Dynamic Control Design Research Articles

Design of Neural Network-Based Adaptive Inverse Dynamics Controller for Motion Control of Stewart Platform

This research article attempts to design Inverse Dynamics Controller (IDC) to execute the motion tracking of Stewart Platform. In the presence of modeling uncertainties and external disturbances, the closed-loop dynamic equation of IDC with fixed gains becomes nonlinear and configuration-dependent, which compromises the motion tracking accuracy. Further, both modeling uncertainties and external disturbances are unavoidable in real life conditions. To tackle this issue, this article proposes a novel control algorithm by combining IDC with Feed-Forward Artificial Neural Network (FF-ANN) trained using PSO. The proposed modified control algorithm offers superior motion tracking accuracy in comparison with traditional IDC.

Design and practical implementation of a Neural Network self-tuned Inverse Dynamic Controller for a 3-DoF Delta parallel robot based on Arc Length Function for smooth trajectory tracking

This paper proposes an online Neural Network self-tuned Inverse Dynamic Controller (IDC) for high-speed and smooth trajectory tracking control of a 3-DoF Delta robot. The foregoing approaches provides a suitable controller for a wide range of nonlinear paths and reduce the end-effector oscillations at high speed. To this end, a compact and accurate dynamic model of the system is derived by taking into account actuators and gearbox dynamics. In order to alleviate some drawbacks of a velocity-based controller, such as not being able to track highly dynamic paths, an Inverse Dynamic Controller (IDC) is designed which can perform fast maneuvers accurately. The proposed IDC controller is practically implemented on the robot in following nonlinear paths comparing to the velocity-based controller. Afterward, controller parameters are tuned by resorting to the so-called Arc Length Function (ALF) in order to improve the smoothness of tracking the prescribed path. After that, a Feedforward Neural Network (NN) is trained with the help of the system’s model and Arc Length Function (ALF) to adjust controller coefficients in real-time implementation adaptively. By comparing the Root Mean Square Error (RMSE) results, it can be inferred that the proposed methods can reduce the end-effector oscillations up to 60 percent in practical implementation compared to other dynamic and kinematic methods. As a result, RMSE error is reduced from 0.00603 for the kinematic controller to 0.00063 by applying the NN-IDC.

LMI-based consensus of linear multi-agent systems by reduced-order dynamic output feedback

This work proposes new conditions for consensus of homogeneous multi-agent systems subjected to exogenous disturbances in directed communication graphs by dynamic output feedback protocols. The agents under investigation are described as linear dynamics, and the communication network is such that each agent receives as information only the output of neighbor agents. The synchronization problem is rewritten as an output feedback stabilization without requiring the Laplacian matrix to be diagonalizable. As the main appeal, we propose new necessary and sufficient conditions for the design of dynamic output feedback controllers of arbitrary order – including static output feedback as a particular case – and sufficient Linear Matrix Inequalities (LMIs) for H∞ consensus. Numerical experiments illustrate the effectiveness of the proposed approach.

Lyapunov-based Robust Adaptive Configuration of the UAS-S4 Flight Dynamics Fuzzy Controller

AbstractIn tandem with the fast-growing demand for Unmanned Aerial Vehicles (UAVs) for surveillance and reconnaissance, advanced controllers for these critical systems are needed. This paper proposes a flight dynamics controller design that considers various uncertainties for the Hydra Technologies UAS-S4 Ehécatl. In order to be realistic, in addition to flight dynamics nonlinearities, three main sources of uncertainties are considered, as those caused by unknown controller’s parameters, modeling errors, and external disturbances. A Robust adaptive fuzzy logic controller is designed, in charge of nonlinear flight dynamics in presence of a variety of uncertainties. The nonlinear flight dynamics is modeled based on the Takagi-Sugeno method relying on the soft association of local linear models. Since this controller is model-based, an optimal reference model is defined, which is stabilised by the Linear Quadratic Regulator procedure. A fuzzy logic controller is then designed for the nonlinear model. Lastly, with the aim to handle the uncertainties, the gains of the fuzzy controller are reconfigured, and are continuously adjusted by Lyapunov-based robust adaptive laws. The performance of the UAS-S4 Robust adaptive fuzzy logic controller is evaluated in terms of lateral and longitudinal flight dynamics stabilisation, and the reference model state variables tracking under various uncertainties.

커플드 인덕터기반의 계통 연계형 Ćuk CCM 인버터의 동적 모델링과 제어기 설계

This paper presents a dynamic modeling and controller design for a grid-connected Ćuk continuous conduction mode (CCM) inverter with a coupled inductor. The primary- and secondary-side inductors of the conventional Ćuk converter are integrated into one coupled inductor in the presented Ćuk CCM inverter, and it reduces the number of passive components. To make the Ćuk CCM inverter with a coupled inductor connected with the grid utility, an output current controller should be designed appropriately. However, the output current control of the presented Ćuk inverter is difficult due to the existence of the right-half plane (RHP) zeros in its transfer function. To solve the problem, a dynamic model of the Ćuk CCM inverter with a coupled inductor is developed and a repetitive controller (RC) coupled with feedback and feedforward controllers is applied to this inverter. A practical design guideline is also presented to select control parameters. Experimental results using a 200-W prototype demonstrate the acceptable performance of the proposed controller.

Dynamic event-triggered control design for a class of [formula omitted]-normal nonlinear time-delay systems with actuator failures

This paper investigates the adaptive tracking control problem for a class of p-normal nonlinear time-delay systems with actuator failures via a dynamic event-triggered strategy. To deal with the time-varying delay, a modified Lyapunov-Krasovskii functional (LKF) with the system powers is constructed. By using radial basis function neural networks and hyperbolic tangent function, the residual terms caused by the derivative of LKF can be handled. Then, to achieve better communication efficiency, a dynamic event-triggered strategy is proposed, in which the threshold parameter is dynamically adjusted with the change of the virtual control signal. With the help of the proposed adaptive controller, all states of the closed-loop system are bounded and a favorable tracking performance is ensured. Finally, two examples are given to demonstrate the effectiveness of the proposed method.

On Active Vibration Absorption in Motion Control of a Quadrotor UAV

Conventional dynamic vibration absorbers are physical control devices designed to be coupled to flexible mechanical structures to be protected against undesirable forced vibrations. In this article, an approach to extend the capabilities of forced vibration suppression of the dynamic vibration absorbers into desired motion trajectory tracking control algorithms for a four-rotor unmanned aerial vehicle (UAV) is introduced. Nevertheless, additional physical control devices for mechanical vibration absorption are unnecessary in the proposed motion profile reference tracking control design perspective. A new dynamic control design approach for efficient tracking of desired motion profiles as well as for simultaneous active harmonic vibration absorption for a quadrotor helicopter is then proposed. In contrast to other control design methods, the presented motion tracking control scheme is based on the synthesis of multiple virtual (nonphysical) dynamic vibration absorbers. The mathematical structure of these physical mechanical devices, known as dynamic vibration absorbers, is properly exploited and extended for control synthesis for underactuated multiple-input multiple-output four-rotor nonlinear aerial dynamic systems. In this fashion, additional capabilities of active suppression of vibrating forces and torques can be achieved in specified motion directions on four-rotor helicopters. Moreover, since the dynamic vibration absorbers are designed to be virtual, these can be directly tuned for diverse operating conditions. In the present study, it is thus demonstrated that the mathematical structure of physical mechanical vibration absorbers can be extended for the design of active vibration control schemes for desired motion trajectory tracking tasks on four-rotor aerial vehicles subjected to adverse harmonic disturbances. The effectiveness of the presented novel design perspective of virtual dynamic vibration absorption schemes is proved by analytical and numerical results. Several operating case studies to stress the advantages to extend the undesirable vibration attenuation capabilities of the dynamic vibration absorbers into trajectory tracking control algorithms for nonlinear four-rotor helicopter systems are presented.

Design of Robust Dynamic Output Feedback Event-Triggering Controllers for Nonlinear Uncertain Systems

This paper presents a design of dynamic output feedback event-triggering control for nonlinear uncertain networked control systems. The plant and actuator asynchronously transmit the measurement and control signals over two different communication channels. We address the norm-bounded time-varying parameter uncertainties in a nonlinear plant. First, considering the exogenous disturbances and noises in the control and measurement signals, sufficient conditions for the <i>L</i>₂ stability of the nonlinear networked control systems are given in the presence of the uncertainties. Then, we propose design conditions to choose the dynamic output feedback control and triggering laws in terms of linear matrix inequalities (LMIs). The proposed conditions enable the controller and event-triggering parameters to be jointly optimized to lessen the number of transmissions, guaranteeing a certain level of <i>L</i>₂ gain. Numerical examples demonstrate the effectiveness of the proposed method.

Intelligent Dynamic Inversion Controller Design for Ball and Beam System

The Ball and beam system (BBS) is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable properties. Designing an effective ball and beam system controller is a real challenge for researchers and engineers. In this paper, the control design technique is investigated by using Intelligent Dynamic Inversion (IDI) method for this nonlinear and unstable system. The proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in it. The Moore-Penrose Generalized Inverse (MPGI) is used to invert the prescribed constraint dynamics to realize the baseline control law. A sliding mode-based intelligent control element is further augmented with the baseline control to enhance the robustness against uncertainties, nonlinearities, and external disturbances. The semi-global asymptotic stability of IDI control is guaranteed in the sense of Lyapunov. Numerical simulations and laboratory experiments are carried out on this ball and beam physical system to analyze the effectiveness of the controller. In addition to that, comparative analysis of RGDI control with classical Linear Quadratic Regulator and Fractional Order Controller are also presented on the experimental test bench.

Anti-Disturbance Dynamic Surface Control for Air-Breathing Hypersonic Vehicles Based on NDO

This paper is concerned with the anti-disturbance dynamic surface controller (DSC) design for an air-breathing hypersonic vehicle (AHV) based on nonlinear disturbance observer (NDO). For the longitudinal model of AHV subjected to the high nonlinearity, the uncertain parameters and the varying disturbance, the feedback linearization method is employed considering the uncertain parameters. Then, a dynamic surface controller is designed based on the inverse hyperbolic sine function to solve the problem of "explosion of terms" in the traditional backstepping control. Furthermore, in order to enhance the disturbance rejection ability, a novel NDO is designed to estimate the model uncertainties and external disturbances. Finally, the simulation results verify the superior tracking performance of the proposed control strategy.

Robust Motion Control Architecture for an Upper-Limb Rehabilitation Exosuit

Upper-limb exosuits are light wearable devices suitable for applications such as rehabilitation or assistance in industrial environments. One of the main drawbacks of these systems is the amount of uncertainties intrinsic to the nature of the device. Moreover, the direct interaction between the exosuit and its user adds disturbances to the system. Therefore, a robust control architecture to these phenomena is required for its appropriate control. In this article, a robust motion (position and speed) control architecture based on a cascade proportional-integral (PI) and a sliding mode controller (SMC), and a nonlinear disturbance observer (NDO) for the upper-limb cable-driven rehabilitation exosuit LUXBIT is designed. We call the proposed controller by the acronym CPISDO. The SMC nature allows to compensate the matched disturbances and uncertainties, while the NDO counteracts the unmatched ones. The PI component helps in reducing tracking error. Dynamic modelling, system architecture and control design are addressed. The CPISDO controller has been implemented over the exosuit and several experiments have been performed over 10 healthy subjects to evaluate the controller’s tracking performance as well as the disturbance rejection. Supertwisting (a state-of-the-art SMC) and PI controllers have been implemented for CPISDO validation. Results are compared with other state-of-the-art solutions.

Adaptive fuzzy output-feedback event-triggered control for fractional-order nonlinear system.

This paper studies the issue of adaptive fuzzy output-feedback event-triggered control (ETC) for a fractional-order nonlinear system (FONS). The considered fractional-order system is subject to unmeasurable states. Fuzzy-logic systems (FLSs) are used to approximate unknown nonlinear functions, and a fuzzy state observer is founded to estimate the unmeasurable states. By constructing appropriate Lyapunov functions and utilizing the backstepping dynamic surface control (DSC) design technique, an adaptive fuzzy output-feedback ETC scheme is developed to reduce the usage of communication resources. It is proved that the controlled fractional-order system is stable, the tracking and observer errors are able to converge to a neighborhood of zero, and the Zeno phenomenon is excluded. A simulation example is given to verify the availability of the proposed ETC algorithm.

Adaptive preassigned finite‐time stability of nonlinear systems with time‐varying powers and full‐state constraints

AbstractThis article discusses adaptive preassigned finite‐time stability of nonlinear systems with unknown time‐varying powers and full‐state constraints. By introducing a concept of practical preassigned finite‐time stable, constructing finite‐time performance functions and nonlinear transformed functions, and integrating high‐power and low‐power terms into dynamic surface control design, an adaptive state‐feedback controller is designed to eliminate the effects of unknown powers and serious unknown parameters in system dynamics, and decrease the computational burden in previous design methods. It is proved that all the signals of the closed‐loop system are bounded, asymmetric time‐varying full‐state constraints are not transgressed, and system states converge to a prescribed arbitrarily small region around zero after a preassigned settling time. Two simulation examples show the effectiveness and advantages of this control scheme.

Rigid-Flexible Coupled Dynamics and PD-Robust Control Design for the Spacecraft with Rotating Solar Panels

The dynamical model for the spacecraft with multiple solar panels and the cooperative controller for such spacecraft are studied in this paper. The spacecraft consists of a rigid platform and two groups of flexible solar panels, where solar panels could be driven to rotate by the connecting shaft. The flexible solar panel involves the use of the orthogonal polynomial in two directions to describe its elastic deformation. By using the Rayleigh–Ritz method, the characteristic equation is derived to obtain natural frequencies and modal shapes of the whole spacecraft. Then the discrete rigid-flexible coupled dynamical equation of the spacecraft is obtained by using the Hamiltonian principle. The equation involves the coupling of the attitude maneuver, solar panels’ driving and vibration suppression. These dynamical behaviors are addressed by the rigid-flexible coupled mode for the first time in this paper. Based on the dynamical equation, the cooperative control scheme is designed by combing the proportional-differential and robust control method. Numerical results show the accuracy of the present modelling method and the validation of the control strategy. The modal analysis implies the complex rigid-flexible coupled characteristic between the central platform and flexible solar panels. The proposed control scheme can maintain the attitude stability while solar panels are being driven, as well as the vibration suppression of flexible solar panels.

Robust path-following control of underactuated AUVs with multiple uncertainties and state constraints

This paper proposes a novel robust controller for horizontal path-following problem of an underactuated AUV subject to multiple uncertainties and state constraints. Firstly, four reduced-order extended state observes (ESOs) are designed to estimate the multiple uncertainties, and the estimated values are adopted in the design of kinematic and dynamic controller. Secondly, to address the state constraints, the barrier Lyapunov function is incorporated with the kinematic controller. To resolve the problem of input saturation, the auxiliary design system is utilized in the dynamic controller. To address the problem of “explosion of complexity” inherent in the conventional back-stepping method, a nonlinear tracking differentiator is utilized to obtain the derivative of the desired yaw speed. Finally, the results of numerical simulation are performed to demonstrate the effectiveness of the proposed controller.

Emerging approaches for nonlinear parameter varying systems

Emerging approaches for nonlinear parameter varying systems

On the efficacy and accuracy of freezing technique for the response analysis of time-varying vehicle-bridge interaction systems

The basic problem of vehicle-bridge interaction (VBI) is a linear time-varying system for which no exact solution is available and even numerical solutions can be complicated. In this paper, the efficacy and accuracy of a freezing technique (FT), in which the time parameter is frozen, applied to obtain the forced response of the VBI system are assessed. To improve the accuracy, a time-step approach, in which FT is employed in each time subinterval, is proposed. The FT is relatively simple to implement and results are validated with and compared to those obtained by a highly accurate Runge-Kutta method (treated as “exact” solution) for different vehicle models, vehicle and bridge parameters, and time steps. It is found that numerical results obtained by the FT are accurate, even for high vehicle speeds. Moreover, the FT outperforms the Newmark-β method. An analytical local error bound for the FT is derived, which shows the error dependence on the vehicle-bridge coupling dynamics, in particular, the tire stiffness and the vehicle speed. An important implication of this study is that, since the FT can be applied to analyze the time-varying VBI system, the method essentially transforms the coupled system into a time sequence of linear time-invariant (LTI) systems and allows tools for dynamic analysis and controller design of LTI systems to be applicable to the VBI problem.

An Improved Integral Inequality for Delay-Dependent Gain-Scheduled LPV Control

The present work examines the delay-dependent gain-scheduling feedback control with guaranteed closed-loop stability and induced L2 norm performance for continuous-time linear parameter-varying (LPV) systems with arbitrary time-varying delay. An extension of Lyapunov stability utilizing Krasovskii functionals is considered to derive stability analysis and synthesis conditions for delay-dependent dynamic output feedback LPV control design. The main challenges associated with this approach are selecting appropriate Lyapunov-Krasovskii functionals (LKFs) and finding efficient integral inequalities to bound the derivative of the LKF. Accordingly, a novel modified parameter-dependent LKF candidate along with an affine version of Jensen’s inequality bounding technique are employed leading to the derivation of less conservative sufficient conditions expressed in terms of convex linear matrix inequalities (LMIs). The proposed methodology is compared with past work in the literature in terms of conservatism reduction and performance improvement through a numerical example. Finally, the application of the proposed output-feedback LPV control design is evaluated on the automated mean arterial blood pressure (MAP) regulation in critical patient resuscitation via vasoactive drug infusion. Closed-loop simulation results are presented to illustrate the potential of the introduced LPV gain-scheduling design to provide MAP set-point tracking in the presence of disturbances and varying input delays.

A Quadratic Programming Based Neural Dynamic Controller and Its Application to UAVs for Time-Varying Tasks

A quadratic programming based neural dynamic (QPND) controller design method is proposed for time-varying trajectory tracking of unmanned aerial vehicles (UAVs). Different from the traditional controller frameworks which only use pitch and roll angles to achieve the horizontal movement of the UAV, all the three attitude angles, i.e., roll, pitch and yaw angles, are applied for horizontal moving in this paper. There are at least three great superiorities of the proposed QPND controller. Firstly, three attitude angles can be coordinated control since the quadratic programming framework incorporates three attitudes. Secondly, the new framework enables the UAV to achieve the additional performance criteria or to perform subtasks. Third, the new controller can track time-varying trajectories due to neural dynamic approach. Specifically, the design process of the controller is divided into position controller design, attitude controller design and quadratic programming formulation. Finally, simulation experiments verify the feasibility and high efficiency of the proposed controller and its superiority compared with some state-of-the-art UAV controllers.

Dynamic learning control design for interval type‐2 fuzzy singularly perturbed systems: A component‐based event‐triggering protocol

AbstractIn this work, the sliding mode control (SMC) problem is addressed for the discrete‐time interval type‐2 fuzzy singularly perturbed systems. A component‐based dynamic event‐triggering scheme is first proposed to determine the transmission of each measurement component according to the prespecified triggering condition, under which each sensor node will transmit independently its signal to the controller. Meanwhile, the SMC approach is used to design an effective interval‐type‐2 fuzzy controller by only utilizing the transmitted component signals, and the ‐independent conditions are developed to attain the stability of the closed‐loop system and the reachability of the sliding domain. In addition, a framework of the optimization control design is established, where the learning‐based iterative optimization algorithm is proposed via reducing the convergence domain around the sliding surface. Finally, the proposed SMC scheme is verified via the simulation results.