider under model uncertainties, actuator dynamics, and external disturbances. First, uniformized motion equations are derived based on Lie derivatives for describing pitch angle and vertical velocity tracking control. Then, the robust adaptive control framework is enhanced by containing an anti-windup auxiliary system and a disturbance observer. The stability of the closed-loop control system based on Lyapunov theory is proven to guarantee the boundedness of the entire internal signals. Finally, multifarious experimental results are also conducted by a self-developed underwater glider to demonstrate the effectiveness of the proposed controller.

Nonlinear robust adaptive control for bidirectional stabilization system of all-electric tank with unknown actuator backlash compensation and disturbance estimation

Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of all-electric tank, it behaves more drastically in high maneuvering environments. In this work, the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved. By utilizing the smooth adaptive backlash inverse model, a nonlinear robust adaptive feedback control scheme is presented. The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term. Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation, which ensures the system stability. Meanwhile, the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality. Finally, Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash. Contrast co-simulations and experiments illustrate the advantages of the proposed approach.

Robust adaptive nonlinear control of plugin hybrid electric vehicles for vehicle to grid and grid to vehicle power flow with hybrid energy storage system

Plugin hybrid electric vehicles (PHEVs) can solve the concerns of toxic gases emissions from fossil fuel. The PHEV under consideration consists of an on-board smart charger and a hybrid energy storage system (HESS) composed of the battery as a primary power source and an ultracapacitor (UC) as a secondary power source conjoined with two DC–DC bidirectional buck-boost converters. The on-board charging unit comprises of an AC–DC boost rectifier and DC–DC buck converter. The entire system’s state model has been derived. An adaptive supertwisting sliding mode controller (AST-SMC) has been proposed for the unitary power factor correction at the grid side, tight voltage regulation of the charger and the DC bus, adaptation of time varying parameters and tracking of the currents involving the variation in the load profile. A genetic algorithm has been applied for optimizing the cost function of the controller gains. Key results refers reduction of chattering, adaptation of parametric variations, nonlinearities and external disturbances of the dynamical system. HESS results presents negligible convergence time and overshoots/undershoots even at the transients, and no steady state error. For the driving mode, the switching between dynamic and static behaviors and for parking mode, vehicle to grid (V2G) and grid to vehicle (G2V) operations have been proposed. In order to make nonlinear controller intelligent to achieve the V2G and G2V functionality, a state of charge based high-level controller has also been proposed. A standard Lyapunov stability criteria has been used to ensure asymptotic stability of the entire system. The proposed controller has been compared with sliding mode control (SMC) and finite time synergetic control (FTSC) by the simulation results using MATLAB/Simulink. Also, the hardware in loop setup has been used to validate the performance in real-time.

Nonlinear robust adaptive precision motion control of motor servo systems with unknown actuator backlash compensation

In this article, the problem of high precision motion control for motor servo systems with modeling uncertainties and unknown actuator backlash is addressed. The combination of synthesized adaptive laws and continuous nonlinear robust term handles parameter uncertainties and system disturbances. The adaptive technique updates the unknown parameters of actuator backlash in real time and the backlash inverse function eliminates the backlash effect. Meanwhile, the designed controller without knowing the range of the disturbance upper bound but automatically estimates through the adaptive law, which improves the engineering practicability. Finally, the theoretical analysis proves the perfect asymptotic stability of the presented controller even with unmodeled disturbances and unknown actuator backlash. Extensive comparative experiments reveal the superiority of the presented method.

LSTM‐based adaptive robust nonlinear controller design of a single‐axis hydraulic shaking table

AbstractThe shaking table has been used extensively in the structure test field to verify the structure's performance against various vibrations, for example earthquakes. In order to replicate the vibrations, which are measured by the acceleration signal, the model of the shaking table should be thoroughly constructed to design the controller. However, parametric uncertainty and strong nonlinearity, such as the nonlinear friction, make it an obstacle to obtaining an accurate model. A neural network‐based controller, specifically a long short‐term memory neural network‐based neural network controller, is designed in this paper to address this issue. The nonlinear systems are estimated by the neural network's universal approximation characteristics, and a long short‐term memory neural network is utilized to optimize the time‐series‐related errors. Furthermore, a robust sliding mode controller is utilized to compensate for the residual error of the neural network and other uncertainties. The semi‐global asymptotic stability of the controller is proved by Lyapunov analysis. Comparative experimental results indicate the superiority of the proposed controller.

Motion Control of a Hydraulic Manipulator with Adaptive Nonlinear Model Compensation and Comparative Experiments

Hydraulic manipulators play an irreplaceable role in many heavy-duty applications. Currently, there are stronger demands for the hydraulic manipulator to achieve high precision, as well as high force/power. However, due to the inherent nonlinearities of its high-order dynamics, the precision of the manipulator has been a common weakness compared with electrically driven ones. Thus, in this paper, a nonlinear adaptive robust control method for the hydraulic manipulator is proposed. To make the controller more applicable to practical engineering projects, this study tried to control each joint independently instead of directly based on the complicated multi-degree high-order dynamics, while guaranteeing the control precision by the adaptive nonlinear model compensation, as well as a robust feedback design. The closed-loop control performance was theoretically verified. Besides, several sets of comparative motion tracking experiments were conducted, and the proposed closed-loop system achieved high precision under different trajectories and postures.

Adaptive robust nonlinear control of spacecraft formation flying: a novel disturbance observer-based control approach

Adaptive robust nonlinear control of spacecraft formation flying: a novel disturbance observer-based control approach

Robust neural network‐based backstepping landing control of quadrotor on moving platform with stochastic noise

AbstractThis article introduces a novel nonlinear control approach for quadrotor landing on a moving ship. The dynamics of the relative position and attitude dynamics with uncertainties, unmodeled dynamics, external disturbances, and control input saturation is derived. Then, a novel robust adaptive constrained backstepping control law for the propeller and torques of the quadrotor is designed. To deal with uncertainties and un‐modeled dynamics, radial basis function is employed. The bounded‐in‐probability stability is used to alleviate the destructive influence of the stochastic Wiener process on the system positions and attitudes. Whereas the quadrotor is under‐actuated, a redundant control input technique, which affects the attitude commands, is presented. The actual control input saturation limits are turned into unknown saturation limits of the redundant control inputs. Also, since two phases for the landing problem are considered, a smooth switching mechanism between the control inputs is developed. Simulation results show the merits and applicability of the developed robust adaptive nonlinear controller.

Nonlinear Adaptive Robust Control of Valve-Controlled Symmetrical Cylinder System

A nonlinear adaptive robust control method based on a differentiable LuGre friction model is proposed for the problems of uncertain parameters, nonlinear friction and time-varying disturbances in valve-controlled symmetrical cylinder system. The proposed method can effectively compensate the uncertain nonlinear characteristics and external disturbances in the system by combining adaptive robust control with state and disturbance observations, as well as sliding mode differential technique. The global stability and boundedness of the proposed control method are proven by applying the Lyapunov theory. The simulation results show that this control method can deal with the problems of the uncertain nonlinearities and disturbances within the system. The proposed control method also presents excellent dynamic performance and robustness.

Disturbance-Rejection-Based Optimized Robust Adaptive Controllers for UAVs

Most applications for small unmanned aerial vehicles (sUAVs) have a critical need for appropriate position and attitude control in environments with extreme external dynamic disturbances such as wind gusts. Moreover, to maximize flight time, UAVs have to operate within strict constraints on payload and under computational efficiency. This article presents an optimized robust adaptive controller for a UAV in the presence of realistic wind gusts that are flying in an urban environment at an altitude lower than 400 ft. The position controller is based on two degree-of-freedom proportional-integral-derivative controller tuned with particle swarm optimization, while the attitude controll is based on a robust adaptive integral backstepping controller. By assuming the knowledge of the predetermined limits of the external and unstructured disruptions (for example, wind gusts) at low altitude, a guaranteed quality of transient and steady-state tracking performance were attained. The aerodynamics, wind gust model, and control modules are integrated into a six-degree-of-freedom UAV with a fully nonlinear robust adaptive controller. Optimal power is obtained for UAVs using the radial inflow model in the presence of wind gusts that are compared with the simplified model. Two case studies were performed systematically for two representative flight paths, namely, up-cruise-down and circular paths. The simulation results demonstrate the robustness and adaptive property of controllers against wind gusts. These results are useful for a variety of UAV applications, e.g. accurate trajectory tracking and autonomous waypoint navigation without loss of performance in the presence of wind disturbances under computational efficacy.

Energy-saving and accurate motion control of a hydraulic actuator with uncertain negative loads

Pump controlled hydraulic actuators are wildly used in the aerospace industry owing to the advantages of energy-saving and integrated configurations. Negative loads may occur to actuators due to external force loads or the inertial force when the actuator decelerates significantly. Uncertain negative load working conditions may cause cavitation, actuator vibration, and even instability to the motion control if the actuator is without sufficient meter-out damping. Various types of hydraulic configuration schemes have been proposed to deal with negative loads of hydraulic actuators. However, few of them can simultaneously achieve energy saving and high control accuracy. This study proposes an energy-saving and accurate motion tracking strategy for a hydraulic actuator with uncertain negative loads. The actuator’s motion is driven by a servomotor pump, which gives full play to the advantage of energy-saving. The meter-out pressure is controlled by proportional valves to provide the optimized meter-out damping. The nonlinear adaptive robust control law is designed, which guarantees the control stability and achieve high tracking accuracy. An integrated direct/indirect adaptation law obtains satisfactory parameter estimations and model compensation for asymptotic motion tracking. Comparative experiments under different working conditions were performed to validate the advantages of the proposed control strategy.

Nonlinear Adaptive Robust Precision Pointing Control of Tank Servo Systems

This paper focuses on the high performance pointing control of tank servo systems with parametric uncertainties and uncertain nonlinearities including nonlinear friction, backlash and structural flexibility. A comprehensive dynamic nonlinear mathematical model of the two-DOF tank servo system is established. Specifically, to accurately describe the nonlinear friction characteristics in actual systems, a continuous friction model is employed. Moreover, a hybrid nonlinear model combining structural flexibility and transmission backlash is constructed to characterize the nonlinear characteristics of the backlash and flexible coupling between the input and output shafts of the drive end for the tank servo system. By using the backstepping method, a nonlinear adaptive robust controller is presented. In the controller, the adaptive law is compounded to dispose of parametric uncertainties and a well-designed continuous nonlinear robust control law is developed for the purpose of coping with unmodeled disturbances. The closed-loop system stability analysis indicates that the presented controller achieves an asymptotic tracking performance with parametric uncertainties and ensures the robustness against unmodeled disturbances theoretically. The effectiveness of the proposed control strategy is verified by a large number of comparative simulation results.

Adaptive Backstepping Compensation of Drives with Sandwiched Deadzone Nonlinearity

In this paper, a nonlinear robust adaptive controller is proposed for gear transmission servo system (GTS) containing a sandwiched deadzone due to improper gear meshing. The controller is robust to dynamic uncertainties and can compensate the effect caused by the sandwiched nonlinearity which is separated from the control input through drive compliance. The proposed design methodology does not require an adaptive inverse deadzone function and does not require the knowledge of its parameter and only the knowledge of upper bounds is required.

Adaptive robust cross-coupling position synchronization control of a hydraulic press slider-leveling.

To achieve a high performance synchronized motion trajectory tracking of the hydraulic press slider-leveling electrohydraulic control system, an adaptive robust cross-coupling control strategy that incorporates the cross-coupling approach into adaptive robust control (ARC) architecture has been proposed. The primary objective of this study was describe that the nonlinear ARC controller together with a cross-coupling control (CCC) controller was integrated to solve the slider-leveling synchronization control system using four axes. A discontinuous projection-based ARC controller was constructed. A robust control method with dynamic compensation type fast adaptation was introduced to attenuate the effects of parameter estimation errors, unmodeled dynamics and disturbances, and improved the transient tracking performance of the system. The stability of the controller was proven by Lyapunov theory and the trajectory tracking error asymptotically convergences to zero. The simulation of a desired reference trajectory was included. The max tracking error of the proposed ARC controller of single axis was kept within-0.06 mm. The trajectory tracking error asymptotically converges to zero, which guaranteed the system would possess good transient behavior and confirmed the stability performance of the control system. The four axes synchronous errors of reference trajectory with cross-coupling controller indicated the maximum synchronization error of the proposed ARC + CCC controller between axis was within ±0.1 mm. The ARC together with a CCC controller for four hydraulic cylinders used parameter adaptation to obtain estimates of model parameters for reducing the extent of parametric uncertainties, and used a robust control law to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. This study result shows that the proposed cross-coupling synchronization control scheme, together with the ARC law, provides excellent synchronization motion performance in a control system with four axes.

Adaptive Robust Dynamic Surface Integral Sliding Mode Control for Quadrotor UAVs under Parametric Uncertainties and External Disturbances

A robust adaptive fuzzy nonlinear controller based on dynamic surface and integral sliding mode control strategy (ADSISMC) is proposed to realize trajectory tracking for a class of quadrotor UAVs. In this study, the composite factors including parametric uncertainties and external disturbances are added to controller design, which make it more realistic. The quadrotor model is divided into two subsystems of attitude and position that make the control design become feasible. The main contributions of the proposed ADSISMC strategy are as follows: (1) The combination of dynamic surface and integral sliding mode makes the system always in sliding stage by finding the appropriate initial position compared with the common sliding mode, and the complexity of explosion in backstepping method is eliminated. (2) By introducing the fuzzy system, the unknown functions and uncertainties can be approximated which significantly improves the robustness and the tracking performance. (3) The switching control strategy is utilized to compensate for the errors between estimated and ideal inputs; the tracking performance of the whole system has been significantly improved. The simulation results show the effectiveness of the proposed control method.