Dynamic Feedforward Control Research Articles

Dynamics Modelling and Adaptive Identification: Towards Improved Human-Robot Interaction in Collaborative Systems

This article presents a novel approach to enhancing human-robot collaboration and safety through advanced dynamic modelling and adaptive identification techniques. We introduce a comprehensive methodology that integrates motion trajectory design with real-time torque detection, addressing the critical limitations of conventional systems that rely on costly joint torque sensors. By simultaneously identifying friction forces in an integrated joint and a simplified two-bar mechanism, our approach leverages existing kinematic and dynamic models to achieve precise dynamic parameter identification. The proposed method significantly advances the fields of drag-teaching and collision detection by eliminating the need for force sensors, thus making it more feasible for mass-produced robotic systems. Our findings demonstrate that accurate dynamic modelling is essential for effective zero-force control, particularly in high-speed drag-teaching scenarios, where inertia and friction present substantial challenges. Experimental validation confirms the efficacy of our dynamic feed-forward controller design and the adaptability of drag-teaching parameters, leading to improved operational flexibility and safety in collaborative environments. This research contributes a critical framework for future developments in intelligent robotic systems, providing a robust basis for integrating advanced human-robot interactions in industrial applications.

High precision control of industrial robot based on flexible joint response model

For industrial robots, their repetition accuracy is high, but their absolute accuracy and trajectory accuracy are low, which limits the application of industrial robots in more scenarios. Current solutions mainly address precision issues caused by static errors through adjustments in kinematic parameters. Approaches such as dynamic feedforward control, torque computation methods, intelligent control, dual encoder control, visual servoing, etc., are employed to enhance dynamic tracking accuracy, yet they commonly suffer from insufficient precision, poor robustness, high costs, and usability challenges. In response to the difficulty in reducing dynamic errors, this paper proposes a high-precision control technique based on compensating for flexible joint responses. By compensating for deviations in flexible joint responses, the trajectory precision at the end-effector of industrial robots is improved.

Data-driven model based adaptive feedback-feed forward control schemes for open cycle - OTEC process

Open Cycle - Ocean Thermal Energy Conversion (OC-OTEC) is one of the most important renewable energy sources that generate electricity and fresh water from seawater utilizing the temperature gradient between the warm surface seawater and the cold deep seawater. This paper aims to develop non-linear data-driven model-based adaptive Feedback Control (FBC) schemes for the OC-OTEC process to track the output power and a dynamic Feed-Forward Control (FFC) scheme to reject the effects of temperature disturbance on power caused by climate variations in OC-OTEC. The experiments are conducted on a laboratory-scale OC-OTEC experimental setup at the National Institute of Ocean Technology, Chennai. Firstly, linear data-driven models are developed using system identification techniques. Based on the developed models, gain scheduling-based adaptive control schemes are developed: Proportional Integral (PI) control and Model Predictive Control (MPC). Secondly, the closed-loop performances of the developed FBC schemes are analysed under servo and regulatory operations. Furthermore, it is observed from the sensitivity analysis results that the temperature disturbance highly influences output over the manipulated variable. Hence, a dynamic FFC scheme is implemented to reject known disturbance of 1 °C variation in temperature gradient from 18 °C to 19 °C due to Sea Surface Temperature (SST) changes in temperature gradient. The results show that the proposed MPC-based FBC-FF scheme effectively enhances the tracking and disturbance rejection performance compared to the PI-based FBC-FF control scheme with a minimum Integral Square Error (ISE) of 3.055 and Control Effort (CE) of 7.505. This experimental data-based, data-driven modelling and adaptive control research provides a new direction for automating OC-OTEC. Further, these studies will help to develop a rugged and automated upscaling OC-OTEC plant control system with proposed feasible control schemes.

Solar PV Array Fed Single Stage BLDC Motor Drive for Water Pumping System

A single-stage photovoltaic-fed field-oriented controlled brushless DC (BLDC) motor drive for water pumping using a 2-degree of freedom (DoF) controller is presented in this paper. The proposed 2-DoF controller consists of a feedback and feedforward loop design. A feedback loop is used to maintain stability and desired performance, in which the PI controller is utilized for controlling the DC voltage at the outer loop, which generates the necessary speed reference. A Fuzzy logic controller is then used in the inner loop to achieve a faster speed response of the BLDC motor. Further, the performance of the system is made faster by incorporating dynamic feed-forward control. MATLAB Simulink is used to design and simulate the system. The OPAL-RT simulator is used to validate the system’s performance in real-time.

Air-flow control in fuel cells using delay-based load governor and feedforward augmented dynamic inversion

The frequent and sudden increase of load in electric vehicles depletes oxygen from the fuel cell cathode, leading possibly to oxygen starvation. This paper presents the design of an air flow controller for fuel cell systems (FCS) that aims to replenish the depleted oxygen. A dynamic inversion is used as the feed-forward compensation for the disturbance effect coming from the load current change. However, the inverted dynamics have negative relative degree (improper) and not physically realizable. To make it proper, an augmentation by delay is done, with the same delay added into demand current. The current-dependent time delay introduced in the demand current gives the FCS the opportunity to prepare a sufficient air flow that can withstand the dip in oxygen excess ratio (OER). Besides, the FCS plant is linearized at various operating points, and the dynamic feedforward controller is designed at several operating points with interpolation applied for in-between values. The simulation results show a considerable improvement in the OER response where the constraint is met and the recovery time is reduced.

An iterative learning method for realizing accurate dynamic feedforward control of an industrial hybrid robot

Feedforward control based on an accurate dynamic model is an effective approach to reduce the dynamic effect of the robot and improve its performance. However, due to the complicated work environment with considerable uncertainty, it is difficult to obtain a high-precision dynamic model of the robot, which severely deteriorates the achievable control performance. This paper proposes an iterative learning method to accurately design the industrial feedforward controller and compensate for the external uncertain dynamic load of the robot. Based on a standard dynamic model, a complete linear feedforward controller is presented. An iterative design strategy is given to iteratively update the feedforward controller by combining the Moore-Penrose Inverse and the PID learning rate. Experiments are carried out on a 5-DOF industrial hybrid robot to validate the effectiveness of the proposed iterative learning method. The experiment results illustrate that the industrial feedforward controller can rapidly converge to the optimal controller and significantly improve the servo performance by using the proposed method. This paper provides an effective method for applying iterative learning control to an unopened industrial control system. It is very useful for the practical control of hybrid robots in industrial field.

Tracking error prediction informed motion control of a parallel machine tool for high-performance machining

Parallel machine tools (PMTs) are suitable for machining parts with complex surface features, owing to their advantages in providing flexible attitude adjustments and quick dynamic responses. However, due to the characteristics of the multiple-axis coupling motions and nonlinear dynamics, how to achieve high-efficiency and high-quality machining using PMTs remains a challenging issue encountered in the field. To solve this problem, in this study, the tracking error generation mechanism for PMTs is originally disclosed, which indicates that the driving limb's tracking error includes the error caused by the time-varying load, and that caused by the input signal. Accordingly, an integrated control method combining real-time dynamic feedforward and feedrate scheduling is proposed for reducing these two parts of the tracking errors. A stepwise identification method that can decouple the friction parameters and inertial parameters is designed for real-time dynamic feedforward control. In addition, by establishing systematic machining quality constraints related to the PMT's dynamic properties, a feedrate scheduling method for complex spline toolpaths is put forward. Finally, toolpath tracking and machining comparison experiments are conducted with a commercial ISG computer numerical control (CNC) kernel to validate the advantages of the proposed control method. The experimental results demonstrate that the proposed integrated control method can effectively improve the machining efficiency and machining quality. In summary, this study analytically formulates a tracking error prediction model for PMTs, and proposes an integrated control method for high-performance machining. The findings of this study provide a feasible way to improve the performance of PMTs, and to further promote their popularization and application in industry.

Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot

The dynamics modeling and trajectory optimization of a segmented linkage cable-driven hyper-redundant robot (SL-CDHRR) become more challenging, since there are multiple couplings between the active cables, passive cables, joints and end-effector. To deal with these problems, this paper proposes a dynamic modeling and trajectory tracking control methods for such type of CDHRR, i.e., SL-CDHRR. First, the multi-coupling kinematics equation (i.e., cable-joint-end) of the hyper-redundant robot is derived. Then, according to the transmission characteristics of the hybrid active/passive segmented linkage, the dynamic equation of series–parallel coupling is derived. It consists of parallel-active dynamics and series-passive dynamics. Furthermore, using the tension of active cables and the pose of the end-effector as optimization indicators, a trajectory tracking framework was constructed by the combination of dynamic feedforward control and PD control. The multi-objective particle swarm optimization method is used to achieve the simultaneous optimization of the energy indicator and control accuracy indicator during the trajectory tracking process. Finally, a MATLAB/SimMechanics co-simulation system is built, and the proposed methods are verified by the built co-simulation system.

Research on multidimensional evaluation of tracking control strategies for self-driving vehicles

Performance evaluation is a necessary stage in development of tracking control strategy of autonomous vehicle system, which determines the scope of application and promotes further improvement. At present, most of the tracking control strategies include performance evaluation. However, performance evaluation criteria differ from work to work, lacking comprehensive evaluation system. This article proposes a multidimensional integrated tracking control evaluation system based on subjective and objective weighting, taking into account the tracking accuracy, driving stability, and ride comfort. Through the co-simulation of CarSim and Simulink, qualitative analysis and quantitative analysis based on multidimensional evaluation system of five coupled longitudinal and lateral control strategies (lateral: pure pursuit feedforward control, dynamic-model-based optimal curvature control (dynamic feedforward control), Stanley feedback control, kinematics feedback control, and dynamic feedback control; longitudinal: the incremental proportion–integration–differentiation control) under typical operating conditions are carried out to analyze the operating range and robustness of each tracking control strategy. The results show that the Stanley tracking control strategy and the dynamic feedback tracking control strategy have a wide range of applications and robustness. The consistency of qualitative analysis results and the quantitative analysis results verify the validity and feasibility of the evaluation system.

Remote Control Laboratory for Three-Tank Hydraulic System Using Matlab, Websockets and JavaScript

This work aims to introduce a new architecture for building virtual and remote laboratories where the building blocks are represented by the Matlab/Simulink computing and simulation software, WebSocket communication technology and a front-end application created in JavaScript programming language. Matlab does not have direct support for WebSockets, but the implementation of the MatlabWebSocket library on the Matlab server has allowed connection through WebSockets that has been accepted with the client side realized in JavaScript. Additionally to the interactivity that is heavily supported by JavaScript, the remote laboratory has been visualized on the client side in 3D by implementation of the Three.js JavaScript library. From the control point of view the new remote laboratory enables to compare nonlinear feedback control with dynamical feedforward control respecting input saturation where in both cases a nonlinear disturbance observer can be used. WebSocket communication technology and the corresponding client interface in the form of a web application create possibilities for the presented remote laboratory to run from the Internet browser and no dedicated application is needed as it was in previous Matlab based laboratories what can be considered as a main contribution.

Dynamic characteristics of a solar‐aided coal‐fired power generation system under direct normal irradiance (DNI) feedforward control

AbstractA solar‐aided coal‐fired power generation (SAPG) system is a new type of power generation system in the field of solar thermal power generation. However, the instability of solar radiation will cause fluctuations in steam temperature, which is unfavorable for the operation of boilers and steam turbines. Based on a 600 MW subcritical coal‐fired power generation unit, TRNSYS software is applied to establish a transient simulation model of SAPG in this paper. A dynamic feedforward control system for steam temperature is set up. Some essential parameters, such as the fuel consumption rate, solar‐heated steam extraction rate, water spraying flow rate, and flue gas damper opening, are under the control of direct normal irradiance (DNI). Then, the dynamic characteristics of SAPG are analyzed using typical weather data. The simulation results show that under the fuel‐saving mode, when solar irradiation changes, the SAPG system achieves a coal reduction of 4.9% by using the steam temperature control system with DNI feedforward control, and the main steam temperature fluctuation is less than 5°C with the reheat steam temperature reduced within a reasonable range. The power generation fluctuation is less than 10 MW, and the solar‐to‐electricity efficiency reaches 22.5%. Some parameters on both the flue gas side and the water/steam side in the utility boiler are simulated to demonstrate the effectiveness of DNI control.

Dynamic feedforward control in decoupling space for a four-degree-of-freedom parallel robot

This article proposes a dynamic feedforward control method for a four-degree-of-freedom parallel robot in decoupling space to improve the control accuracy and robust stability. The mass matrix and the gravity component are obtained from the rigid-body dynamic model that is formulated by means of the link Jacobian matrices and the principle of virtual work. Then using the positive definiteness of the mass matrix and singular value decomposition algorithms, a decoupling transformation matrix is obtained to convert the physical joint space to the decoupling modal space. In the modal space, a decoupling closed-loop controller design has been implemented for each driven leg. Afterward, by applying the gravity component of the dynamic model, a feedforward control subsystem has been designed to compensate the influence of gravity load on the parallel robot, which can further reduce the negative impacts caused by modeling inaccuracies. This numerical simulation analysis shows that the ideal control accuracy and robust stability have been achieved using the dynamic feedforward decoupling control method for the nonlinear and strongly coupled systems of the parallel robot. The described controller has a simple structure and can be easily realized in practice.

Dynamic Modeling and Experimental Validation of Door-Opening Process by a Mobile Manipulator

Door-opening is a critical problem for robots used for rescue purposes in nuclear power plants (NPPs). A force and torque (F/T) sensor is not used in the rescue task for door-opening in the NPPs environment. It is, therefore, necessary to study the dynamic model of door-opening. The NPPs door and a door handle dynamic model are significant to the mechanical design, simulation, and dynamic feed-forward control of an NPP robot. To obtain the accurate force data of door-opening, a method based on a gravity compensation algorithm combined with a transformation of the contact force of the end effector is proposed. This paper analyzes the structural features and dynamics model of a fire door and a door handle. Methods for identifying the model parameters are also developed by combining a Nelder-Mead simplex search with the least-squares algorithm. The extensive door-opening experiments were carried out in this paper, and the results validate the fidelity of the derived dynamic models of the door and the door handle.

Active Compliance Control on the Hydraulic Quadruped Robot With Passive Compliant Servo Actuator

A hydraulic servo actuator with passive compliance (HPCA) is designed for hydraulic actuated quadruped robots, aiming to solve the response discrepancy of the low-bandwidth servo valve to impact forces between robot's feet and the ground. This paper focuses on the performance of this passive compliance method combined with an active compliance control strategy when used on quadruped robots. First, the frequency-response characteristics of the HPCA are further discussed. Then, combined with the requirements of the quadruped robot, a compliant method characterized by incorporating dynamic feedforward control and joint angle feedback control items into the virtual model is proposed. Finally, both the new algorithm and the performance of the HPCA are verified by simulation and experiment. The results demonstrate that, compared with the original actuator, the frequency-response characteristics of the HPCA have better adaptability for the quadruped robot, while the efficiency of the active compliance control is also improved by this novel passive compliance strategy.

<inline-formula> <tex-math notation="LaTeX">$\mathcal{H}_\infty$ </tex-math> </inline-formula>-Optimal Parallel Feedforward Control Using Minimum Gain

This letter presents static and dynamic parallel feedforward controller synthesis methods that render a linear time-invariant system minimum phase by augmenting its output. The system output is perturbed the least amount possible by minimizing the gain of the parallel feedforward controller while ensuring the augmented system is minimum phase. This is done by minimizing the maximum singular value of a static parallel feedforward controller or the weighted H ∞ norm of a dynamic parallel feedforward controller. Static and dynamic parallel feedforward controllers are synthesized using direct and indirect methods that involve bilinear matrix inequality constraints and are solved iteratively using linear matrix inequalities. The direct method enforces a minimum gain constraint directly on the augmented system, while the indirect method solves for an asymptotically stabilizing negative feedback controller that is inverted to obtain the parallel feedforward controller. Numerical examples are provided to demonstrate the effectiveness of the proposed controller synthesis methods.

Dynamic feedforward control of spatial cable-driven hyper-redundant manipulators for on-orbit servicing

SUMMARYThe hyper-redundant manipulators are suitable for working in the constrained on-orbit servicing environment due to the extreme flexibility. However, its modelling and control are very challenging due to the characteristics of non-linearity and strong coupling. In this paper, considering the multi-level mapping among the motors, cables, joints, and end-effector, a proportional derivative (PD) with dynamic feedforward compensation control system is designed. The corresponding control system is divided into five parts: controller, planner, actuator, manipulator, and sensor. The actual control torque consisting of the desired feedforward torque and the feedback torque is generated by the controller. In order to improve the tracking accuracy and maintain rapid response, the torque, which is calculated by the dynamics model of the traditional joint-driven manipulator, is regarded as the desired feedforward torque. The parameters of interest are the angle and velocity of the universal joint and motors. The planner plans and converts the desired parameters of the universal joint to corresponding motors. Combining with the feedback angles and velocities signals of the corresponding motors, the feedback torque can be calculated by the PD control module. Finally, typical cases of six universal joints (12DOFs) manipulators are simulated and experimented. The results demonstrate that the method is very efficient for controlling spatial cable-driven hyper-redundant manipulators.

A Method to Realize Accurate Dynamic Feedforward Control of a Spray-Painting Robot for Airplane Wings

The dynamic characteristic has an important effect on the motion precision of a robot and dynamic feedforward control is an effective approach to reduce the effect. However, it is difficult to realize the accurate dynamic feedforward control in an industrial servo system and determine the feedforward coefficients. This paper proposes a method to realize the accurate dynamic feedforward control of a spray-painting robot for airplane wings with large workspace and time-varying dynamics. The basic control method is still the feedback control system with dynamic feedforward compensation, which is the most widely used in industrial field. The control parameters of the closed-loop feedback control system are designed based on atlas method. Considering that only the acceleration and velocity feedforward compensations are provided in an industrial servo system, the mapping relationship between the complete dynamic model and the velocity and acceleration compensators is investigated. Then, the method to realize the accurate feedforward compensation in the industrial servo system is presented based on the complete dynamic model. For a complex robot without an accurate dynamic model, the approach to realize the accurate feedforward compensation is also discussed. The experiment on a physical prototype validates the effect of the proposed methods. This paper is very helpful for the practical control of robots in an industrial field.

Semi-physical modeling and control of a centrifugal compressor for the air feeding of a PEM fuel cell

Air compressor which is to used to deliver the air (including about 21% oxygen) to the cathode channel for electrochemical reaction is a crucial component for the polymer electrolyte membrane (PEM) fuel cell. The working characteristics of the compressor greatly influences the fuel cell performance as well as the durability. In this paper a semi-physical modeling method is adopted to analyze the operating property of a centrifugal compressor which is more suitable for automotive fuel cells because of its compactness. This model includes many physical and empirical parameters which are very difficult to determine. Interior-point optimization method based on Newton iteration is used to identify those parameters. The result shows that the modeled compressor map has a good agreement with the experimental data. Meanwhile, the compressor efficiency is analyzed and compared with the measurement to further validate the developed model. This compressor is thus adapted to a validated 10 kW fuel cell model. A dynamic feedforward controller is proposed based on the load torque to control the air mass flow, eliminating the disturbance produced by the compressor load in transient. The simulation results show that this compressor could satisfy requirements of the fuel cell under dynamic load situations while keeping both the fuel cell and compressor with high efficiencies.

Robust guaranteed cost ILC with dynamic feedforward and disturbance compensation for accurate PMSM position control

This contribution presents a robust ILC control design based on guaranteed costs. By combining this ILC design with dynamic feedforward control and an observer-based disturbance compensation, the initial tracking errors in an early learning stage can be reduced. The benefits of the proposed design approach are pointed out at the example of a robust position control of a Permanent Magnet Synchronous Motor (PMSM), which is subject to uncertain model parameters. The paper is concluded with convincing experimental results from a dedicated test rig. Moreover, a comparison with a classical observer-based tracking control is provided.

Longitudinal tunnel ventilation control. Part 1: Modelling and dynamic feedforward control

Road tunnels exceeding a certain minimum length are equipped with a ventilation system. In case of a fire it is used to achieve a predefined air flow velocity in the tunnel by adequately controlling the installed jet fans in order to ensure sufficient visibility for persons to safely follow the escape routes. As the dynamics of the air flow in road tunnels strongly depend on the tunnel length, short tunnels with longitudinal ventilation systems pose a challenging control task. In this paper, non-linear dynamic feedforward control is proposed for longitudinal ventilation control in case of an emergency. For this purpose, an analytical non-linear zero-dimensional model of the air flow is feedback linearised. Due to its special properties, which are presented and analysed, two different versions of feedforward control are proposed: One is focused on performance, the other on robustness. Finally, the beneficial behaviour of the presented two-degrees-of-freedom control approach is demonstrated by its application to an Austrian motorway tunnel.