Nonlinear Actuator Research Articles

Adaptive hierarchical optimization control for electrohydraulic suspension with resistor-capacitor operator

The controller design for integrated electrohydraulic suspension with leaf spring is a complicated and challenging task, aiming to achieve optimal dynamic performance for heavy vehicles. Considering the hysteresis property of leaf spring, parameter uncertainties and nonlinearity, a novel hierarchical optimization control strategy including upper and bottom controllers is proposed to effectively suppress the vertical vibration of vehicle body. To describe the hysteresis property of leaf spring, a novel resistor-capacitor operator hysteresis model is identified by experiment and optimized by genetic algorithm. Based on hysteresis model, the filter adaptive backstepping control with sprung mass uncertainty is designed as upper controller to generate the desired active force for electrohydraulic actuator. Then, the projection adaptive fuzzy sliding mode control is designed as bottom controller for nonlinear actuator with time-varying fluid parameter to accurately track the required target force. Additionally, a stratified sampling algorithm is investigated to optimize the parameters of hierarchical control strategy for addressing multi-objective optimization issue of electrohydraulic suspension with leaf spring. Finally, the results show that the proposed method has better robustness and effectiveness, and it can ensure ride comfort, safety and optimal performance.

Optimal adaptive fuzzy fault-tolerant control applied on a quadrotor attitude stabilization based on particle swarm optimization

This article discusses the problem of stabilizing the attitude control of a quadrotor system, which is subject to uncertainty, external disturbances, and sensor and actuator faults. To address these challenges, the control stage employs universal approximators, such as fuzzy systems, which estimate the system’s uncertainties and eliminate nonaffine nonlinear actuator faults. In addition, the particle swarm optimization technique is used to adjust the adaptive parameters and fuzzy initial values. The robust control term is carefully designed to handle approximation errors, time-varying sensors, and external disturbances. To solve the issue of the unavoidable algebraic loop during the actuator approximation phase, a Butterworth low-pass filter is integrated. This approach automatically deals with external disturbances, and no further approximation is necessary. Furthermore, the controller can be reconfigured online to enable fast-fault compensation without requiring a fault detection or isolation unit. To prove the global stability and boundedness of all signals in the closed-loop system, Lyapunov theory is used.

Adaptive fuzzy fault‐tolerant control for cooperative output regulation with unknown nonlinear disturbances and actuator faults

AbstractThe cooperative output regulation problem with actuator faults and unknown nonlinear disturbances is a challenging research area in multi‐agent systems. This paper proposes an adaptive fuzzy fault‐tolerant controller to address this problem by employing a fuzzy logic system for approximating the unknown nonlinear disturbances. The internal model principle is utilized to transform the cooperative output regulation problem into a stability problem of an auxiliary system, with the aim of compensating for actuator failures in the system. By incorporating fuzzy logic system, the adaptive controller is able to approximate and compensate for the unknown nonlinear disturbances. Extensive simulations are conducted to validate the robustness and performance of the proposed method. The adaptive controller effectively handles actuator faults and achieves output regulation with unknown nonlinear disturbances.

Active flutter suppression of nonlinear fin-actuator system via inverse system and immersion and invariance method

Structural nonlinearities such as freeplay will affect the stability and even flight safety of the fin-actuator system. There is a lack of a practical method for designing Active Flutter Suppression (AFS) control laws for nonlinear fin-actuator systems. A design method for the AFS controller of the nonlinear all-movable fin-electromechanical actuator system is established by combining the inverse system and the Immersion and Invariance (I&I) theory. First, the composite control law combining the inverse system principle and internal model control is used to offset the nonlinearity and dynamics of the actuator, so that its driving torque can follow the ideal signal. Then, the ideal torque of the actuator is designed employing the I&I theory. The unfavorable oscillation of the fin is suppressed by making the output torque of the actuator track the ideal signal. The simulation results reveal that the proposed AFS method can increase the flutter speed of the nonlinear fin-actuator system with freeplay, and a set of controller parameters is also applicable for wider freeplay within a certain range. The power required for the actuator does not exceed the power that can be provided by the commonly used aviation actuator. This method can also resist a certain level of noise and external disturbance.

Application of Modeling and Control Approaches of Piezoelectric Actuators: A Review

Piezoelectric actuators find extensive application in delivering precision motion in the micrometer to nanometer range. The advantages of a broader range of motion, rapid response, higher stiffness, and large actuation force from piezoelectric actuators make them suitable for precision positioning applications. However, the inherent nonlinearity in the piezoelectric actuators under dynamic working conditions severely affects the accuracy of the generated motion. The nonlinearity in the piezoelectric actuators arises from hysteresis, creep, and vibration, which affect the performance of the piezoelectric actuator. Thus, there is a need for appropriate modeling and control approaches for piezoelectric actuators, which can model the nonlinearity phenomenon and provide adequate compensation to achieve higher motion accuracy. The present review covers different methods adopted for overcoming the nonlinearity issues in piezoelectric actuators. This review highlights the charge-based and voltage-based control methods that drive the piezoelectric actuators. The survey also includes different modeling approaches for the creep and hysteresis phenomenon of the piezoelectric actuators. In addition, the present review also highlights different control strategies and their applications in various types of piezoelectric actuators. An attempt is also made to compare the piezoelectric actuator’s different modeling and control approaches and highlight prospects.

Influence of optical property contrast on the critical distribution of electrostatic torques in double-beam torsional Casimir actuators: Non-linear actuation toward chaotic motion.

Here, we discuss how to achieve the stable actuation of a double beam torsional micro-actuator over the largest possible displacement of the moving component under the influence of Casimir and electrostatic torques, when the rotating component is constructed from different materials. The main part of this study is devoted to finding the optimal distribution of the electrostatic torque between the left and right sides of the micro-actuator to reach the maximum stable operation of the device. The latter is manifested by switching from homoclinic to heteroclinic orbits in the phase portraits. Indeed, the bifurcation curves and the phase portraits have been employed to show the sensitivity of the critical distribution of the electrostatic torque, beyond which the device does show stable performance, on the contrast of the optical properties of the moving component and the applied voltage in a conservative autonomous system. Moreover, for driven systems, the Melnikov function approach and the Poincaré portraits are used to study the presence of chaotic motion, which eventually leads to stiction. It is shown that the application of the optimal distribution of the electrostatic torque can significantly decrease the possibility of chaotic motion, and at this optimal level, the threshold curves reveal less difference between systems with different optical contrast.

Quadratic Programming for Continuous Control of Safety-Critical Multiagent Systems Under Uncertainty

This paper studies the control problem for safety-critical multi-agent systems based on quadratic programming (QP). Each controlled agent is modeled as a cascade connection of an integrator and an uncertain nonlinear actuation system. In particular, the integrator represents the position-velocity relation, and the actuation system describes the dynamic response of the actual velocity to the velocity reference signal. The notion of input-to-output stability (IOS) is employed to characterize the essential velocity-tracking capability of the actuation system. The standard QP algorithms for collision avoidance may be infeasible due to uncertain actuator dynamics. Even if feasible, the solutions may be non-Lipschitz because of possible violation of the full rank condition of the active constraints. Also, the interaction between the controlled integrator and the uncertain actuator dynamics may lead to significant robustness issues. Based on the current development of nonlinear control theory and numerical optimization methods, this paper first contributes a new feasible-set reshaping technique and a refined QP algorithm for feasibility, robustness, and local Lipschitz continuity. Then, we present a nonlinear small-gain analysis to handle the inherent interaction for guaranteed safety of the closed-loop multi-agent system. The proposed method is illustrated by numerical simulation and a physical experiment.

Input–output finite-time stabilisation for periodic piecewise polynomial systems with nonlinear actuator faults: an observer-based approach

This paper is concerned with the input–output finite-time (IO-FT) stabilisation problem for a class of continuous-time periodic piecewise polynomial systems (PPPSs) with immeasurable states and external disturbances via state estimation-based robust reliable controller. Firstly, to reflect the actuality, a parameter uncertainty that exhibits the random nature and the actuator faults with nonlinear character are considered in the addressed PPPSs and the control scheme, respectively. In detail, the randomness of uncertain parameters is portrayed by the stochastic variable and it is presumed to pursue the Bernoulli distributions. Secondly, to estimate the immeasurable states of PPPSs, a periodic piecewise polynomial observer is designed depending on the output of PPPSs. The main intent of this article is to devise a state estimation-based robust reliable controller to ascertain the IO-FT stabilisation of the PPPSs. Moreover, by bridging the Lyapunov stability theory, linear matrix inequality technique and IO-FT stability theory, the required IO-FT stabilisation conditions in the frame of linear matrix inequality are procured for the system under consideration. Eventually, simulation results of the addressed PPPSs are shown in line with the proposed analytical findings, revealing the competence, inherent capability and utility of the devised control protocol.

Anti-disturbance control for HVs system subject to nonlinear actuator characteristics with extended state observer

This paper proposes a radial basis function neural network and the actuator fault extended state observer based fast non-terminal sliding mode fault-tolerant control scheme for hypersonic vehicles (HVs) system. The proposed scheme can cope with actuator faults, actuator saturation, parameter uncertainties, and external disturbances for HVs systems, without relying on redundancy as some passive FTC methods do. Moreover, an anti-windup compensator is designed to mitigate the input saturation effects. Furthermore, the finite-time stability of the attitude angle of the HVs system is proved by Lyapunov's theorem. Numerical simulations validate the effectiveness of the proposed scheme.

Adaptive Saturated Path Following Control of Underactuated AUV With Unmodeled Dynamics and Unknown Actuator Hysteresis

This article addresses the three-dimensional (3-D) path-following problem of underactuated autonomous underwater vehicles (AUVs) in the presence of multiple uncertainties and nonlinearities, including unmodeled dynamics, actuator hysteresis, input saturation, and oceanic disturbance. First, the AUV kinetic model is reconstructed as a second-order nonlinear system by coupling the smooth saturation function and hysteresis dynamics of actuators. Second, the 3-D tracking error is derived in a simplified manner based on the relative motion theory. Then the approach angle-based symmetrical hyperbolic-tangent line-of-sight (SHLOS) guidance and kinematic control scheme are designed to ensure the global asymptotic stability of the kinematic system. Third, two sets of kinetic control schemes are designed without prior knowledge of AUV dynamics and disturbance, where the Nussbaum gain technique is applied to deal with the unknown hysteresis parameter. The application of the reconstructed kinetic model avoids the degraded performance caused by actuator nonlinearities. The first scheme is improved by adaptively estimating the bound of the generalized disturbance-like term which lumps the unmodeled dynamics, external disturbance, and saturation approximation error. The improved scheme guarantees the global stability of the system and transient tracking performance. Finally, comparative simulation studies under dynamic oceanic environments prove the effectiveness and robustness of the proposed control schemes.

On the state-of-the-art of CFD simulations for wave energy converters within the open-source numerical framework of DualSPHysics

There are currently several types of devices capable of harnessing wave energy, exploiting a broad variety of physical transformation processes. These devices – known as Wave Energy Converters (WECs) – are developed to maximize their power output. However, there are still uncertainties about their response and survivability to loads induced by adverse environmental conditions, with a consequent increase of the Levelized Cost of Energy (LCOE), which prevents in fact their commercial diffusion. As evidenced by a large body of research, marine renewable energy devices need to have more robust design practices. To address this issue, we propose the CFD-based DualSPHysics toolbox as a support in the design stages. DualSPHysics is high-fidelity software inherently suited to numerically address most challenges posed by multiphysics simulations, which are required to reliably predict WEC response in situations well beyond operational conditions. It should be noted that WECs, generally, may be connected to the seabed and comprise mechanical systems named Power Take-Offs (PTO) used to convert the energy from waves into electricity or other usable energies. To reproduce these features, DualSPHysics benefits from coupling with the multiphysics library Project Chrono and the dynamic mooring model Moordyn+. In this work, the augmented DualSPHysics framework is utilised to simulate a range of very different types of WECs with a variety of elements, such as catenary connections, taut mooring lines, or linear and nonlinear PTO actuators. Version 5.2 of the open-source licensed code was recently released, making the numerical framework publicly available as one unit. This work aims to provide a numerical review of past applications, and to demonstrate how the same open-source code is able to simulate very different technologies.
 
 Specifically, this paper proposes routine modeling and validation procedures using the SPH-based solver DualSPHysics applied to five different WEC types: i) a moored point absorber (PA); ii) an oscillating wave surge converter (OWSC); iii) a floating OWSC (so called FOSWEC); iv) a wave energy hyperbaric converter (WEHC); and v) a multi-body attenuator (so called Multi-float M4). For each device listed above, we provide validation proof against physical model data for various components of the floater(s) and PTO related quantities, performed under specific sea conditions that aim to challenge their survivability. Within the scope of this research, we present the WEC response with respect to the degrees of freedom that really matter for each of the floatings due to hydrodynamic interactions (i.e., heave, surge, and pitch), along with quantities more intimately connected to the anchoring systems (e.g., line tension) or the mechanical apparatus (e.g., end-stopper force). The quality of the results, the discussion built upon them and the demonstrated solver exploitability to a wide range of WECs show that one software model can run all cases using the exact same methodology, which is of great value for the marine energy R&D community. Finally, we discuss future research objectives, which include the implementation of automation to apply open control systems and possible applications to subsets of WEC farm arrays and other floating energy harnessing devices.

Tracking Control of Uncertain Neural Network Systems with Preisach Hysteresis Inputs: A New Iteration-Based Adaptive Inversion Approach

To describe the hysteresis nonlinearities in smart actuators, numerous models have been presented in the literature, among which the Preisach operator is the most effective due to its capability to capture multi-loop or sophisticated hysteresis curves. When such an operator is coupled with uncertain nonlinear dynamics, especially in noncanonical form, it is a challenging problem to develop techniques to cancel out the hysteresis effects and, at the same time, achieve asymptotic tracking performance. To address this problem, in this paper, we investigate the problem of iterative inverse-based adaptive control for uncertain noncanonical nonlinear systems with unknown input Preisach hysteresis, and a new adaptive version of the closest-match algorithm is proposed to compensate for the Preisach hysteresis. With our scheme, the stability and convergence of the closed-loop system can be established. The effectiveness of the proposed control scheme is illustrated through simulation and experimental results.

Discrete-time robust event-triggered actuator fault-tolerant control based on adaptive networks and reinforcement learning

This paper focuses on the topic of fault-tolerant control for discrete-time systems with nonlinear uncertainties and actuator faults. It considers both passive and active faults as part of the analysis and design. The proposed adaptive controller, based on a nonlinear electronic circuit, handles offset-biasing, sensitivity variation, and dead-zone effects. An event-triggered mechanism, utilizing a sliding surface, enhances robustness and reduces data transmission. Adaptive networks called MiFRENs are employed, trained using reinforcement learning. Theoretical analysis guarantees boundedness of internal signals and tracking error. Experimental results validate the scheme, demonstrating required conditions, reduced data transmission, and robust performance. Comparative evaluations confirm its superiority

Observer-Based Finite-Time Fault-Tolerant Control for Nonstrict-Feedback Nonlinear Systems With Multiple Uncertainties

In the fault-tolerant control (FTC) tasks of nonstrict-feedback nonlinear systems, unmeasurable states, disturbance, and actuator faults are recognized as the main factors that obstacle the effective controller design and, thus, the tracking performance improvement. To tackle these obstructions, a fuzzy observer is introduced to address the difficulties of the unmeasurable states involving nonstrict-feedback nonlinear systems by benefiting from the approximation property of fuzzy logic systems. Owing to the newly employed damping term in the intermediate control law being utilized to compensate for the possibly unlimited number of faults, the proposed FTC strategy is able to deal with actuator faults properly without imposing tighter requirements on the fault mechanism. To reach fast transient performance, stability of finite time is reached by exploiting the backstepping method. The investigated strategy ensures that all the responses of the systems are semiglobal practical finite-time stable. Meanwhile, the tracking error converges to a small neighborhood of the origin within finite time. In addition, to demonstrate its effectiveness, the provided approach is applied to the position tracking of a robotic system, which shows anticipated control performances in spite of various uncertainties.

Consensus Tracking of Singular Multiagent Systems via Sliding-Mode Approach

The admissible consensus tracking control of singular multiagent systems under nonlinear actuator attacks is investigated in this paper. A novel distributed adaptive protocol is designed, which can approximate the actuator attack by adaptive updating the weight matrix of neural network. An integral sliding surface is constructed based on the singularity of agents, and the sliding mode dynamics can reach the sliding mode surface in finite time under the proposed protocols. Sufficient conditions of impulse free and consensus tracking control of the singular multiagent systems are proved, and the attenuation of external disturbances is verified. The effectiveness of the proposed methods is verified through the numerical simulation examples.

Solving the Non-Linear Motion in a Micromanipulation System Powered by Thermocapillary Flows

Non-contact micromanipulation tools have emerged as a promising solution for manipulating small components. However, they are mainly based on non-linear actuation principles requiring ad-hoc control strategies. This paper proposes non-linear control laws to actuate a non-contact manipulation system based on thermocapillary flows for the manipulation of micro-objects on an air-water interface. The actuation system consists of steering a laser beam to locally heat the liquid surface, thus inducing a thermocapillary flow. The resulting flow propels floating objects away from the laser spot with a significant velocity (up to ten body-length per second) but the behavior is highly non-linear. Notably, small errors in the laser positioning are amplified and give place to non-linear motion. Therefore, we developed a control method consisting of a non-linear position controller including a laser position observer. We achieve stable 2D position control in this non-linear system, with a precision of 0.3 mm on a 0.5 mm object.

Trajectory tracking control of an underwater vehicle in the presence of disturbance, measurement errors, and actuator dynamic and nonlinearity

AbstractUnderwater vehicles are rich systems with attractive and challenging properties such as nonlinearities, external disturbances, and underactuated dynamics. These make the design of an advanced and robust controller quite a challenging task. This paper focuses on designing a model-free high-order sliding mode controller in a six-degree-of-freedom trajectory tracking task. The purpose of the control is accurate trajectory tracking and considerably reducing the chattering phenomenon in situations where the remotely operated vehicle (ROV) works in the presence of external disturbances, measurement errors, and actuator dynamics and nonlinearity, which is not seen in previous research. To demonstrate the stability of the closed-loop system, the Lyapunov theory is employed to ensure the asymptotic stability of tracking errors. A linear Kalman filter for estimating measurement errors is proposed to be used to correct positioning system outputs (speed, position, and attitude). In a hardware-in-the-loop test, the proposed controller for the ROV is tested in a real-time application, considering external disturbances, measurement errors, and actual thrusters. In addition, comparing the outcomes with the performance of the PID controller and the supper twisting controller shows the superiority of the proposed controller. Due to the existence of the measurement noise, spectrum analysis is also performed.

Adaptive control for a class of flexible mechanical systems with bending deformation and torsion deformation in the presence of nonlinear time-varying actuator faults and unknown control directions

Vibration control problem of a class of flexible mechanical systems with bending deformation and torsion deformation in the presence of nonlinear time-varying actuator faults and unknown control directions is considered in this paper. The dynamics model of this kind of flexible mechanical system, which includes two kinds of coupled vibration deformation and unknown nonlinear disturbances, is composed of some partial differential equations. In order to overcome the control difficulty brought by unknown control directions and time-varying nonlinear actuator faults, a Nussbaum function based adaptive boundary controller is designed to suppress the bending and twist vibration deformations of the mechanical system. The stability of the system is proved by Lyapunov direct method, and the effectiveness of the proposed control scheme is verified by numerical simulation at the end of this paper.

Optofluidic memory and self-induced nonlinear optical phase change for reservoir computing in silicon photonics

Nanophotonics allows to employ light-matter interaction to induce nonlinear optical effects and realize non-conventional memory and computation capabilities, however to date, light-liquid interaction was not considered as a potential mechanism to achieve computation on a nanoscale. Here, we experimentally demonstrate self-induced phase change effect which relies on the coupling between geometric changes of thin liquid film to optical properties of photonic waveguide modes, and then employ it for neuromorphic computing. In our optofluidic silicon photonics system we utilize thermocapillary-based deformation of thin liquid film capable to induce nonlinear effect which is more than one order of magnitude higher compared to the more traditional heat-based thermo-optical effect, and allowing operation as a nonlinear actuator and memory element, both residing at the same compact spatial region. The resulting dynamics allows to implement Reservoir Computing at spatial region which is approximately five orders of magnitude smaller compared to state-of-the-art experimental liquid-based systems.

Nonlinear Inflatable Actuators for Distributed Control in Soft Robots.

As soft robotic systems grow in complexity and functionality, the size and stiffness of the needed control hardware severely limits their application potential. Alternatively, functionality can be embodied within actuator characteristics, drastically reducing the amount of peripherals. Functions such as memory, computation, and energy storage then result from the intrinsic mechanical behavior of precisely designed structures. Here, actuators are introduced with tunable characteristics to generate complex actuation sequences from a single input. Intricate sequences are made possible by harnessing hysteron characteristics encoded in the buckling of a cone-shaped shell incorporated in the actuator design. A large variety of such characteristics are generated by varying the actuator geometry. This dependency is mapped and used for creating a tool to determine the actuator geometry that yields a desired characteristic. Using this tool, a system with six actuators is created that plays the final movement of Beethoven's Ninth Symphony with a single pressure supply.