Feedforward Control Design Research Articles

Feedforward boundary control of 2[formula omitted]2 nonlinear hyperbolic systems with application to Saint-Venant equations

Because they represent physical systems with propagation delays, hyperbolic systems are well suited for feedforward control. This is especially true when the delay between a disturbance and the output is larger than the control delay. In this paper, we address the design of feedforward controllers for a general class of 2×2 hyperbolic systems with a single disturbance input located at one boundary and a single control actuation at the other boundary. The goal is to design a feedforward control that makes the system output insensitive to the measured disturbance input. We show that, for this class of systems, there exists an efficient ideal feedforward controller which is causal and stable. The problem is first stated and studied in the frequency domain for a simple linear system. Then, our main contribution is to show how the theory can be extended, in the time domain, to general nonlinear hyperbolic systems. The method is illustrated with an application to the control of an open channel represented by Saint-Venant equations where the objective is to make the output water level insensitive to the variations of the input flow rate. Finally, we address a more complex application to a cascade of pools where a blind application of perfect feedforward control can lead to detrimental oscillations. A pragmatic way of modifying the control law to solve this problem is proposed and validated with a simulation experiment.

Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder

This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed controller, with an 80% reduction in RMS cylinder position error, and that the separate feedforward states are able to adapt to model uncertainties in both directions of motion.

Design of the state feedback-based feed-forward controller asymptotically stabilizing the double-pendulum-type overhead cranes with time-varying hoisting rope length

Abstract In this paper we focus our attention on the design of the feedback-based feed-forward controller asymptotically stabilizing the double-pendulum-type (D-P-T) crane system with the time-varying rope length in the desired end position of payload (the origin of the coordinate system). In principle, two cases are considered, in the first case, the sway angle of payload is uncontrolled and second case, when the sway angle of payload is controlled by an external force. Precise mathematical modeling in the framework of Lagrange formalism without the traditional neglect of the important structural parameters of the D-P-T crane system and numerical simulation in the Matlab environment indicate the substantial reduction of the transportation time to the desired end position.

MIMO multirate feedforward controller design with selection of input multiplicities and intersample behavior analysis

Inversion-based feedforward control is a basic method of tracking controls. The aim of this paper is to design MIMO multirate feedforward controller that improves continuous-time tracking performance in MIMO LTI systems considering not only on-sample but also intersample behavior. Several types of MIMO multirate feedforward controllers are designed and evaluated in terms of the 2-norm of the control inputs. The approach is compared with a conventional MIMO single-rate feedforward controller in simulations. The approach improves the intersample behavior through the optimal selection of input multiplicities with MIMO multirate system inversion.

Data-driven design of fault-tolerant control systems based on recursive stable image representation

Driven by the increasing needs in the process industry for designing fault-tolerant control systems based on process data and maintaining its performance during online operation, data-driven realization and design of feed-forward fault-tolerant control systems with embedded residual generation are studied. To this end, a parameterized and data-driven realization form of stable image representation in a feedback control loop is derived first. On this basis, a feed-forward controller design scheme is proposed for fault-tolerant purpose. It is followed by a recursive approach for online tuning the feed-forward controller in case of malfunctions, which is triggered by a fault detection scheme based on the so-called stable kernel representation. The effectiveness of the proposed fault-tolerant method is demonstrated by a case study on the laboratory three-tank system.

Cooperative adaptive optimal output regulation of nonlinear discrete-time multi-agent systems

This paper studies a cooperative adaptive optimal output regulation problem for a class of strict-feedback nonlinear discrete-time (DT) multi-agent systems (MASs) with partially unknown dynamics. Adaptive distributed observer, reinforcement learning (RL) and output regulation techniques are integrated to compute an adaptive near-optimal tracker for each follower. First, under the output regulation theory, the cooperative adaptive optimal output regulation problem is decomposed into a feedforward control design problem which can be addressed by solving nonlinear regulator equations, and an adaptive optimal feedback control problem. Different from general adaptive optimal stabilization problem of nonlinear DT systems, the value function of the optimal output regulation problem is positive semidefinite. This paper analyzes the stability of the closed-loop system without relying on the Lyapunov stability theory and also proposes a policy iteration (PI) approach to approximate the value function with the convergence proof. Then, an adaptive distributed observer is designed for each follower so that they can estimate the state of the leader. A model-state-input structure is developed to find the solutions to regulator equations for each follower and a critic–actor structure is employed to solve the optimal feedback control problem using the measured data based on the neural network (NN) and RL. It is shown that using the estimate values, the tracking errors are uniformly ultimately bounded. A simulation example is given to show the effectiveness of the proposed method.

Data-Driven Design of Feedforward Controllers with Performance Guarantee

Data-Driven Design of Feedforward Controllers with Performance Guarantee

A novel smart assistive knee brace incorporated with shape memory alloy wire actuator

The knee plays a significant role in locomotion and stability of the entire body through supporting the body weight and assisting the lower body kinematics during walking. However, the knee is at constant risk of becoming weakened due to disease, age, and accidents. One approach to treating weakened knee is wearing an assistive knee brace. To design a clinical knee brace, many factors such as weight and compliant mechanism should be considered. In this study, a novel smart assistive knee brace mechanism incorporated with wire actuators made of shape memory alloys is proposed to ameliorate the issues associated with weight and flexibility of existing brace designs. Unlike earlier studies, the proposed orthosis includes pressure sensor, shape memory actuator, and smart linkage. Furthermore, two distinct shape memory alloy actuator design concepts with improved stiffness are developed, and the best option is chosen systematically and prototyped. The novel mechanism proposed in this research overcomes the weight of the lower limb during swing phase using the combined shape memory alloy actuation and feed-forward controller design. As such, it can be used as a potential replacement to its conventional counterparts when the higher weight reduction as well as a flexible and controllable mechanism are simultaneously sought.

An Iterative Approach for Accurate Dynamic Model Identification of Industrial Robots

Dynamic model has broad applications in motion planning, feedforward controller design, and disturbance observer design. Particularly, with the increasing application of model-based control in industrial robots, there has been a resurgence of research interest in accurate identification of dynamic models. However, on the one hand, most existing identification methods directly rely on least squares or weighted least squares (WLS), which suffer from outliers and could lead to physical infeasible solutions. On the other hand, nonlinearity of the friction model is seldom treated in a unified way with linear regression. Moreover, recent researches have shown that proper exciting trajectories are crucial to the identification accuracy, but few of previous works take measurement noise into consideration when optimizing the exciting trajectories. In this article, we propose an iterative approach which integrates WLS, iteratively reweighted least squares with linear matrix inequality constraints, and nonlinear friction models so that the above-mentioned issues can be properly solved altogether. Our research also reveals that performance can be improved by including priori knowledge of measurement noise in the optimization of exciting trajectories. The proposed approach is supported by experimental analysis of four different combinations within the framework on a 6-DoF industrial robot.

Interval-Based Modeling of High-Temperature Fuel Cells for a Real-Time Control Implementation Under State Constraints

Interval-based state estimation techniques represent promising approaches for the quantification of worst-case bounds of those sets of state variables that are reachable over a finitely long time horizon under the consideration of bounded uncertainty. In previous work, it has been shown that such estimation techniques cannot only be employed for the class of linear uncertain systems but also for nonlinear ones if they are reformulated in terms of quasi-linear state-space representations. However, naive polytopic uncertainty models may lead to quite conservative enclosures of the reachable states. Those, in turn, lead to conservative control strategies if the aforementioned interval enclosures are combined with strategies for the design of robust feedforward and feedback controllers. Therefore, this paper aims at the reduction of pessimism during interval-based state estimation by means of novel uncertainty models, relying on a parameter bounding approach that is implemented by means of a correlation analysis as well as a suitable principle axes transformation of the parameter space. The practical applicability of the proposed procedure is visualized for an experimentally validated thermal model of a solid oxide fuel cell stack, for which the computed interval bounds of reachable states represent a fundamental requirement for the design of a combined feedforward and feedback control allowing for preventing the violation of upper temperature limits in a guaranteed way.

Combined Feedforward Control and Disturbance Rejection Control Design for a Wafer Stage: A Data-Driven Approach Based on Iterative Parameter Tuning

This article presents a data-driven algorithm that combines the advantages of iterative feedforward tuning and disturbance rejection control to satisfy the precision requirements and ensure extrapolation capability of wafer scanning. The proposed algorithm differs from pre-existing algorithms in terms of its low requirement of system model, high extrapolation capability for non repetitive trajectory tracking tasks, and high tracking precision. The feedforward controller is tuned based on instrumental variables. It utilizes tracking errors from past iterations to eliminate reference-induced errors without requiring a system model. Meanwhile, the system inverse is approximated during iterative process, and then a disturbance rejection control based on iterative tuning is constructed to compensate for disturbance-induced errors. The proposed algorithm is applied to a wafer stage. The experimental results validate the effectiveness and superiority of the proposed algorithm.

Feedforward control design for shaking table by Data driven control considering control input limitation

The burden of control adjustment of shaking table is increasing with the background of lack of skilled operators. With such background, there is a strong demand for a method to achieve desired control performance regardless of the operator’s skill. The data-driven control is a promising approach to meet this requirement. However, even though an actual controller has an input limit, the data-driven control cannot handle it. Therefor, we proposed a novel method that considers the input limit based on data-driven prediction and an optimal problem with a penalty function. We verified the effectiveness of the proposed method through experiments using a small shaking test device.

Adaptive optimal dynamic surface control of strict‐feedback nonlinear systems with output constraints

SummaryIn this paper, an adaptive optimal control strategy is proposed for a class of strict‐feedback nonlinear systems with output constraints by using dynamic surface control. The controller design procedure is divided into two parts. One is the design of feedforward controller and the other is the design of optimal controller. To guarantee the satisfaction of output constraints in feedforward controller, nonlinear mapping is utilized to transform the constrained system into an unconstrained system. Neural‐network based adaptive dynamic programming algorithm is employed to approximate the optimal cost function and the optimal control law. By theoretical analysis, all the signals in the closed‐loop system are proved to be semi‐globally uniformly ultimately bounded and the output constraints are not violated. A numerical example illustrates the effectiveness of the proposed scheme.

Uncertainty identification of blade-mounted lidar-based inflow wind speed measurements for robust feedback–feedforward control synthesis

Abstract. The current trend toward larger wind turbine rotors leads to high periodic loads across the components due to the non-uniformity of inflow across the rotor. To address this, we introduce a blade-mounted lidar on each blade to provide a preview of inflow wind speed that can be used as a feedforward control input for the mitigation of such periodic blade loads. We present a method to easily determine blade-mounted lidar parameters, such as focus distance, telescope position, and orientation on the blade. However, such a method is accompanied by uncertainties in the inflow wind speed measurement, which may also be due to the induction zone, wind evolution, “cyclops dilemma”, unidentified misalignment in the telescope orientation, and the blade segment orientation sensor. Identification of these uncertainties allows their inclusion in the feedback–feedforward controller development for load mitigation. We perform large-eddy simulations, in which we simulate the blade-mounted lidar including the dynamic behaviour and the induction zone of one reference wind turbine for one above-rated inflow wind speed. Our calculation approach provides a good trade-off between a fast and simple determination of the telescope parameters and an accurate inflow wind speed measurement. We identify and model the uncertainties, which can then be directly included in the feedback–feedforward controller design and analysis. The rotor induction effect increases the preview time, which needs to be considered in the controller development and implementation.

Tracking control for the helicopter with time-varying disturbance and input stochastic perturbation

In this paper, the tracking control problem is investigated for the helicopter under time-varying disturbance, input stochastic perturbation, and unmeasurable flapping motion states. Firstly, a state observer and a disturbance observer are constructed to estimate the unmeasurable states and the time-varying disturbance, and the estimation of the disturbance is used in the feedforward controller design. Secondly, under the input stochastic perturbation, a feedback controller is constructed to guarantee the stochastic stability of the closed-loop error system. Using the stochastic control theory and the linear matrix inequality technique, the stability of the closed-loop error system is analyzed, and the gain of the controller is acquired via a solvable sufficient condition. Finally, an example is presented to illustrate the effectiveness of the proposed method.

Design of a central feedforward control of torque vectoring and rear-wheel steering to beneficially use tyre information

ABSTRACT This paper presents the design of a central feedforward control for the two chassis control systems rear-wheel steering (RWS) and torque vectoring (TV) which have related areas of intervention in lateral dynamics. A control strategy is presented in order to follow desired target values consisting of yaw acceleration and sideslip angle velocity. Central attention is given to the use of additional tyre information with the aim of enhancing vehicle handling and stability. With the knowledge of the mounted tyre type, an adaption law for the desired target values is derived. Although the focus is based on the usage of new tyre information, this modelling approach basically has the potential to reduce the need for coordination among the two systems RWS and TV, exploiting the synergies between both of them. Starting from an extended single-track model an exact Input–output linearisation method is used to design the feedforward control. This is followed by a proof of stability for the external and the internal dynamics of the controller. For the subsequent investigation, in a preliminary step, real-world in vehicle tests are carried out under varying tyre types with a wide spreading of characteristics. This serves as a basis to identify the most important tyre parameters for the controller and to derive the target goals. Finally, the controller is implemented in a 14-DOF non-linear entire vehicle model in Matlab/Simulink, that serves for simulations with a virtual vehicle plant. The performance of the presented feedforward control is assessed by specified objective criteria for steady-state and transient open-loop manoeuvres in lateral dynamics. These criteria are used to investigate the effectiveness of the control design with the aim to achieve the defined target motion. In addition to that, the manoeuvre results also serve to evaluate the control effort, involved in the coordinated cooperation of both systems.

The engineering principles of combining a transcriptional incoherent feedforward loop with negative feedback

BackgroundRegulation of gene expression is of paramount importance in all living systems. In the past two decades, it has been discovered that certain motifs, such as the feedforward motif, are overrepresented in gene regulatory circuits. Feedforward loops are also ubiquitous in process control engineering, and are nearly always structured so that one branch has the opposite effect of the other, which is a structure known as an “incoherent” feedforward loop in biology. In engineered systems, feedforward control loops are subject to several engineering constraints, including that (1) they are finely-tuned so that the system returns to the original steady state after a disturbance occurs (perfect adaptation), (2) they are typically only implemented in the combination with negative feedback, and (3) they can greatly improve the stability and dynamical characteristics of the conjoined negative feedback loop. On the other hand, in biology, incoherent feedforward loops can serve many purposes, one of which may be perfect adaptation. It is an open question as to whether those that achieve perfect adaptation are subject to the above engineering principles.ResultsWe analyzed an incoherent feedforward gene regulatory motif from the standpoint of the above engineering principles. In particular, we showed that an incoherent feedforward loop Type 1 (I1-FFL), from within a gene regulatory circuit, can be finely-tuned for perfect adaptation after a stimulus, and that the robustness of this behavior is increased by the presence of moderate negative feedback. In addition, we analyzed the advantages of adding a feedforward loop to a system that already operated under negative feedback, and found that the dynamical properties of the combined feedforward/feedback system were superior.ConclusionsOur analysis shows that many of the engineering principles used in engineering design of feedforward control are also applicable to feedforward loops in biological systems. We speculate that principles found in other domains of engineering may also be applicable to analogous structures in biology.

능동 롤 제어를 위한 피드포워드 제어기 설계에 관한 연구

능동 롤 제어를 위한 피드포워드 제어기 설계에 관한 연구

Mixed feedback and feedforward control design for multi-axis vibration isolation systems

This paper proposes a multi-loop single-input single-output control strategy for multi-axis vibration isolation systems. In this strategy, a combination of acceleration feedback and relative position feedback is used to improve the suppression of disturbances acting directly on the isolated payload. In addition, feedforward control is used to counteract the effect of floor vibrations. By mixing the control loops, amplification of sensor noise is minimized while performance in terms of vibration isolation and leveling is optimized. Experimental validation of the control strategy at an industrial vibration isolation system demonstrates performance improvement within the frequency range of interest in multiple directions, which illustrates the effectiveness and usefulness of the proposed design method.

String Stable Model Predictive Cooperative Adaptive Cruise Control for Heterogeneous Platoons

Cooperative adaptive cruise control (CACC) is a potential solution to decrease traffic jams caused by shock waves, increase the road capacity, decrease fuel consumption and improve safety. This paper proposes an integrated solution to a combination of four challenges in these CACC systems. One of the technological challenges is how to guarantee string stability (the ability to avoid amplification of dynamic vehicle responses along the string of vehicles) under nominal operational conditions. The second challenge is how to apply this solution to heterogeneous vehicles. The third challenge is how to maintain confidentiality of the vehicle parameters. Finally, the fourth challenge is to find a method which improves robustness against wireless packet loss. This paper proposes a model predictive control approach in combination with a feed-forward control design, which is based on a shared vector of predicted accelerations over a finite time horizon. This approach is shown to be applicable to a heterogeneous sequence of vehicles, while the vehicle parameters remain confidential. In previous works such an approach has shown to increase robustness against packet losses. Conditions for string stability are presented for the nominal operational conditions. Experimental results are presented and indeed demonstrate string stable behavior.