Fast finite-time tracking control for a 3-DOF cable-driven parallel robot by adding a power integrator✰

Cable-driven parallel robots (CDPRs) usually suffer from kinematic and dynamic uncertainties, which makes it difficult for traditional trajectory tracking control algorithms to achieve high precision, fast response time, and robustness. In this study, we present a novel fast finite-time tracking control (FFTTC) algorithm which solves this problem to a large extent. Specifically, we firstly used a function of exponential errors with fractional power combined with API technique, to deal with the key difficulty of the convergence rate degradation which exists in traditional finite-time tracking control (TFTTC) when system states are far from the equilibrium point. Simultaneously, the API technique was used to avoid the problem of the explosion of complexity. To facilitate algorithm evaluation, the finite-time stability of the close system consisting of the proposed FFTTC algorithm and the CDPRs was proved mathematically and the settling time was estimated correspondingly. The trajectory tracking experiments were performed on a 3-DOF CDPR driven by 4 cables. Simulation and experimental results show that the proposed FFTTC algorithm can cope with external disturbances, variable load, and inaccurate model parameters. The comparison experiment indicates that the proposed FFTTC algorithm is superior to the model predictive control and TFTTC algorithms in precision, response speed and robustness.     

新型终端滑模在光电稳定平台中的应用

为了提高光电伺服稳定平台的跟踪精度,针对系统中干扰的影响提出一种新型终端滑模控制算法。首先,提出一种新型终端滑模干扰观测器的设计方法,实现对系统中干扰的快速估计和实时补偿。其次,设计新型终端滑模控制器来提高系统的跟踪精度,结合有限时间收敛和自适应控制的思想,对切换增益进行在线调整,有效地抑制了滑模控制中的抖振问题,使系统状态能够在有限时间内快速地收敛到所设计的滑模面上,并对未估计干扰进行精细化补偿。最后利用Lyapunov理论证明控制系统的稳定性。实验结果表明:该控制策略保证了光电跟踪系统视轴对运动目标的跟踪精度,在0.05 Hz时误差小于0.002,在2 Hz时误差小于0.034,增强了系统的鲁棒性。     

Finite-time control of DC–DC buck converters via integral terminal sliding modes

This article presents novel terminal sliding modes for finite-time output tracking control of DC–DC buck converters. Instead of using traditional singular terminal sliding mode, two integral terminal sliding modes are introduced for robust output voltage tracking of uncertain buck converters. Different from traditional sliding mode control (SMC), the proposed controller assures finite convergence time for the tracking error and integral tracking error. Furthermore, the singular problem in traditional terminal SMC is removed from this article. When considering worse modelling, adaptive integral terminal SMC is derived to guarantee finite-time convergence under more relaxed stability conditions. In addition, several experiments show better start-up performance and robustness.     

Robust adaptive tracking control of uncertain electrostatic micro-actuators with H-infinity performance

A novel adaptive robust tracking control scheme is proposed for a class of single-degree-of-freedom (1DOF) electrostatic micro-actuator systems in the presence of parasitics, parameter uncertainties and external disturbances. This method integrates the adaptive dynamic surface control and H-infinity control techniques. Based on this method, both the design procedure and the derived tracking controller itself are simplified, and the controller guarantees that the output tracking error satisfies the H-infinity tracking performance. In addition, the tracking accuracy can be adjusted by an appropriate choice of the design parameters of the controller. Simulation results show that prescribed transient output tracking performance can be achieved, and the closed-loop system exhibits good robustness to system uncertainties.     

A Neuro-Sliding-Mode Control With Adaptive Modeling of Uncertainty for Control of Movement in Paralyzed Limbs Using Functional Electrical Stimulation

During the past several years, several strategies have been proposed for control of joint movement in paraplegic subjects using functional electrical stimulation (FES), but developing a control strategy that provides satisfactory tracking performance, to be robust against time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, muscle fatigue, and external disturbances, and to be easy to apply without any re-identification of plant dynamics during different experiment sessions is still an open problem. In this paper, we propose a novel control methodology that is based on synergistic combination of neural networks with sliding-mode control (SMC) for controlling FES. The main advantage of SMC derives from the property of robustness to system uncertainties and external disturbances. However, the main drawback of the standard sliding modes is mostly related to the so-called chattering caused by the high-frequency control switching. To eliminate the chattering, we couple two neural networks with online learning without any offline training into the SMC. A recurrent neural network is used to model the uncertainties and provide an auxiliary equivalent control to keep the uncertainties to low values, and consequently, to use an SMC with lower switching gain. The second neural network consists of a single neuron and is used as an auxiliary controller. The control law will be switched from the SMC to neural control, when the state trajectory of system enters in some boundary layer around the sliding surface. Extensive simulations and experiments on healthy and paraplegic subjects are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed neuroadaptive SMC. The results show that the neuro-SMC provides accurate tracking control with fast convergence for different reference trajectories and could generate control signals to compensate the muscle fatigue and reject the external disturbance.     

A decentralized indirect adaptive control for a class oftwo-time-scale nonlinear systems with application to flexible-jointmanipulators

In this paper, the problem of an indirect adaptive decentralized control for a class of two-time scale interconnected systems is considered. The concept of an integral manifold is first utilized to construct the dynamics of corrected slow subsystems. Fast subsystems are also constructed to represent the dynamics of the fast modes. A composite control scheme based on full state feedback is then developed to guarantee stability and robustness of the closed-loop system. The controller is designed by taking into account the effects of unmodeled dynamics, identification errors, and parameter variations. Stability analysis of the resulting closed-loop full-order system subject to the composite controller is presented. To demonstrate the application of the proposed algorithm, an example of a two-link flexible-joint manipulator is considered. Simulation results are provided to validate the applicability of the proposed control scheme     

Indirect sliding mode control based on gray-box identification method for pneumatic artificial muscle

We present an indirect robust nonlinear controller for position-tracking control of a pneumatic artificial muscle (PAMs) testing system. The system modeling is reviewed, for which the existence of uncertain, unknown, and nonlinear terms in the internal dynamics is presented. From the obtained results, an online identification method is proposed for estimation of the internal functions with learning rules designed via a Lyapunov derivative function. A robust nonlinear controller is then designed based on the approximated functions to satisfy the control objective under the sliding mode technique. Appropriate selection of the smooth robust gain and the sliding surface ensures convergence of the tracking error to a desired level of performance. Stability of the closed-loop system is proven through another Lyapunov function. The proposed approach is verified and compared with a conventional proportional–integral–differential (PID) controller, adaptive recurrent neural network (ARNN) controller, and robust nonlinear controller in a real-time system with three different kinds of trajectories and loading. From the comparative experimental results, the effectiveness of the proposed method is confirmed with respect to transient response, steady-state behavior, and loading effect.     

Finite-time tracking controller design for nonholonomic systems with extended chained form

A design scheme of the finite-time tracking controller is given for the nonholonomic systems with extended chained form. The relay switching technique and the terminal sliding mode control scheme with finite-time convergence are used to the design of the controller. The global stability is guaranteed and the system states accurately track the states of the reference model in finite time. The simulation results for two physical models of a knife-edge and a wheeled mobile robot have demonstrated the effectiveness of the proposed algorithm.     

Neuro-Fuzzy Dynamic-Inversion-Based Adaptive Control for Robotic Manipulators—Discrete Time Case

In this paper, we present a stable discrete-time adaptive tracking controller using a neuro-fuzzy (NF) dynamic-inversion for a robotic manipulator with its dynamics approximated by a dynamic T-S fuzzy model. The NF dynamic-inversion constructed by a dynamic NF (DNF) system is used to compensate for the robot inverse dynamics for a better tracking performance. By assigning the dynamics of the DNF system, the dynamic performance of a robot control system can be guaranteed at the initial control stage, which is very important for enhancing system stability and adaptive learning. The discrete-time adaptive control composed of the NF dynamic-inversion and NF variable structure control (NF-VSC) is developed to stabilize the closed-loop system and ensure the high-quality tracking. The NF-VSC enhances the stability of the controlled system and improves the system dynamic performance during the NF learning. The system stability and the convergence of tracking errors are guaranteed by the Lyapunov stability theory, and the learning algorithm for the DNF system is obtained thereby. An example is given to show the viability and effectiveness of the proposed control approach     

Experimental implementation of spatial H/sub /spl infin// control on a piezoelectric-laminate beam

This paper is aimed to develop a feedback controller that suppresses vibration of flexible structures. The controller is designed to minimize the spatial H/sub /spl infin// norm of the closed-loop system. This technique guarantees average reduction of vibration throughout the entire structure. A feedthrough term is incorporated into the truncated flexible-structure model to compensate for the neglected dynamics in the finite-dimensional model. Adding the feedthrough term reduces the uncertainty associated with the truncated model, which is instrumental in ensuring the robustness of the closed-loop system. The controller is applied to a simply-supported piezoelectric-laminate beam and is validated experimentally to show the effectiveness of the proposed controller in suppressing structural vibration. It is shown that the spatial H/sub /spl infin//. control has an advantage over the pointwise H/sub /spl infin// control in minimizing the vibration of the entire structure. This spatial H/sub /spl infin// control methodology can also be applied to more general structural vibration suppression problems.     

Digital repetitive learning controller for three-phase CVCF PWMinverter

In this paper, a plug-in digital repetitive leaning control scheme is proposed for three-phase constant-voltage constant-frequency (CVCF) pulsewidth modulation inverters to achieve high-quality sinusoidal output voltages. In the proposed control scheme, the repetitive controller (RC) is plugged into the stable one-sampling-ahead-preview-controlled three-phase CVCF inverter system using only two voltage sensors. The RC is designed to eliminate periodic disturbance and/or track periodic reference signal with zero tracking error, The design theory of plug-in repetitive learning controller is described systematically and the stability analysis or overall system is discussed. The merits of the controlled systems include features of minimized total harmonic distortion, robustness to parameter uncertainties, fast response, and fewer sensors. Simulation and experimental results are provided to illustrate the effectiveness of the proposed scheme     

Enhancement of tracking ability in piezoceramic actuators subject to dynamic excitation conditions

An operator representing the inverse dynamics of hysteretic effects inherent to piezoceramic actuators is used to enhance the tracking accuracy of a piezoceramic-driven positioning system when subject to dynamic reference input signals covering a wide frequency range. An open-loop tracking controller and a closed-loop tracking controller are developed based on the new inverse algorithm and are experimentally shown to achieve high-accuracy tracking control.     

New robust adaptive control algorithm for high-performance ACdrives

This paper presents a new robust structure for a model reference adaptive control (MRAC) controller for field-oriented-controlled (FOC) drives which requires no prior knowledge of the drive parameters and is guaranteed to provide global asymptotic stability of the closed-loop system. This structure simplifies the design and implementation of the adaptive controller requiring less effort to synthesis than a standard MRAC system. Discussion on theoretical aspects, such as selection of a reference model, stability analysis proof, gain adaptive process, steady-state error elimination, and robustness to unmodeled dynamics are included. The paper describes many practical aspects of the implementation, such as adaptive gain analysis, adaptive rate selection, the gain variation limits, gain windup prevention measure, and initial values. The new robust adaptive controller has been successfully implemented on an FOC drive and experiment results for dynamic tracking, sudden loading and unloading, and gains adaptation under different operation conditions are presented to support the robustness of the proposed controller     

A learning scheme for low-speed precision tracking control of hybrid stepping motors

Servo control of the hybrid stepping motor is complicated due to its highly nonlinear torque-current-position characteristics, especially under low operating speeds. This paper presents a simple and efficient control algorithm for the high-precision tracking control of hybrid stepping motors. The principles of learning control have been exploited to minimize the motor's torque ripple, which is periodic and nonlinear in the system states, with specific emphasis on low-speed situations. The proposed algorithm utilizes a fixed proportional-derivative (PD) feedback controller to stabilize the transient dynamics of the servomotor and the feedforward learning controller to compensate for the effect of the torque ripple and other disturbances for improved tracking accuracy. The stability and convergence performance of the learning control scheme is presented. It has been found that all error signals in the learning control system are bounded and the motion trajectory converges to the desired value asymptotically. The experimental results demonstrated the effectiveness and performance of the proposed algorithm.     

Adaptive coupling control for overhead crane systems

Due to the requirements of high positioning accuracy, small swing angle, short transportation time, and high safety, both motion and stabilization control for an overhead crane system becomes an interesting issue in the field of control technology development. Since the overhead crane system is subject to underactuation with respect to the load sway dynamics, it is very hard to manipulate the crane system in a desired manner, namely, gantry position tracking and sway angle stabilization. Hence, in this paper, a nonlinear control scheme incorporating parameter adaptive mechanism is devised to ensure the overall closed-loop system stability. By applying the designed controller, the position error will be driven to zero while the sway angle is rapidly damped to achieve swing stabilization. Stability proof of the overall system is given in terms of Lyapunov concept. To demonstrate the effectiveness of the proposed controller, results for both computer simulation and experiments are also shown.     

Sliding mode control combined with extended state observer for an ankle exoskeleton driven by electrical motor

A novel sliding mode control combined with extended state observer (ESO) is proposed for an ankle exoskeleton driven by electrical motor. During the process of assisting, it is necessary to design an effective controller for assisting torque of ankle exoskeleton. However, the parameter uncertainty of complex dynamics model and the irregular motion of human ankle may affect the torque control accuracy. For a high control precision of assisting torque when facing the modeling uncertainty, the sliding mode control is employed, but a large switching gain is usually needed in order to suppress the disturbance, which cause the control signal vibrate greatly. ESO can observe and suppress the disturbance and modeling uncertainty, but its tracking performance needs to be improved. Therefore, the proposed complex controller takes the advantages of sliding mode control and extended state observer, which can not only improve torque tracking performance but also overcome the disturbance force caused by the change of human joint angle without increasing chattering of control signal. Experimental studies are carried out to validate the effectiveness of the proposed control. The results show the presented controller have better torque tracking performance and robustness stability, and the proposed controller can reduce the chattering compared with the tradition sliding mode control.     

Robust force control with a feed-forward inverse model controller for electro-hydraulic control loading systems of flight simulators

A hybrid control strategy for an electro-hydraulic control loading system (EHCLS) of a flight simulator in the presence of a control mechanism kinetic parameter perturbation is proposed to improve the force tracking accuracy and guarantee robust stability of the EHCLS system. A double-loop model of the EHCLS, including the control mechanism and the hydraulic mechanism, is established and analyzed from the force-displacement impedance perspective. A force closed-loop parameter model of the EHCLS is identified by a recursive-least-squares (RLS) algorithm and its inverse model is designed using a zero phase error compensation technology to expand the frequency bandwidth of the force closed-loop system of the EHCLS. A μ theory of robust control is employed to design a stable controller for enhancing robust stability of the EHCLS in the presence of uncertainties of the inner loop, the control mechanism and the high frequency disturbance force. Simulation and experimental results show that the proposed hybrid control approach can greatly improve the control performance of the EHCLS by expanding the frequency bandwidth of the force closed-loop system and enhancing stability of the EHCLS, which can decrease displacement output response error of the EHCLS from 10.34% to 3.1%.     

Time delay control with state feedback for azimuth motion of thefrictionless positioning device

A time delay controller with state feedback is proposed for azimuth motion control of the frictionless positioning device which is subject to the variations of inertia in the presence of measurement noise. The time delay controller, which is combined with a low-pass filter to attenuate the effect of measurement noise, ensures the asymptotic stability of the closed-loop system. It is found that the low-pass filter tends to increase the robustness in the design of the time delay controller, as well as the gain and phase margins of the closed-loop system. Numerical and experimental results support that the proposed controller guarantees a good tracking performance, irrespective of the variation of inertia and the presence of measurement noise     

Robust motion controller design for high-accuracy positioningsystems

This paper presents a controller structure for robust high speed and accuracy motion control systems. The overall control system consists of four elements: a friction compensator; a disturbance observer for the velocity loop; a position loop feedback controller; and a feedforward controller acting on the desired output. A parameter estimation technique coupled with friction compensation is used as the first step in the design process. The friction compensator is based on the experimental friction model and it compensates for unmodeled nonlinear friction. Stability of the closed-loop is provided by the feedback controller. The robust feedback controller based on the disturbance observer compensates for external disturbances and plant uncertainties. Precise tracking is achieved by the zero phase error tracking controller. Experimental results are presented to demonstrate performance improvement obtained by each element in the proposed robust control structure     

Adaptive robust fast control for induction motors

A new induction motor position controller that exhibits fast response and robustness is proposed. The control strategy is based on the well-known linear quadratic regulator design principle. By adaptively adjusting a penalty parameter, it is shown that the control strategy enables the induction motor system to exhibit fast convergence. Meanwhile, since the sliding mode will occur in the transient process, the fast control inherits the robustness in matched uncertainties of the sliding-mode control. In addition, to alleviate the chattering effect of the switching control signal, a low-pass filter is used to smooth the control and its design is integrated with the switching control design. The performance of the proposed control strategy is verified by experimental results