Feedforward Control Action Research Articles

Lifted time stable inversion based feedforward control for linear non-minimum phase systems

The feedforward control strategy exhibits substantial capability and high-precision control for output tracking tasks. However, the feedforward control action obtained through solving the inverse problem is unstable for non-minimum phase systems. In this paper, a novel stable inversion method is presented, termed lifted time stable inversion. Compared to the existing method, the proposed method does not necessitate infinite window to accomplish the tracking tasks. A comprehensive analysis of the developed method is provided, focusing on analysis of finite time stability and input–output finite time stability, aspects that have garnered limited attention in the literature on feedforward control. Furthermore, the relationship with existing stable inversion method is illustrated by constructing a linear transformation of the initial conditions for both inversions. Simulation results substantiate the validity of the finite time bounds and demonstrate the superior tracking advantage of the proposed method relative to the existing method. The performance of the proposed method is further displayed experimentally on a piezoelectric ceramic positioning platform.

Analysis and Preliminary Results of a Feedback-Feedforward Controller for Depth of Anesthesia

In a computer-based anaesthesia control system, the depth of hypnosis must be correctly maintained. The regulated variable is the Bispectral Index scale (BIS) controlled via the Propofol drug rate. The anesthesiologist administers Propofol to prevent unwanted fluctuations in the controlled variable during surgical stimulation, which acts as an unmeasurable disturbance on the BIS signal. In this paper, a feedback controller is paired with a feedforward control action. Based on existing clinical protocols, a digitalized disturbance signal that mimics the actual surgical stimulus is employed in the feedforward controller design as a measurable disturbance. To account for the time delay in the BIS measurements, a time delay estimation algorithm is developed and used to estimate the patient time delay. The digitalized disturbance signal is then shifted based on the estimated time delay to ensure a pre-emptive action of the feedforward controller. Two different designs of the feedforward controller are developed. Closed loop simulations considering a nominal patient with and without the feedforward control action are presented and compared. The results show that the surgical stimulus is better tackled using a feedforward control action, even if the actual surgical stimulus is not entirely known.

Insensitivity to propagation timing in a preview-enabled wind turbine control experiment

Lidar scanners are capable of taking measurements of a wind field upstream of a wind turbine. The wind turbine controller can use these measurements as a “preview” of future disturbances impacting the turbine. Such preview-enabled (or feedforward) controllers show superior performance to standard wind turbine control configurations based purely on a feedback architecture. To capitalize on the performance improvements that preview wind measurements can provide, feedforward control actions should be timed to coincide with the arrival of the wind field at the wind turbine location. However, the time of propagation of the wind field between the lidar measurement location and the wind turbine is not perfectly known. Moreover, the best time to take feedforward control action may not perfectly coincide with the true arrival time of the wind disturbance. This contribution presents results from an experiment where preview-enabled model predictive control was deployed on a fully-actuated, scaled model wind turbine operating in a wind tunnel testbed. In the study, we investigate the sensitivity of the controller performance to the assumed propagation delay using a range of wind input sequences. We find that the preview-enabled controller outperforms the feedback only case across a wide range of assumed propagation delays, demonstrating a level of robustness to the time alignment of the incoming disturbances.

Plantwide Decentralized Controller Design for Hybrid Solar Thermal Power Plant

Solar Thermal Power (STP) plants are promising avenues for solar energy assisted power generation. However, they face operational challenges due to diurnal and seasonal variations in available solar radiation, and varying atmospheric conditions in terms of cloud cover, dust levels, etc. Thus, to operate an STP plant at high efficiency and to meet the electricity demand, optimization and control strategies are critical. This paper focuses on designing decentralized controllers to ensure the safe and efficient operation of a hybrid STP which was designed and commissioned a few years ago (Nayak et al., Current Science, 2015, 109, 1445–1457). The STP is hybrid as it uses two different technologies for solar power collection, namely Parabolic Trough Collector (PTC) for heating oil and a Linear Fresnel Reflector (LFR) for generating direct steam. Superheated steam, generated using heat exchangers, subsequently drives the turbine generator block to generate electricity. In the current work, we develop decentralized controllers which ensure safe operation while meeting the production target of the hybrid STP. Towards this end, key control loops in the plant are identified. Continuous transfer function models are identified for these control loops using step tests. PID controllers are then obtained for these loops based on the resulting transfer function models. Wherever relevant, the feedback action of PID controllers is supplemented by a feedforward control action that reacts to the disturbances. Override control action is also implemented to ensure safe operation. The utility of the proposed plantwide decentralized control scheme is demonstrated via simulation studies by comparing the performance of the hybrid STP under open-loop and closed-loop in presence of disturbances and significant dynamic variability in the plant operation via two case studies. Results indicate significantly superior performance of closed-loop operation across various performance metrics.

Design and experimental validation of a robust model predictive control for the optimal trajectory tracking of a small-scale autonomous bulldozer

Trajectory tracking of an unmanned ground vehicle (UGV) is essential due to its extensive construction, agriculture, and military applications. In this paper, we propose an efficient, robust model predictive control (RMPC) for the trajectory tracking of a small-scale autonomous bulldozer in the presence of perturbations by unknown but bounded disturbances. The proposed RMPC is designed by considering a linearised tracking error-based model combined with a feed-forward and optimal control action to achieve the proposed trajectory. The presence of a corrective feedback controller as a time-varying finite-time linear quadratic regulator (LQR) suppresses the uncertainties acting on the real system by regulating around the nominal system. Pose estimation, required for control feedback, is based on sensor data fusion performed by an extended Kalman filter (EKF) map-based localiser, which processes inertial measurement unit (IMU) and light detection and ranging (LiDAR) measurements. Experiments are performed using a real robot (Husky A200) to validate the proposed control scheme’s performance. The experimental results show that the proposed controller can safely track target trajectories with low processing time, small tracking errors, and smooth control actions. Finally, the proposed control scheme is compared with related techniques and outperforms them in tracking accuracy.

An Optimal Islanding Detection Scheme for an Inverter-based Distribution Generation System

In this paper, an optimal controller-based islanding detection scheme is proposed for an inverter-based distributed generation system (DGS). Islanding is both harmful and unsafe but unavoidable state in a DGS. Therefore, islanding state is required to be detected quickly and accurately. A reactive power control strategy for islanding is presented in this work. It is reported that the active and reactive power mismatches in a DGS forces its voltage or frequency to deviate. That deviation is recorded continuously in this scheme and islanding state is reported when the deviation touches the thresholds. To help in this tracking process, a modified H8-based optimal controller whose parameters are tuned with LMI is proposed. It can offer both feedback and feed-forward control actions. The proposed DGS is modelled using MATLAB/SIMULINK and tested taking several case studies. It is found that, islanding condition is rapidly detected compared to that of the uncontrolled scheme yielding an optimal solution. Further, it is an inexpensive, robust, compact in structure and very easy to implement too.

A Novel Fast Error Convergence Approach for an Optimal Iterative Learning Controller

Design an optimized iterative learning control for linear and nonlinear dynamical systems is a challenging task. Norm-optimal iterative learning control (NOILC) is a valuable criterion for these dynamical systems. An iterative learning control algorithm based on optimal control theory is proposed, and the stability and convergence conditions of the proposed control algorithm are analyzed by using the convergence conditions of iterative learning control, and the control design is carried out based on feedforward and feedback control structure. At the same time, by introducing a weighted matrix coefficient to the feedforward control action, the convergence speed of iterative learning control algorithm based on optimal control theory is improved, and it is applied to the Matlab simulation control system. The results show that the convergence effect of the basic optimal control theory and the iterative learning control algorithm based on the weighted matrix coefficient is significant and the performance of the trajectory tracking is improved. The numerical example simulated on MATLAB@2019 and mollified results confirm the validation of the designed algorithm.

Structure-Preserving Constrained Optimal Trajectory Planning of a Wheeled Inverted Pendulum

The wheeled inverted pendulum (WIP) is an underactuated, nonholonomic mechatronic system, and has been popularized commercially as the Segway . Designing a control law for motion planning, that incorporates the state and control constraints, while respecting the configuration manifold, is a challenging problem. In this article, we derive a discrete-time model of the WIP system using discrete mechanics and generate optimal trajectories for the WIP system by solving a discrete-time constrained optimal control problem. Furthermore, we describe a nonlinear continuous-time model with parameters for designing a closed-loop linear–quadratic regulator (LQR). A dual control architecture is implemented in which the designed optimal trajectory is, then, provided as a reference to the robot with the optimal control trajectory as a feedforward control action, and an LQR in the feedback mode is employed to mitigate noise and disturbances for ensuing stable motion of the WIP system. While performing experiments on the WIP system involving aggressive maneuvers with fairly sharp turns, we found a high degree of congruence in the designed optimal trajectories and the path traced by the robot while tracking these trajectories. This corroborates the validity of the nonlinear model and the control scheme. Finally, these experiments demonstrate the highly nonlinear nature of the WIP system and robustness of the control scheme.

$\mathcal {H}_\infty$-Based Terrain Disturbance Rejection for Hydraulically Actuated Mobile Manipulators With a Nonrigid Link

Decoupling the end-effector motion from that of the mobile base of mobile manipulators traversing uneven terrains is important. This is especially so in mining, where material spillage from excavators and front-end loaders reduces productivity and slows down operations because of increased clean-up and maintenance times. Thus, this article proposes a strategy that relies on H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> feedback control combined with feedforward action to improve the rejection of terrain disturbances that affect the orientation of the end-effector. The dynamic model of the mobile manipulator considers a floating base with nonpermanent contacts at each wheel, hydraulic actuators with nonlinear dynamics and a nonrigid arm. The arm flexibility is modeled as a passive spring-damper joint to account for inherent cantilever effects of real excavators and loaders. The analysis considers three different H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller structures (single-input single-output (SISO) with feedforward, single-input multiple-output without feedforward, and multiple-input multiple-output without feedforward) to determine the benefits or disadvantages of employing the pitch rate of the mobile base as a feedforward control action or as an input handled by the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller and using only the end-effector actuator or also the other actuated joints of the arm. The root-mean-square error (RMSE) was reduced between 73.8%-86.0% when driving an industrial semiautonomous skid-steer loader over a ramp using the SISO H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller with feedforward action.The tilt angle error was kept on average less than 0.9 ± 0.1°. The same controller yields a reduction of the RMSE between 23.5%- 38.4% and a tilt angle error smaller than 3.39 ± 0.07° on average when traversing over a bump. Hence, the strategy proposed to reject ground disturbances should contribute to reducing material spillage of existing autonomous machines that navigate with little operator intervention along mining galleries, but that cannot avoid disturbing material lying on the ground or the characteristic unevenness of mining terrains.

Nonlinear L1 adaptive control of stagnation pressure in a cryogenic wind tunnel

Cryogenic wind tunnel is a sophisticated aerodynamics ground test facility, which operates in cryogenic temperature with injection of liquid nitrogen. The multi-variable, nonlinear and coupled dynamics existing between the temperature, pressure and Mach number in the tunnel, poses great challenges for the effective control of the tunnel. L1 adaptive control is a new control methodology developed in recent years with good robustness properties, which has good potentials to address these challenges. But this control method does not provide full adaptive feedforward control in its generic structure. In the paper, adaptive feedforward control action is introduced into the standard L1 adaptive control architecture for nonlinear systems in the presence of matched un-modeled dynamics. This new control structure is applied to the stagnation pressure control in a cryogenic wind tunnel, which could also be used for the control of temperature and Mach number in the tunnel. This new method could effectively compensate known disturbances with linear gain uncertainty, which occur in the nonlinear systems, while retaining the closed-loop control performance of L1 adaptive control. After the proof and discussions on the stability of this method, simulations of the stagnation pressure control in the wind tunnel are presented. The results and analysis demonstrate the effectiveness of the proposed control architecture.

Distributed PI Control For Heterogeneous Nonlinear Platoon of Autonomous Connected Vehicles

In this paper we present a distributed PI-based control law that guarantees the platoon formation to track leader velocity with a pre-fixed inter-vehicular distance, when vehicles are heterogeneous in both parameters and nonlinear drivetrain dynamics. Moreover, differently from most of the approaches in the literature, the proposed PI protocol intrinsically compensates for the nonlinear, heterogeneous and uncertain drivetrain dynamics without requiring any feedforward control action. We formulate sufficient conditions for closed-loop heterogeneous non-linear vehicular network stability that can be used to tune the PI control parameters. Simulation results confirm the effectiveness of the proposed PI controller in both nominal and uncertain platooning scenario.

A geometric optimization method for the trajectory planning of flexible manipulators

Lightweight and flexible robots offer an interesting answer to industrial needs for safety and efficiency. The control of such systems should be able to deal properly with the flexible behavior in the links and the joints. In this paper, a feedforward control action is computed by solving the inverse dynamics of the system. Flexibility in the system is modeled using finite elements formulated in the local frame. The inverse problem is then solved using a constrained optimization formulation. This local frame representation reduces the nonlinearity in the equations of motion and improves the convergence of the numerical scheme. To illustrate the method, numerical examples of a serial and a parallel 3D robot are shown.

An Adaptive Fuzzy Feedforward-Feedback Control System Applied to a Saccharification Process

Abstract In industrial bioprocess control, disturbance sources typically influences process variable regulation. These disturbances may reduce a system control performance or even affect the final bioproduct quality. Therefore, feedforward control is desired because it anticipates the effects caused by these disturbances in an attempt to keep the process variable at the setpoint value. However, designing a feedforward control law requires process modeling, which can be a tough task when dealing with bioprocesses that are intrinsically nonlinear and multivariable systems. Thus, an adaptive feedforward control law or other advanced control system is needed for satisfactory disturbance rejection. For this reason, a general fuzzy feedforward control system is proposed in this paper to replace the classical feedforward control, making it easier to implement the feedforward control action by avoiding nonlinear and multivariable process modeling. The adaptive fuzzy feedforward-feedback (A4FB) system was applied to a product concentration control loop in an enzymatic reactor, to reject disturbances caused by variations in the substrate and enzymatic solutions feed concentration. The results showed that the A4FB controller rejected much more disturbance effects than classical feedforward control law, demonstrating its advantage, supported by not only its simple implementation, but also its improved disturbance rejection.

Tracking Error Learning Control for Precise Mobile Robot Path Tracking in Outdoor Environment

This paper presents a Tracking-Error Learning Control (TELC) algorithm for precise mobile robot path tracking in off-road terrain. In traditional tracking error-based control approaches, feedback and feedforward controllers are designed based on the nominal model which cannot capture the uncertainties, disturbances and changing working conditions so that they cannot ensure precise path tracking performance in the outdoor environment. In TELC algorithm, the feedforward control actions are updated by using the tracking error dynamics and the plant-model mismatch problem is thus discarded. Therefore, the feedforward controller gradually eliminates the feedback controller from the control of the system once the mobile robot has been on-track. In addition to the proof of the stability, it is proven that the cost functions do not have local minima so that the coefficients in TELC algorithm guarantee that the global minimum is reached. The experimental results show that the TELC algorithm results in better path tracking performance than the traditional tracking error-based control method. The mobile robot controlled by TELC algorithm can track a target path precisely with less than $10$ cm error in off-road terrain.

Decentralized Trajectory Tracking Control for Soft Robots Interacting With the Environment

Despite the classic nature of the problem, trajectory tracking for soft robots, i.e., robots with compliant elements deliberately introduced in their design, still presents several challenges. One of these is to design controllers which can obtain sufficiently high performance while preserving the physical characteristics intrinsic to soft robots. Indeed, classic control schemes using high-gain feedback actions fundamentally alter the natural compliance of soft robots effectively stiffening them, thus de facto defeating their main design purpose. As an alternative approach, we consider here using a low-gain feedback, while exploiting feedforward components. In order to cope with the complexity and uncertainty of the dynamics, we adopt a decentralized, iteratively learned feedforward action, combined with a locally optimal feedback control. The relative authority of the feedback and feedforward control actions adapts with the degree of uncertainty of the learned component. The effectiveness of the method is experimentally verified on several robotic structures and working conditions, including unexpected interactions with the environment, where preservation of softness is critical for safety and robustness.

Data-Driven Subspace Predictive Control of a Nuclear Reactor

This paper introduces a methodology of designing subspace predictive reactor core power control during load-following mode of operation. The central idea is to implement predictive control law directly from the preprocessed input–output data set without using any explicit process model. The controller is designed to include design constraints, feedforward control, and integral control action effectively. Furthermore, time variations in the process are taken into account by recursively updating control parameters with the arrival of new data set. The efficacy of the proposed technique is demonstrated for tracking various load rejection as well as load-following transients for a pressurized water nuclear reactor. A detailed parameter sensitivity analysis is carried out to analyze the controller performance.

Robust synchronous generator excitation based on novel feedforward control

Summary In this paper, a synchronous generator excitation controller based on a novel feedforward control action is proposed. The main purpose of the new feedforward action is to enable a more robust excitation of the synchronous generator operating in varying operating conditions when connected to a power grid, for any superimposed stator voltage controller. Namely, the dynamic performance of the proposed controller is compared with a conventional proportional-integral (PI) controller, and with the PI controller combined with a feedforward action based on the direct component of the stator current. It is analytically shown that the novel controller improves the robustness when compared to 2 aforementioned solutions. Also, by simulation and experimental tests, it is shown that for the loaded synchronous generator, the novel controller, which is designed to have a similar response speed in open circuit as conventional controllers, exhibits up to 2 times faster dynamic performance.

Control of nonlinear vibrations using the adjoint method

In this paper, a new methodology is proposed to address the problems of suppressing structural vibrations and attenuating contact forces in nonlinear mechanical systems. The computational algorithms developed in this work are based on the mathematical framework of the calculus of variation and take advantage of the numerical implementation of the adjoint method. To this end, the principal aspects of the optimal control theory are reviewed and employed to derive the adjoint equations which form a nonlinear differential-algebraic two-point boundary value problem that defines the mathematical solution of the optimal control problem. The adjoint equations are obtained and solved numerically for the optimal design of control strategies considering a twofold control structure: a feedforward (open-loop) control architecture and a feedback (closed-loop) control scheme. While the feedforward control strategy can be implemented using only the active control paradigm, the feedback control method can be realized employing both the active and the passive control approaches. For this purpose, two dual numerical procedures are developed to numerically compute a set of optimal control policies, namely the adjoint-based control optimization method for feedforward control actions and the adjoint-based parameter optimization method for feedback control actions. The computational methods developed in this work are suitable for controlling nonlinear nonautonomous dynamical systems and feature a broad scope of application. In particular, it is shown in this paper that by setting an appropriate mathematical form of the cost functional, the proposed methods allow for simultaneously solving the problems of suppressing vibrations and attenuating interaction forces for a general class of nonlinear mechanical systems. The numerical example described in the paper illustrates the key features of the adjoint method and demonstrates the feasibility and the effectiveness of the proposed adjoint-based computational procedures.

Load speed regulation in compliant mechanical transmission systems using feedback and feedforward control actions

The problem of controlling the load speed of a mechanical transmission system consisting of a belt-pulley and gear-pair is considered. The system is modeled as two inertia (motor and load) connected by a compliant transmission. If the transmission is assumed to be rigid, then using either the motor or load speed feedback provides the same result. However, with transmission compliance, due to belts or long shafts, the stability characteristics and performance of the closed-loop system are quite different when either motor or load speed feedback is employed. We investigate motor and load speed feedback schemes by utilizing the singular perturbation method. We propose and discuss a control scheme that utilizes both motor and load speed feedback, and design an adaptive feedforward action to reject load torque disturbances. The control algorithms are implemented on an experimental platform that is typically used in roll-to-roll manufacturing and results are shown and discussed.

Robust Trajectory Tracking Error Model-Based Predictive Control for Unmanned Ground Vehicles

This paper proposes a new robust trajectory tracking error-based control approach for unmanned ground vehicles. A trajectory tracking error-based model is used to design a linear model predictive controller and its control action is combined with feedforward and robust control actions. The experimental results show that the proposed control structure is capable to let a tractor-trailer system track both linear and curvilinear target trajectories with low tracking error.