Feedforward Parameters Research Articles

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

Feedforward control can significantly enhance the performance of motion systems through compensation of known disturbances. This paper aims to develop a new procedure to tune a feedforward controller based on measured data obtained in finite time tasks. Hereto, a suitable feedforward parametrization is introduced that provides good extrapolation properties for a class of reference signals. Next, connections with closed-loop system identification are established. In particular, instrumental variables, which have been proven very useful in closed-loop system identification, are selected to tune the feedforward controller. These instrumental variables closely resemble traditional engineering tuning practice. In contrast to pre-existing approaches, the feedforward controller can be updated after each task, irrespective of noise acting on the system. Experimental results confirm the practical relevance of the proposed method.

Triple Feed-forward APIOBPCS Based Resilience and Operational Costs Assessment of Supply Chain

In order to trade off between supply chain resilience and operational cost, a sort of triple feed-forward automatic pipeline, inventory and order-based production control system(TFF-APIOBPCS) is presented. A first order differential feedforward unit, introduced to production control model APIOBPCS, enables the model to mitigate the impact of fluctuations in demand on actual inventory. Aiming at different pole distribution of the production control system, analysis of the relationship between the parameters of first order differential feedforward and resilience are conducted under zero steady-state error. Supply chain operational cost model is constructed by comprehensive consideration of inventory cost and production regulation cost. Supply chain system simulations with a unit step signal and a stochastic signal as the customer demand evaluate the effect of the first order differential feedforward parameters on supply chain resilience and operational cost, and reveal the validity of TFF-APIOBPCS. The results show that, for different degree of volatility of demand, setting the parameters of first order differential feedforward unit reasonably, can obtain better equilibrium of elasticity and operation cost.

Adaptive pseudo-derivative feedback with a feed-forward gain controller for permanent magnet synchronous motor servo system based on integrated iterative learning control

This article proposes an adaptive pseudo-derivative feedback with a feed-forward gain controller based on the integrated iterative learning control for the permanent magnet synchronous motor servo system. At first, the improved just-in-time online model identification method is adopted to identify and linearize the nonlinear servo system to obtain the model information for the control strategy. Second, a model-based iterative learning control strategy is presented for the tracking control of permanent magnet synchronous motor servo system. Meanwhile, to guarantee the robust convergence of the iterative learning control system, a new tuning methodology considering the model uncertainties is proposed to select the weighting matrices of the iterative learning control. Third, to further improve control performance, an online generalized predictive control is integrated in the iterative learning control framework, referred to as integrated iterative learning control. By combining generalized predictive control and iterative learning control, the integrated iterative learning control can complement both control methods to obtain good performance, because online generalized predictive control can respond to disturbances immediately and iterative learning control can correct bias left uncorrected by the online controller. Finally, an adaptive pseudo-derivative feedback with a feed-forward gain controller is designed based on the integrated iterative learning control. Since the integrated iterative learning control can be expressed by the pseudo-derivative feedback with a feed-forward gain parameter, the design can achieve both performance improvement and simple controller structure. Experiments confirm the effectiveness of the proposed adaptive pseudo-derivative feedback with a feed-forward gain controller.

4WD mobile robot for autonomous steering using single camera based vision system

Purpose – The purpose of this paper is to demonstrate System-of-Systems (SoS) approach to design and development of unmanned robotic platform for greenhouse agricultural application. Design/methodology/approach – SoS design approach is important in developing engineering products. It was observed that while system integration considers designs in a multi-disciplinary level framework, SoS is viewed as a solution focussed approach. In this paper, the authors have demonstrated SoS approach to develop a mobile robot platform. The wheels of the platform are independently controlled by using brushless DC and stepper motors based on fieldbus type Distributed Control System scheme. Findings – The constraints for autonomous traveling were identified during the first phase followed by development of 12 distinct sub-routines during second phase of training. Optimal camera installation angle, driving speeds, steering angle per pixel were found to be valuable constraints for feed-forward parameters for real-time driving. The platform was field tested in a tomato planted greenhouse for yield and weed mapping. Research limitations/implications – The paper focusses on studying vision-based autonomous four-wheel-drive (4WD) constraints and their implementation limitations. Practical implications – The platform was field tested in a tomato planted greenhouse for yield and weed mapping. Social implications – The platform can be used for agricultural operations such as crop scouting, monitoring, spraying, and mapping in a medium to large-scale greenhouse setting. Originality/value – The research and presentation is original. Starting from its mechanical specification to wheel performance study, development of path patterns for training and global navigation algorithm for testing and validation were achieved. The platform can autonomously be driven without any manual intervention.

Design and implementation of a 2-DOF PID compensation for magnetic levitation systems

This paper employs a 2-DOF (degree of freedom) PID controller for compensating a physical magnetic levitation system. It is shown that because of having a feedforward gain in the proposed 2-DOF PID control, the transient performance of the compensated system can be changed in a desired manner unlike the conventional 1-DOF PID control. It is also shown that for a choice of PID parameters, although the theoretical loop robustness is the same for both the compensated systems, in real-time, 2-DOF PID control may provide superior robustness if a suitable choice of the feedforward parameter is made. The results are verified through simulations and experiments.

Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

Joint input shaping and feedforward for point-to-point motion: Automated tuning for an industrial nanopositioning system

Feedforward control can effectively compensate for the servo error induced by the reference signal if it is tuned appropriately. This paper aims to introduce a new joint input shaping and feedforward parametrization in iterative feedforward control. Such a parametrization has the potential to significantly improve the performance for systems executing a point-to-point reference trajectory. The proposed approach enables an efficient optimization procedure with global convergence. A simulation example and an experimental validation on an industrial motion system confirm (i) the performance improvement obtained by means of the joint input shaping and feedforward parametrization compared to pre-existing results, and (ii) the efficiency of the proposed optimization procedure.

Design of a PD Controller Combined with a MRAS-Based LFFC for a Two - Link Robot Manipulator

In this paper we introduce a new control structure which consists of a PD controller and a Model Reference Adaptive System-based Learning Feed-Forward Controller to a two-link robot manipulator. The proposed approach seeks to benefit the multi-variable control of multi-input multi-output systems with variable parameters, nonlinear behavior, and significant coupling in the system dynamics. Conventionally, the function approximators with standard neural networks were used which enabled to approximate complex non-linear functions. The idea of LFFC is applied but without using the complex neural networks. Instead, we propose to use MRAS-based adaptive components. The well-known Lyapunov approach is used to find stable adaptive laws for the feed-forward parameters in such way that learning converges. The effectiveness of the proposed approach is demonstrated by simulation analysis.

On the asymptotic hyperstability of switched systems under integral-type feedback regulation Popovian constraints

This paper deals with the asymptotic hyperstability of switched time-varying dynamic systems involving switching actions among linear time-invariant parametrizations in the feed-forward loop for any feedback regulator controller potentially being also subject to switching through time while being within a class which satisfies a Popov-type integral inequality. Asymptotic hyperstability is proved to be achievable under very generic switching laws if at least one of the feed-forward parametrization possesses a strictly positive real transfer function, a minimum residence time interval is respected for each activation time interval of such a parametrization and a maximum allowable residence time interval is simultaneously maintained for all active parametrizations which are not positive real, if any. In the case where all the feed-forward parametrizations possess a common Lyapunov function, asymptotic hyperstability of the switched closed-loop system is achieved under arbitrary switching.

A Fuzzy Control Method Combined with Optimal Feed-Forward for Dry Desulfurization of Slurry Fluidized Bed Boiler

It is the most effective resource use practices for coal slurry to be used as fuel for fluidized bed boiler. The dry desulfurization of slurry fluidized bed boiler is a large time delay system, and the load disturbance of this system changes frequently. In order to achieve stable control of SO2 emission and meet environmental requirements, a fuzzy control technology combined with the optimal feed-forward was designed. Combined with field experience, a fuzzy controller system was designed by fuzzy control technology, and then the integral process was added to achieve non-error track. To reduce the impact of desulfurizer and other factors, based on the principle of feed-forward, an objective to minimize disturbance impact was obtained, and then a nonlinear programming problem for solving the optimal feed-forward parameters was established, from which the best feed-forward form can be obtained. Results of 440T/H fluidized bed boiler show that the proposed method has satisfactory control effect. SO2 concentration can fully meet environmental emission requirements, and its fluctuation is relatively small.

A Dimmable High Power Factor Single-Switch Electronic Ballast for Compact Fluorescent Lamps With Incandescent Phase-Cut Dimmers

A novel dimmable high-power-factor compact fluorescent lamp (CFL) electronic ballast that is compatible with standard incandescent lamp dimmers is proposed in this paper. In the proposed system, the dimming controller uses the phase angle of the dimmer as the input feedforward parameter for the duty ratio control of the switch in the power circuit. As a result, a wide range of light output can be achieved with a small range of phase angles of the phase-cut dimmer. The ballast power circuit is a single-switch single-stage resonant inverter, which is essentially a fusion of a SEPIC converter and a single-switch current-fed inverter. Detailed operating principles of the proposed system will be discussed in this paper. System stability analysis that includes the effects of the phase-cut dimmer is also provided. Experimental results are given for a 13-W CFL to demonstrate and highlight the merits of the proposed work.

Linear Motor Velocity and Acceleration Motion Control Study Based on PID+Velocity and Acceleration Feedforward Parameters Adjustment

This paper adopts with a PMAC Programmable Multi-axis Controller to control a linear motor through adjusting PID + velocity and acceleration feedforward parameters of the control card. The motor can reach 50-nm precision at lower speed. The PLC real-time monitoring function of the software is used to monitor the actual pace of registers. The real-time online adjustment of PID parameters of the motor at various speeds is realized, which makes the motor reach high motion accuracy at various velocity and acceleration.

Application of Perfect 2 Degrees-of-Freedom Control System to Mechanical Apparatuses

The perfect 2 degrees-of-freedom control system was previously proposed in the field of plant control. Its feature is that an accurate mathematical model is not required on application. In other words, model-free is the strong point of this control. However, though recommended values against tuning parameters are presented, its reasons are not clarified. In addition, tuning method is not identified. In this paper firstly, though the application of the perfect 2-DOF to two kind of mechanical equipments, a tuning method is experimentally cleared and derived performance is presented. Next, it is shown that the derived tuning procedure agrees with the Kitamori's method. Finally, based on the zero assignment which is created by tuning the feedforward parameters, the shaping of positioning waveform becomes obvious. Especially, under the special set of these parameters, it becomes clear that the influence due to the vibratory pole can be loose.

Semianalytical transient solution of a delayed differential equation and its application to the tracking motion in the sensory-motor system

We derived semianalytically the transient solution of a delayed differential equation that had been shown to be a simple but good model of the sensory-motor system. In the present Brief Report, we applied this transient solution for studying the global nature of the transient tracking motion when visual target information is changed suddenly. The results clarified that the dynamic error minimization principle in hand motion observed experimentally is robust over a wide range of the parameter space of the delay time, the time constant, and the feedforward parameter.

Linguistic information feedforward-based dynamical fuzzy systems

In this paper, we first propose a linguistic information feedforward-based dynamical fuzzy system (LIFFDFS) in which the past fuzzy inference output represented by a membership function is fed forward locally with trainable parameters. Our LIFFDFS can overcome the common static mapping drawback of conventional fuzzy systems. We also give a detailed description of its underlying principle and general structure. Next, based on the gradient descent method, an adaptive learning algorithm for the feedforward parameters is derived. The proposed LIFFDFS is further employed in the prediction of time series. The well-known Box-Jenkins gas furnace data are used here as an evaluation example. Simulation results demonstrate that this new dynamical fuzzy system has the advantage of inherent dynamics and is, therefore, well suited for handling temporal problems, such as process modeling and control

Neural network control of functional neuromuscular stimulation systems

Functional Neuromuscular Stimulation (FNS) is a technique used for restoring the ability to stand and walk to individuals with neurological deficits of the lower extremities. Existing FNS systems operate by electrically activating a set of paralyzed muscles with a predetermined sequence of stimulus pulses, thus they operate in a open-loop or feed-forward (FF) mode. This work is directed at developing a procedure for customizing FF parameters and adapting them online. A neural network control system is described and evaluated in studies on a computer simulated musculoskeletal model. Results demonstrate the ability of the control system to customize and adapt the FF controller parameters on-line.

Low-sensitivity realization of switched-capacitor filters

Two low-sensitivity switched-capacitor filter structures implementing the strays-insensitive switched-capacitor biquads are presented. They are based on a generalized multiple-loop-feedback (GMF) topology, which is formed by the combination of the follow-the-leader-feedback (FLF) and inverse follow-the-leader-feedback (IFLF) topologies. Design equations that relate the feedback and feedforward parameters to the discrete-time transfer function are derived for both structures. Sensitivity analyses of the proposed structures as well as of the previously published ones are carried out using Monte Carlo simulations. It was found that the modified GMF structure possesses a lower sensitivity with respect to capacitance ratios.

Feedforward Control of Pure Transport Delay Processes

This paper is concerned with the investigation of a feedforward control approach for a class of industrial systems which can be adequately modeled as a pure transport delay. The feedforward control loop is assumed to contain a sensor and actuator both with appreciable dynamics) as well as the feedforward controller. For this class of problems it turns out that application of the standard feedforward control approach leads to controllers which are, from a practical standpoint, unrealizable. The problem arises because the standard approach is based on an attempt to exactly cancel the effects of input disturbances. An alternate design approach is discussed in which a simple and easily realizable controller structure is assumed, and the controller parameters are chosen so that a suitable measure of system performance achieves a satisfactory value. The performance measure used is based on the frequency function relating the input disturbance spectrum to the output spectrum. This approach leads to some simple guidelines for choosing the feedforward controller parameters.

Stability of commensalistic systems.

AbstractThe response of two‐species commensalistic systems in a chemostat has been investigated after perturbations in steady state conditions and after step changes in dilution rate. The system is inherently stable with not more than three overshoots and undershoots possible. More complicated commensalistic systems are less stable, with limit cycle response occurring after dilution rate changes when feedback inhibition and feedforward activation occurs. In general variation of feedback parameters is more effective in changing the behavior of the systems than variation of feedforward parameters. Limited agreement with the experimental data of Chao and Reilly was obtained.