Nonlinear Actuator Research Articles

Adaptive fixed‐time prescribed performance control of vehicular platoons with unknown dead‐zone and actuator saturation

AbstractThis article focuses on the problem of fixed‐time prescribed performance platoon control for heterogeneous vehicles with unknown dead‐zone and actuator saturation. First, an equivalent transformation is developed to approximate the actuator nonlinearity (i.e., dead‐zone and saturation), which reduces the complexity of controller design. Then, to guarantee the tracking errors converge to the predetermined region in the given time, a modified prescribed performance function is presented. Based on this, a novel adaptive sliding mode control scheme is developed in the context of fixed‐time theory, which is proved to be capable of ensuring individual vehicle stability and string stability in fixed time. In addition, under the proposed control scheme, the convergence time is independent of initial conditions of the system. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.

Tracking control and disturbance rejection for nonlinear switched control systems with saturation effects

AbstractThis article focuses on the concerns of a tracking control and active disturbance rejection for nonlinear switched systems described by Takagi–Sugeno fuzzy framework with state‐dependent nonlinear perturbations, actuator saturations and disturbances. Especially, a nonlinear equivalent‐input‐disturbance technique is employed to guarantee that only the external disturbances are rejected while retaining the beneficial nonlinearity of the system. Notably, with the aid of the lifting technique, the modified repetitive control are accurately described by a continuous‐discrete two‐dimensional model is designed to improve the tracking precision. The fuzzy‐membership‐function‐dependent piecewise Lyapunov–Krasovskii functional (LKF) by exploiting the knowledge of the membership functions are built to assure the exponential stability of the investigated system. Moreover, the controller and observer gains can be obtained as solutions to a set of strict linear matrix inequalities. Finally, an application example based on the cognitive radio model is given to verify the efficacy of the proposed control protocol.

Anti-disturbance observer-based control for fuzzy chaotic semi-Markov jump systems with multiple disturbances and mixed actuator failures

This article develops robust stabilization and anti-disturbance control design for fuzzy chaotic semi-Markov jump systems with randomly occurring uncertainties, nonlinear actuator faults, matched and mismatched disturbances. Primarily, the matched disturbances stimulated from the exogenous systems are dealt with by constructing a disturbance observer. At the same time, mismatched part is handled by the extended passivity performance. Additionally, the actuator fault model which encompasses both linear and nonlinear characteristics is put forward in the controller design. Thus, by taking advantage of the parallel distributed compensation methodology, a composite anti-disturbance control is framed by combining the fuzzy rule-based nonlinear fault-tolerant controller and estimation of the disturbance. Thereafter, by selecting relevant mode-dependent Lyapunov function candidate, adequate criteria are acquired in the context of linear matrix inequalities to ensure robust asymptotic stability along with the endorsed extended passivity performance level for the closed-loop system. In due course, by solving the developed inequalities under the aegis of MATLAB platform, the gain matrices of the devised controller and the framed disturbance observer are obtained. Last of all, to validate the effectiveness and applicability of the theoretical findings, simulation results of standard Chua’s circuit system, Lorenz system and Rössler system are exploited.

Improving the ride comfort of full car model with a decoupling intelligent model free controller

A new technique of active control is presented for enhancing the dynamic responses of full car systems with bias to ride comfort performance. A seven degrees of freedom full car model is used, and its performance is evaluated on a bump road and random road. The proposed scheme is a combination between traditional controller design methods with an algebraic estimator of perturbations that will be eliminated online. From the inputs and the outputs signals, the unmodeled phenomenon can be estimated and be subtracted for ensuring the proper functioning of the system. The precise mathematical model of the system is not required for the implementation of the control scheme and is replaced by ultra-local models. Furthermore, the effectiveness of the algebraic estimator of road profile is introduced for applying the excitation sources of the reference generator. The road profiles in front of the vehicle are estimated separately from the rear road profiles. The ride comfort is improved progressively with the novel controller configuration by 83% from the passive case. Further, pitching and rolling fluctuations are reduced by 80% and 85% respectively. The numerical simulations illustrate the effectiveness and the robustness against vehicle body mass deviation and nonlinear actuator saturation of the proposed control method compared to passive and Active Disturbance Rejection Controller based on Input Decoupling Transformation.

Predictor-Based Fuzzy Adaptive Containment Control for Nonlinear Multiagent Systems With Actuator Nonlinearity and Unmeasurable States

This article investigates the containment control problem of nonlinear multiagent systems subject to actuator nonlinearity, unmeasured states, and unknown external disturbances. The predictor technique is employed for each subsystem, and the prediction error is utilized to update the adaptive law. The problem of actuator nonlinearity with dead zone and saturation input is solved by introducing an auxiliary control signal. Incorporating the state observer and disturbance ones, an extended state observer is proposed to compensate the effect of unmeasurable and unknown disturbances, simultaneously. Based on Lyapunov theory and graph theory, it is shown that the devised control scheme guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Moreover, the followers can enter the dynamic convex hull spanned by the dynamic leaders. A simulation example with comparison analysis is provided to illustrate the effectiveness of the theoretical results.

ADP-Based Remote Secure Control for Networked Control Systems Under Unknown Nonlinear Attacks in Sensors and Actuators

In this article, we concentrate on a class of networked control systems (NCSs) under the unknown nonlinear attacks, which target the sensors and actuators with remote communication channels. To attenuate the attacks remotely, the remote secure control scheme based on the adaptive dynamic programming (ADP) is proposed. First, the dynamic process of NCSs with nonlinear sensors and actuators attacks is analyzed and an adaptive remote estimator is designed to obtain the state information of the NCSs from a long distance, which is the key to achieve the purpose of remote control. Moreover, to compensate for the unknown nonlinear attacks, the adaptive law of the remote estimator is presented based on recursive least square. Furthermore, we consider the influence of the estimation errors, the minimax control theory is applied to improve the design of the policy iteration algorithm, and the ADP-based remote secure control strategy is proposed to rely on the remote estimation information. Then, the neural networks are built to implement the online algorithm. Finally, results’ analysis illustrates on two networked power systems the effectiveness of the proposed method.

Finite-Time Adaptive Cooperative Fault-Tolerant Control for Multi-Agent System With Hybrid Actuator Faults

Aiming at the uncertain parameters and transient instability of the system caused by the actuator fault of the multiagent system, this article adopts the radial basis function neural networks to approximate unknown nonlinear function. Then, a novel adaptive fault-tolerant controller is designed based on the combination back-stepping technology and dynamic surface technology to compensate the unknown nonlinear hybrid actuator faults, thereby improving the fault tolerance of the system. Furthermore, the designed controller can guarantee the transient stability of the system through finite-time theory and Lyapunov stability theory. Finally, the comparison of two simulation examples is given to verify the effectiveness of the designed controller, which provided an effective research idea for engineering practice.

Nonlinear actuation of micromechanical Casimir oscillators with topological insulator materials toward chaotic motion: Sensitivity on magnetization and dielectric properties.

We have investigated the dynamical actuation of micro-electromechanical systems under the influence of attractive and repulsive Casimir forces between topological insulator plates as a function of their dielectric function and coating magnetization. The analysis of the Casimir force in the limit of strong and weak magnetization shows that the attractive force, which is produced for plate magnetizations in the same direction, is greater than the repulsive force that is produced for opposite magnetizations. However, both forces remain comparable for intermediate magnetizations. Moreover, for weak magnetization, the attractive force becomes stronger for an increasing dielectric function, while the opposite occurs for the repulsive force. On the other hand, increasing magnetization decreases the influence of the dielectric function on both the repulsive and attractive forces. Furthermore, for conservative systems, bifurcation and phase portrait analysis revealed that increasing magnetization decreases the regime of stable operation for devices with attractive forces, while their operation remains always stable under the presence of repulsive forces. Finally, for non-conservative periodically driven systems, the Melnikov function and Poincaré portrait analysis show that for magnetizations in the same direction leading to strong attractive Casimir forces, chaotic motion toward stiction is highly likely to occur preventing the long-term prediction of actuating dynamics. A remedy for this situation is obtained by the application of any magnetization in opposite directions between the interacting surfaces since the repulsive force makes it possible to prevent stiction.

A fractional-order Duhem model of rate-dependent hysteresis for piezoelectric actuators

In this paper, a Fractional-Order Duhem Model (FODuhem) is proposed to describe the rate-dependent hysteresis nonlinearity of piezoelectric actuators (PEAs). A fractional-order operator is introduced on the basis of the traditional Duhem model, and the unique nonlocal memory property of the fractional-order operator makes it possible to describe the memory effect inherent in hysteresis. A differential evolutionary algorithm was used to identify the parameters of the FODuhem model. Finally, experimental results clearly show that the FODuhem model can better describe the rate-dependent hysteresis behavior of piezoelectric actuators compared with the conventional Duhem model.

A New Type-3 Fuzzy Logic Approach for Chaotic Systems: Robust Learning Algorithm

The chaotic systems have extensive applications in various branches of engineering problems such as financial problems, image processing, secure communications, and medical problems, among many others. In most applications, a synchronization needs to be made with another favorite chaotic system, or output trajectories track the desired signal. The dynamics of these systems are complicated, they are very sensitive to the initial conditions, and they exhibit a stochastic unpredictable behavior. In this study, a new robust type-3 fuzzy logic control (T3-FLC) is designed that can be applied for a large case of chaotic systems under faulty actuators and unknown perturbed dynamics. The dynamic uncertainties are estimated by the online learned type-3 fuzzy logic systems (T3-FLSs). The rules of T3-FLS are optimized by the Lyapunov theorem. The actuator nonlinearities are identified by a new method. The effects of approximation error (AE), dynamic perturbations and unknown time-varying control gains are tackled by the designed adaptive compensator. The designed compensator is constructed by online estimation of the upper bound of AE. By several simulations and comparison with the new FLS-based controllers, the better performance of the designed T3-FLC is shown. In addition, the performance of the designed controller is examined in a secure communication system.

Extremum‐seeking control for unknown static maps with mixed actuator nonlinearity

AbstractThis study proposes an extremum‐seeking controller design for unknown static maps subject to a combination of saturated and discrete actuators with unknown characteristics but with measurable final control elements. The proposed design techniques incorporate a filter for each uncertain actuator that enables the design of a constrained extremum‐seeking control that operates at a slow time‐scale. The stability analysis demonstrates that the closed‐loop system has a practically asymptotically stable equilibrium at the unknown constrained optimum of the optimization problem. A simulation is presented that demonstrates the effectiveness of the proposed technique.

A fluidic relaxation oscillator for reprogrammable sequential actuation in soft robots

A fluidic relaxation oscillator for reprogrammable sequential actuation in soft robots

Fractional-order control for nano-positioning of piezoelectric actuators

Piezoelectric actuators are widely used in the field of high-precision positioning control. However, due to the inherent hysteresis nonlinearity of piezoelectric actuators, it can seriously affect their accuracy in tracking and positioning systems, and even cause system instability. In order to suppress the hysteresis characteristics of piezoelectric, based on the analysis of piezoelectric characteristics and the characteristics of classical Bouc–Wen model, a Bouc–Wen model is adopted to describe the hysteresis characteristics of piezoelectric actuators, an artificial bee colony (ABC) algorithm is used to identify Bouc–Wen. The maximum error of the model is 2.49%. According to the established hysteresis model, its inverse model is obtained as the feedforward controller, and the inverse model compensation method is used to realize the open-loop control of the system. Since the feedforward controller based on the inverse model cannot eliminate the modeling errors and external disturbances of the inverse model, a fractional-order controller is designed on the basis of inverse compensation, and a compound control method combining feedforward control and feedback control is adopted. Experiments show that the fractional-order control system has fast response speed, small steady-state error and simple structure compared with other nonlinear controllers, positioning error is about 3%.

Thin liquid film as an optical nonlinear-nonlocal medium and memory element in integrated optofluidic reservoir computer

Understanding light–matter interaction lies at the core of our ability to harness physical effects and to translate them into new capabilities realized in modern integrated photonics platforms. Here, we present the design and characterization of optofluidic components in an integrated photonics platform and computationally predict a series of physical effects that rely on thermocapillary-driven interaction between waveguide modes and topography changes of optically thin liquid dielectric film. Our results indicate that this coupling introduces substantial self-induced phase change and transmittance change in a single channel waveguide, transmittance through the Bragg grating waveguide, and nonlocal interaction between adjacent waveguides. We then employ the self-induced effects together with the inherent built-in finite relaxation time of the liquid film, to demonstrate that the light-driven deformation can serve as a reservoir computer capable of performing digital and analog tasks, where the gas–liquid interface operates both as a nonlinear actuator and as an optical memory element.

A Discrete Non-Linear Series Elastic Actuator for Active Ankle-Foot Orthoses

This letter outlines the modelling, design, and experimental validation of a novel power-efficient actuator for an active ankle-foot orthosis (AAFO). The actuator is based on a new principle of discrete non-linear stiffness. Two or more linear springs are discretely compressed at specified displacement intervals to reduce the peak mechanical power required to actuate the AAFO. The actuator uses a crank-rocker configuration. The connecting link is comprised of the discrete non-linear technique, a DC motor powers the crank, and the rocker is connected directly to the ankle joint. Multi-objective optimization is carried out to select the link lengths and spring stiffnesses to reduce input power and size. The actuator design weighs 460 g with bounding box dimensions of 103x45x94 mm. The newly proposed discrete non-linear stiffness configuration reduces the peak mechanical input power by 77.2% with respect to nominal biological ankle joint power. A prototype was developed and tested using static loading and human walking trials to verify the actuator models and simulations. The experimental results confirm the validity of the models by comparing the actual and theoretical ankle and motor torque values in the presence of discrete variable stiffness.

Motion control for earth excavation robot based on force pre-load and cross-coupling compensation

In the earthmoving automation procedure, the properties of large inertia, strong nonlinearity and flow coupling of multiple actuators are not considered comprehensively in relevant studies, which restricts the accuracy and efficiency performance of leveling tasks. To solve the problem of limited accuracy caused by the difficulty in modeling hydraulic flow coupling and the hysteresis of terminal compensation, we proposed a coordinated motion control method for an automatic earth excavation robot, which reduced the contour error from the perspective of force preloading and terminal control compensation. Various experiments show that the motion coordination of the proposed controller is significantly better than the PID-based controller and the contour-based controller. Due to its stability in multiple conditions, we believe the system will provide an effective earthmoving automation solution for different types of excavators in control. For further study, the soil force estimation will be integrated to improve the system performance under more tasks.

Continuous finite-time extended state observer design for electro-hydraulic systems

This paper presents a novel framework towards a time-varying observer design for nonlinear electro-hydraulic actuators. The key idea of this paper is to employ a positive-increasing function associated with the observer objective to improve the estimation performance. An extended state observer is designed to estimate the full state variables and the uncertainties without any knowledge about the upper bounds of the uncertainties and their derivatives. First, without loss of generality, the system model is divided into three parts, and the extended state observers are designed for each part, independently. Then, the time-varying gains of each observer are designed to make the observation errors uniformly bounded. Finally, the simulated performance of the presented framework is compared with two valid approaches including high-order sliding mode and high-gain extended state observers.

Non‐fragile reliable control of nonlinear positive semi‐Markovian jump systems with nonlinear actuator faults

AbstractThis paper investigates the non‐fragile reliable control of nonlinear positive semi‐Markovian jump systems with nonlinear actuator faults. First, a novel fault model consisting of linear and nonlinear terms is established for the systems. By constructing a stochastic co‐positive Lyapunov function, the non‐fragile reliable controller is designed for the systems with additive gain perturbations using matrix decomposition technique. Then, the proposed design is extended for dealing with multiplicative gain perturbations and variable gain perturbations. Under the designed controllers, the resulting closed‐loop systems are positive and stochastically stable. All presented conditions are solvable in terms of linear programming. Finally, two illustrative examples are provided to verify the effectiveness of the theoretical results.

A Novel Design of Torsion Spring-Connected Nonlinear Stiffness Actuator Based on Cam Mechanism

Abstract The nonlinear stiffness actuator (NSA) is a type of compliant joint with variable stiffness that is necessary for human–machine collaboration and has been the focus of extensive research attention. This academic work presents the principle of a torsion spring-connected nonlinear stiffness actuator (TSNSA), a NSA suitable for implementing revolute motions, which contrasts with existing NSAs that often have bulky mechanisms and are affected by a limited range of movement. It has a split sleeve, disc springs, and cam mechanisms (CMs) that when correctly configured, can passively and actively adjust stiffness, where the speed of stiffness regulation can be effectively improved. The mathematical model of a split sleeve inserted into a torsion spring is designed to analyze the behavior of mechanical components. Furthermore, a detailed CM profile has been designed to obtain the desired nonlinear stiffness. Its theoretical analysis includes numerical simulations with results consistent with the desired deflection–torque profile.

Efficient pneumatic actuation modeling using hybrid physics-based and data-driven framework

Soft robotics, characterized by structural compliance, offers advantages when handling fragile objects and interacting with humans. Modeling the mechanical behavior of soft robots, however, is often overlooked in previous studies due to the difficulty of capturing their nonlinear deformation. In this work, we present a highly efficient predictor for pneumatic actuation utilizing a combination of data-driven surrogate modeling and physics-based optimization. This hybrid methodology explicitly captures the nonlinear mechanics of pneumatic components, which greatly accelerates the searching of static equilibrium, and thus help elucidate how the overall grasping system will interact with the environment. We have additively manufactured and tested a robotic device on various objects. Results show that our model can predict pneumatic actuation very closely matching to that of the experiments with orders of magnitude faster computational speed than traditional numerical simulations. Moreover, the proposed framework can be extended to model various soft robotic devices with nonlinear actuation components.