Precise Tracking Control Research Articles

Realization of High Fidelity Power-Hardware-in-the-Loop Capability Using a MW-Scale Motor-Generator Set

Power-hardware-in-the-loop (PHIL) is a vital technique for realistic testing of prototype systems. While the application of power electronics-based amplifiers to enable PHIL capability has been widely reported, the use of motor-generator (MG) sets as the PHIL interfaces has not been fully investigated. This article presents the realization of the first MW-scale PHIL setup using an MG set as the power amplifier, which offers a promising solution for testing novel systems for the integration of distributed energy resources. Uniquely, this article presents a methodology that introduces augmented frequency and phase control loops that can be integrated to commercially-available MG set's existing frequency controller for precise frequency and phase tracking. Internal model control is used for the controllers design and tuning. The developed control algorithm is tested in a MW-scale MG set that couples a Great Britain (GB) transmission network model simulated in a real time simulator to an 11 kV distribution network. Experimental results are presented, which demonstrate that the proposed control methodology is highly effective in maintaining the synchronization between the simulated and physical systems, thereby capable of enabling the MG set as a PHIL interface.

Attitude Control of a Small Spacecraft via Tube-Based Model Predictive Control

Precise attitude tracking control of small satellites is a demanding task due to the limited hardware resources of sensors, actuators, and processors equipped on board. Moreover, the effects of model uncertainty and persistent disturbance, such as gravity-gradient, magnetic, aerodynamic, and solar radiation pressure torques, on the satellite dynamics make the attitude control of miniaturized spacecraft more challenging. Consequently, under actuator limitations and stringent pointing requirements, robust controllers represent a more reliable solution to comply the mission constraints. In this paper, a tube-based robust model predictive control algorithm is exploited to address robust attitude control of CubeSat within an Earth-observation scenario, and its performance is evaluated. The proposed algorithm successfully achieves the three-axis stabilization required by the payload, using reaction wheels and applying constraints on the actuator torque and speed saturation as well as on pointing accuracy. To properly estimate the effectiveness of the proposed approach, the comparison with a nonlinear model predictive control is presented with the consideration of different sample times. The robustness of these two control schemes is then compared running 100 simulations, each one with random initial condition. The results demonstrate the effectiveness of the proposed robust algorithm for precise attitude tracking control of small satellites.

Repetitive Control Meets Continuous Zero Phase Error Tracking Controller for Precise Tracking of B-Spline Trajectories

In this paper, a novel repetitive control scheme is presented and discussed, based on the so-called B-spline filters. These dynamic filters are able to generate a B-spline trajectory if they are fed with the sequence of control points defining the curve. Therefore, they are ideal tools for generating online reference signals with the prescribed level of smoothness for driving dynamic systems, possibly together with a feedforward compensator. In particular, a continuous zero phase error tracking controller (ZPETC) can be used for tracking control of nonminimum phase systems but because of its open-loop nature it cannot guarantee the robustness with respect to modeling errors and exogenous disturbances. For this reason, ZPETC and trajectory generator have been embedded in a repetitive control scheme that allows to nullify interpolation errors even in nonideal conditions, provided that the desired reference trajectory and the disturbances are periodic. This paper is based on the results presented in the conference paper [L. Biagiotti, F. Califano, and C. Melchiorri, “Repetitive control of non-minimum phase systems along b-spline trajectories,” in Proc. IEEE 55th Conf. Decis. Control , 2016, pp. 5496–5501.], where asymptotic stability of the overall control scheme has been proved mathematically, but extends such results with an experimental validation based on a nonminimum phase system. Different models of the same physical system have been identified and used in the implementation of this model-based control scheme, allowing a real evaluation of the relationship between control system performance and model accuracy.

Feedforward Control of the Rate-Dependent Viscoelastic Hysteresis Nonlinearity in Dielectric Elastomer Actuators

Dielectric elastomer actuators have shown promising applications in the field of soft robotics. However, due to their rate-dependent viscoelastic hysteresis nonlinearity, it is still challenging to achieve precision tracking control of dielectric elastomer actuators. In this letter, we propose a feedforward control approach that can compensate for the rate-dependent viscoelastic hysteresis nonlinearity with maximum tracking errors of 6.18% and root-mean-square errors of 2.96% when the frequency of the input voltage is between 0.05 Hz and 1.5 Hz. Our control approach consists of two feedforward compensators: 1) for the ease of the hysteresis compensation, a creep compensator is firstly developed to remove the viscoelastic creep nonlinearity; 2) based on a phenomenological mathematical model, an inverse hysteresis compensator is then developed to compensate for the rate-dependent viscoelastic hysteresis nonlinearity. Experimental results of tracking various periodic trajectories demonstrate that: the maximum tracking errors are reduced by 87.17% and the root-mean-square errors are decreased by 89.53%, by comparing the results without the viscoelastic compensation. It is the first time to successfully compensate for both the viscoelastic creep nonlinearity and rate-dependent hysteresis nonlinearity of dielectric elastomer actuators by a feedforward control approach, which may pave the way for further applications in dielectric-elastomer-actuators based soft robotics.

A general approach to precise tracking of nonlinear systems subject to non-vanishing uncertainties

In this work we introduce a new and systematic methodology for precise tracking control of normal-form nonlinear systems subject to non-vanishing/non-parametric uncertainties. We propose a general solution to achieving robust tracking with a rate of convergence that can be pre-assigned as fast as desired (e.g. super exponential or even closer to a pre-specified finite time). The key design tool is the utilization of a time-varying feedback gain through a time-varying scaling function that satisfies certain conditions. Our method also features with complete rejection (rather than partial attenuation) of uncertainties/disturbances and regulation of the tracking error to zero. A generic and analytical procedure to construct the time-varying rate function is provided, extending and generalizing the existing results in the literature.

Adaptive finite‐time neural network control for redundant parallel manipulators

AbstractThis paper reports our study of an adaptive finite‐time neural network control scheme for redundant parallel manipulators. The proposed controller is based on fully tuned radial basis function neural networks (RBFNs), nonsingular fast terminal sliding mode control (NFTSMC), and nonlinearities in output feedback. RBFNs with a fully online update on the output weights and both the centers and variances of Gaussian functions are used to estimate system uncertainties and disturbances. The proposed approach possesses several advantages over other existing approaches like robustness, rapid response, nonsingularity, higher precision, finite‐time convergence, and better tracking control performance. The stability of the parallel manipulators is ensured by the Lyapunov theory. Finally, simulation results validate the effectiveness of the proposed methodology.

Dynamic modeling and terminal sliding mode control of a 3-DOF redundantly actuated parallel platform

An improved 3-degrees-of-freedom (DOF) redundantly actuated parallel platform (RAPP) has been designed to adjust the pose of heavy-loaded and large-scaled equipment. This paper presents the dynamic modeling and controller designing of the 3-DOF parallel mechanism. According to the specific structure and characteristics, the proposed mechanism is considered as a multibody system, whose dynamic model is formulated via Lagrange's Equations. On the foundation of dynamics analysis, a control strategy based on the terminal sliding mode is presented to achieve precise motion tracking control. The simulation results indicate that the designed controller not only makes an improvement on the trajectory tracking ability, but also enhances the robustness under constantly changing parameters and disturbance. Experiments are also conducted on the pose adjustment prototype system to validate the RAPP's performance and assess the control method.

Terminal sliding mode control of rail pressure for gasoline direct injection engines

The desired fuel rail pressure is a crucial factor for guaranteeing the gasoline direct injection (GDI) engine to work stably. In order to solve the rail pressure control problem, the detailed nonlinear model of GDI is derived and reasonable simplification of this model is carried out for the following controller design. Terminal sliding mode control strategy is proposed to design the rail pressure controller with Lyapunov stability. The designed approach with the fast terminal sliding mode surface makes the system have the capacity of global fast convergence and achieves precise tracking control. To demonstrate the validity of the designed control method, simulations are conducted by tracking the different reference rail pressures. Results show that the designed controller tracks the given reference accurately and has strong robustness.

Indirect Adaptive Robust Trajectory Tracking Control of Hard Rock TBM with Load Variation of Tunneling Face

Posture adjustment of open-type hard rock tunnel boring machine (TBM) can be achieved by properly adjusting the hydraulic pressure of gripper cylinder and torque cylinders. However, the time-varying inhomogeneous load acting on tunneling face of TBM and complex stratum working condition can cause the trajectory deviation. In this paper, the position and posture rectification kinematics and dynamics models of TBM have been established in order to track the trajectory. Moreover, there are uncertain parameters and uncertain loads from complex working conditions in the dynamic model. An indirect adaptive robust control strategy is applied to achieve precise position and posture trajectory tracking control. Simulation results show when the position deviation only occurs in Y-axis and the current orientation is parallel with the designed axis, the deviation can be corrected by controlling the pressure of gripper cylinder and the actual trajectory meets the designed axis when TBM is pushed forward 0.14 m in X-axis. If the deviation only occurs in Z-axis, then the deviation can be corrected by controlling torque cylinders. If the position deviation occurs both in Y-axis and Z-axis at the same time, the pressure of gripper cylinder and torque cylinders should be controlled at the same time to rectify the deviation. Simulation results are shown to illustrate the effectiveness and robustness of the proposed controller. This research proposes an indirect adaptive robust controller that can track the planned tracking trajectory smoothly and rapidly.

Precise Position Tracking Control With an Improved Transient Performance for a Linear Piezoelectric Ceramic Motor

In this paper, an output feedback position tracking control problem relevant for a linear piezoelectric ceramic motor is studied. The main goals of the control design include achieving extremely high resolution, accuracy, stability, and improved transient performance when system uncertainties, unknown dynamics, and external disturbances act on the system. The proposed control approach is designed in such a way that the implementation of the high-precision micro/nanopositioning is possible. An adaptive sliding-mode-based scheme is adopted to synthesize a robust controller. Stability analysis of the control approach is performed and it is analytically shown that the position tracking error asymptotically converges to zero. The important advantages of this control approach are: 1) designing a controller without the requirement of prior knowledge about uncertainty/disturbance bounds; 2) having a chattering-free control input; and 3) obtaining a fast response without overshoot. The proposed control strategy was experimentally validated and compared to the existing control approaches.

Energy efficiency improvement of heavy-load mobile hydraulic manipulator with electronically tunable operating modes

The conventional hydraulic drive system for a heavy-load mobile manipulator is usually operated under single mode, such that both inlet/outlet and potential energy losses are large to lower the energy efficiency. In this paper, a novel electro-hydraulic drive system is presented to improve energy efficiency. Extended control degrees of freedom are obtained utilizing the independent metering valve and electronic controlled pump. Then, multiple operating modes are carried out pertaining to the cylinder, valve, and pump. To achieve both optimal energy efficiency and precise motion tracking, both multi-mode switching and multi-variable controller are designed to accommodate with time-varying and uncertain load characteristics. As a consequence, the inlet, outlet, and potential energy losses can be decreased simultaneously. The experimental validation is conducted by using a three-joint manipulator in a 2 t excavator. A duty cycle of movement including all three actuators and covering full load quadrants is used to evaluate the efficiency improvement. Compared with the conventional load sensing system, the proposed multi-mode switching system using the pump pressure with valve meter-in control mode yields a 25.8% energy-saving ratio. Furthermore, the pump flow with valve mete-out control mode yields a 35.3% energy-saving ratio. Using this combined control mode, higher efficiency can be obtained due to the minimum inlet losses, but faster dynamic response together with higher overshoot will appear. It is proved that the energy efficiency is improved, while the motion tracking performance is not degraded by introducing the multi-mode switching.

Identification and adaptive multi‐dimensional Taylor network control of single‐input single‐output non‐linear uncertain time‐varying systems with noise disturbances

In this paper, an adaptive control approach based on the multi-dimensional Taylor network (MTN) is proposed to control the non-linear uncertain time-varying systems with noise disturbances. MTNs are introduced to formulate adaptive filtering, non-linear identification and optimal control. First, an MTN filter is developed to eliminate the control interference and measurement noise, so that the model output without stochastic disturbance can be obtained. Then, an MTN identifier (MTNI) is so designed as to be capable of dynamic mapping and require fewer weights than traditional neural networks. On the basis of the above, the MTN controller (MTNC) is developed to realise the precise tracking control of the system. The non-linear uncertain time-varying system is identified by MTNI, which then provides sensitivity information of the plant to MTNC to make it adaptive. Furthermore, the skeletonisation algorithm is adopted to remove redundant inputs and redundant regression items from MTNI and MTNC for concise MTNs. Successful convergence and faster learning are guaranteed using the Lyapunov theorem, and the optimal learning rates are identified. Simulation results demonstrate that the proposed approach features its accurate identification, excellent tracking and better anti-interference capability for the adaptive real-time control of uncertain, stochastic and time-varying non-linear systems.

Sliding Mode Force Control of an Electrohydraulic Servo System with RBF Neural Network Compensation

In this paper, the dynamics of an electrohydraulic servo system is analyzed. It is difficult to achieve the precise force tracking control due to its high nonlinearities and parameter uncertainties. For the accurate force tracking control, a sliding mode control algorithm with radial basis function (RBF) neural network compensation was proposed. The theory verifies that the algorithm is globally asymptotically stable. The experimental results show that the proposed algorithm is not only effective and better than the PID control in the force tracking control, but also robust to external uncertain disturbances. DOI: http://dx.doi.org/10.5755/j01.mech.25.1.21279

Adaptive Sliding Mode Disturbance Observer-Based Composite Control With Prescribed Performance of Space Manipulators for Target Capturing

The requirements for the control performances of space manipulators, especially for the stability and accuracy of the attitude control systems of the base spacecrafts, are ever increasing during the space target capturing tasks. However, the system uncertainties caused by parameter variations will degrade the system performances severely. This paper investigates the precise and fast trajectory tracking control problem for the free-flying space manipulator, after capturing a space target with uncertain mass. To compensate the system uncertainty with complex and uncertain dynamics, a novel adaptive sliding mode disturbance observer (ASMDO) is proposed. Then, a composite controller with prescribed transient and steady-state performances is developed. It is proved that the estimation error of ASMDO can be stabilized in finite-time, though the bound of the derivative of system uncertainty is unknown. Meanwhile, the trajectory tracking error can also be stabilized in finite-time and has preassigned maximum overshoot and steady-state error. Finally, numerical simulations and experimental studies are presented to demonstrate the effectiveness of proposed methods.

Identification of a Dynamic Friction Model and Its Application in a Precise Tracking Control

Identification of a Dynamic Friction Model and Its Application in a Precise Tracking Control

Adaptive Nonsingular Terminal Sliding Mode Backstepping Control for the Speed and Tension System of the Reversible Cold Strip Rolling Mill Using Disturbance Observers

In order to weaken the influences of system uncertainties and coupling items on the coordinated tracking control performance of the speed and tension system of the reversible cold strip rolling mill, an adaptive nonsingular terminal sliding mode (ANTSM) backstepping control strategy using disturbance observers is proposed. First, time-varying gain extended state observers (TVGESOs) are constructed to dynamically observe the system's mismatched uncertainties, which weaken the initial peak phenomenon of the traditional extended state observer (ESO), and effectively improve the system's tracking control precision. Next, based on the backstepping control and the second order sliding mode integral filters, adaptive nonsingular terminal sliding mode controllers (ANTSMCs) for the speed and tension system of the reversible cold strip rolling mill are designed, which solve the “differential explosion” problem of conventional backstepping control, and make sliding mode variables converge in finite time. Again, neural network adaptive method is used to approximate the system's matched uncertainties, and the approximation values are introduced into the designed controllers for compensations. Finally, simulation research is carried out on the speed and tension system of a 1422 mm reversible cold strip rolling mill by using actual data, and the results show the validity of the proposed control strategy.

Sliding mode control with PI-based saturation for nano-positioning

This paper proposes a modified sliding mode controller with proportion-integral (Pl)-based saturation (PISSMC) for nano-positioning of Piezoelectric Actuators (PEAs). Based on the sliding mode theory, the controller can consider hysteresis as the uncertainty of the system, which the non-linearities of hysteresis and model imperfection can be processed to achieve precise positioning and tracking control. The PI term of this controller can decrease the steady-state error of the system and alleviate the chattering of the discontinuous part of the Sliding Mode Controller (SMC). Further, as the only measurable information is the position state, a high-gain observer is adopted to estimate the other states. The designed controller employs a linear PEA system as parameters estimation of the model to estimate the control gain and compensate for the process non-linearity. The robust stability of the PISSMC is proved through a Lyapunov stability analysis. Experimental results demonstrate that compared with the traditional SMC, the proposed controller can accomplish better control performance, such as more accurate resolution, less steady-state error and slighter chattering.

Adaptive Discrete-Time Estimated Inverse Control for Piezoelectric Positioning Stage

This article aims at designing an adaptive estimated inverse control scheme to realize precise tracking control for a class of discrete-time nonlinear system with hysteresis nonlinearities. To this end, firstly, the dynamic surface control technology with digital first-order low-pass filter is designed and the original control system does not need to be transformed into an unknown special form. Then, the procedures of the controller design are greatly simplified. Secondly, the hysteresis nonlinearity is mitigated by constructing an discrete-time estimated inverse hysteresis compensator. Finally, the validity of the proposed adaptive control scheme is verified by the computer control experiments on a hardware-in-the-loop simulation platform. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SUUB).

Practical adaptive fractional‐order nonsingular terminal sliding mode control for a cable‐driven manipulator

SummaryFor the high precise tracking control purpose of a cable‐driven manipulator under lumped uncertainties, a novel adaptive fractional‐order nonsingular terminal sliding mode control scheme based on time delay estimation (TDE) is proposed and investigated in this paper. The proposed control scheme mainly has three elements, ie, a TDE element applied to properly compensate the lumped unknown dynamics of the system resulting in a fascinating model‐free feature; a fractional‐order nonsingular terminal sliding mode (FONTSM) surface element used to ensure high precision in the steady phase; and a combined reaching law with adaptive technique adopted to obtain fast convergence and high precision and chatter reduction under complex lumped disturbance. Stability of the closed‐loop control system is analyzed with the Lyapunov stability theory. Comparative simulations and experiments were performed to demonstrate the effectiveness of our proposed control scheme using 2‐DOF (degree of freedom) of a cable‐driven manipulator named Polaris‐I. Corresponding results show that our proposed method can ensure faster convergence, higher precision, and better robustness against complex lumped disturbance than the existing TDE‐based FONTSM and continuous FONTSM control schemes.

Tracking Control of Networked Multiple Linear Switched Reluctance Machines Control System Based on Position Compensation Approach

This paper proposes the precise tracking control for the multiple linear switched reluctance machines (LSRMs) with network-induced time delays by using the motor positions compensation method. Considering the mutual position disturbances among the multiple motors, two network topologies are proposed for the multiple LSRMs control system. In order to improve the tracking precision, the motor position signals are used to compensate the tracking errors among the three motors. The encoders-to-controller and the controller-to-actuator time delays are modeled as a discrete-time Markov chain which denotes the whole random time delay step for the closed-loop control system. The stability conditions and the tracking controller design method for the networked LSRMs control system are proposed by using Lyapunov theory and the inequality techniques. Several groups of experimental results are presented to verify the effectiveness and practicability of the proposed method for the networked multiple LSRMs control system.