Feedforward Term Research Articles

ADP-based adaptive control of ship course tracking system with prescribed performance

In this paper, an adaptive dynamic programing (ADP)-based adaptive control problem is studied for the ship course tracking system with prescribed performance. Firstly, the complex sea conditions will bring difficulty to ship course tracking when unmanned ship sailing on sea. In order to overcome this difficulty, a prescribed performance feedforward term is designed in the controller to improve the course tracking ability of ship. Secondly, by defining a cost function, an ADP technology is exploited to achieve an optimal control of ship course tracking system. Finally, the stability of the closed loop system is turned out by Lyapunov stability theory and all signals are uniformly ultimately bounded (UUB). Simulation results validate the effectiveness of the proposed method.

Dynamic modeling, clutch parameter adaptation, and control of automatic transmission for tracked vehicles

In this study, a novel TCU control structure and algorithms including also dynamic model of the transmission will perform the gear shifting of automatic transmissions used in tracked military vehicles are designed. In case of inherent wear of the clutches, the clutch parameters are estimated by means of an adaptation algorithm that uses only the information from the transmission input and output speed sensors. These estimated clutch parameters are used in clutch torque calculation is utilized by control algorithms. For the clutch speed control in the inertia phase, a PID control structure with a negative feedforward term that cancels the nonlinearities of the system is proposed. The feedforward term utilizes the estimated wear clutch coefficients in the calculation of friction coefficients. The parameters of the PID controller are optimized by a genetic algorithm. The designed all structure are firstly tested on a MATLAB/Simulink power train simulation model, and then tested using a unique transmission on a transmission dynamometer test bench to examine its suitability for real transmission scenarios. The performances of proposed PID control and a backstepping nonlinear controller that we constructed for the tracked vehicles are compared with and without clutch wear. Maximum tracking error is decreased by 98% with proposed adaptive PID control structure with nonlinear feedforward term compare to backstepping controller. In the case of clutch wear, the back-stepping control exists in the literature has been found to result in oscillation. By updating the estimated friction coefficient from adaptation algorithm, in the backstepping controller, it is concluded that these oscillations can be eliminated. Additionally, on-off solenoid valves, are widely used, are known to cause torque interruptions and jerks during gear shifting. It has been observed the control structure presented in this study reduced the jerks by one quarter.

Semi‐global output regulation of continuous‐time linear systems subject to input saturation via output feedback: A model‐free method

SummaryThis article considers the output regulation problem of continuous‐time linear systems subject to input saturation in the scenario that the system dynamics are unknown. Based on the low‐gain technique and the output feedback technique, we construct an output feedback control law to solve the output regulation problem with input saturation. Since the system dynamics are unknown, we estimate the feedback and feedforward terms in the control law with a two‐step data‐driven method. An output feedback adaptive dynamic programming algorithm is proposed to estimate the feedback term. An online updating algorithm based on output tracking error is proposed to estimate the feedforward term directly without solving the output regulation equations. Both algorithms don't rely on the measurement of the internal states of the exosystem and the original system. We show that the input saturation caused by the iterative feedforward gain matrix in the online updating algorithm doesn't affect the convergence of the algorithm. With these two data‐driven algorithms, the control law doesn't rely on the dynamics anymore. The low‐gain control law obtained by the model‐free method prevents input saturation from occurring and hence solves the output regulation problem. Finally, a numerical example is provided to validate the theoretical results.

The effect of path curvature on the stability of reversing truck–semitrailer in the presence of feedback delay

Stability analysis of the low-speed reverse motion along clothoid curve is presented for the truck–semitrailer combination. The single-track kinematic model supplemented with the steering system and the lower-level controller is applied. A higher-level controller is designed to stabilise the reverse motion of the vehicle. Linear state feedback with time delay is used with feedforward term to force the vehicle to the desired path. The linear stability analysis is done by semi-discretization and D-subdivision methods to determine the optimal control gain setup. The effects of path curvature and time delay on the stability are investigated and verified via numerical simulations. Results are validated via experiments using a small-scale test rig.

Design of an Intelligent Cascade Control Scheme Using a Hybrid Adaptive Neuro-Fuzzy PID Controller for the Suppression of Drill String Torsional Vibration

Eliminating the excessive stick–slip torsional vibrations of drill strings by utilizing an effective controller can significantly increase penetration rates and reduce drilling operation costs. The present study aims to develop a fast and intelligent cascade control structure for a multi-degree-of-freedom drill string system under torsional vibrations. The proposed control configuration consists of two control loops in a cascade arrangement. The first controller estimates the top drive velocity reference from the actual drill bit velocity and its reference. The role of the second controller is to regulate the top drive velocity to its reference by generating the necessary torque for the drilling operation process to progress. Each control loop is designed based on a hybrid adaptive neuro-fuzzy PID and feedforward term. The latter assures fast regulation when there are sudden changes in operation. To evaluate the performance of the suggested cascade feedforward neuro-fuzzy PID (CFF-NFPID) control structure, extensive simulations were conducted using Matlab/Simulink. The simulation results clearly showed that the proposed CFF-NFPID controller provided high-performance control with variations in the weight on the bit and the desired drill bit rotary speed in comparison with that of cascade feedforward fuzzy PID, sliding-mode, cascade feedforward PID, cascade PID, and conventional PID controllers. Furthermore, the control robustness is very suitable despite the change in the system parameters.

A novel quadrotor carrying payload concept via PID with Feedforward terms

PurposeThis paper introduces control strategy to enhance the performance of a novel quadrotor unmanned aerial vehicle designed for medical payload delivery. The aim is to achieve precise control and stability when carrying and releasing payloads, which alter the quadrotor’s mass and inertia characteristics.Design/methodology/approachThe equations of motion specific to the payload-carrying quadrotor are derived. A feedforward-proportional-integral-derivative (FF-PID) control strategy is then proposed to address the dynamic changes during payload release. The PID components use propeller speed/orientation information for stability. FF terms based on derivatives of desired position/orientation variables enable adaptation to real-time mass fluctuations.FindingsExtensive simulations, encompassing various fault scenarios, substantiate the effectiveness of the FF-PID approach. Notably, our findings demonstrate superior performance in maintaining altitude precision and stability during critical phases such as takeoff, payload release and landing. Graphical representations of thrust and mass dynamics distinctly illustrate the payload release event. In contrast to the linear quadratic regulator (LQR) and conventional PID control, which encountered difficulties during the payload release process, our approach proves its robustness and reliability.Research limitations/implicationsThis study, primarily based on simulations, demands validation through real-world testing in diverse conditions. Uncertainties in dynamic parameters, external factors and the applicability of the proposed approach to other quadrotor configurations require further investigation. Additionally, this research focuses on controlled payload release, leaving unexplored the challenges posed by unforeseen scenarios or disturbances. Hence, adaptability and fault tolerance necessitate further exploration. While our work presents a promising approach, practical implementation, adaptability and resilience to unexpected events are vital considerations for future research in the field of autonomous aerial medical deliveries.Practical implicationsThe proposed control strategy promises enhanced efficiency, reliability and adaptability for autonomous aerial medical deliveries in critical scenarios.Social implicationsThe innovative control strategy introduced in this study holds the potential to significantly impact society by enhancing the reliability and adaptability of autonomous aerial medical deliveries. This could lead to faster and more efficient delivery of life-saving supplies to remote or disaster-affected areas, ultimately saving lives and reducing suffering. Moreover, the technology’s adaptability may have broader applications in fields like disaster relief, search and rescue missions, and industrial cargo transport. However, its successful integration into society will require careful regulation, privacy safeguards and ethical considerations to ensure responsible and safe deployment while addressing potential concerns related to noise pollution and privacy intrusion.Originality/valueWhile PID control of quadrotors is extensively studied, payload release dynamics have been overlooked. This research studies integration of FF control to enable PID adaptation for a novel payload delivery application.

Current Sensorless Pole-Zero Cancellation Output Voltage Control for Uninterruptible Power Supply Systems with a Three-Phase Inverter

This article presents a proportional–derivative (PD) type output voltage regulator without the current feedback, taking into account system parameter and load variations. The main advantages are given as follows: First, the first-order output voltage derivative observer is developed without the requirement of system parameter information, which makes it possible to stabilize the system without current sensing. Second, a simple self-tuner implements the feedback-loop adaptation by updating the desired dynamics accordingly. Third, the observer-based active damping injection for the PD-type controller results in the closed-loop system order reduction to 1 by the pole-zero cancellation, including the disturbance observer as a feed-forward term. The prototype uninterruptible power supply system comprised of a 3 kW three-phase inverter, inductors, and capacitors verifies the practical merits of the proposed technique for linear and nonlinear loads.

Attitude modelling and real-time robust control of a 3-DoF quadcopter UAV test bench

Abstract In this work, a three degrees-of-freedom (3-DoF) static quadcopter unmanned aerial vehicle (UAV) test-rig of a pendulum-type configuration is custom-designed, developed, instrumented, and interfaced with a PC. The rig serves as a test bed to develop high-fidelity mathematical models as well as to investigate autopilot designs and real-time closed-loop controllers’ performances. The Simulink Desktop Real-Time software is employed for the quadcopter’s attitude signals acquisition and real-time implementation of closed-loop controllers on a target microcontroller hardware. The mathematical models for pitch, roll, and yaw axes are derived via the first principle and validated with the experimental linear system identification (SI) techniques. Subsequently, employing the multi-parameter root contour technique, the classical proportional integral derivative (PID) controllers are designed and implemented in real-time on the quadcopter UAV test rig. This served as a benchmark controller for comparing it with an integral-based linear quadratic regulator (LQR) controller. Further, to improve the transient response of the LQR controller, a novel robust integral-based LQR controller with a feedforward term (LQR-FF) is implemented, which shows much superior performance than the benchmark and basic LQR controller. This work thus will act as a precursor for a more complex 3-DoF autopilot design of an untethered quadcopter.

A Model-Free Online Learning Control for Attitude Tracking of Quadrotors

This paper investigates the problem of attitude tracking in quadrotor unmanned aerial vehicles (UAVs) using a model-free online learning control (MFOLC) scheme. The attitude system, which is represented by unit quaternions, is considered in the presence of uncertain and unknown inertia parameters, time-varying external disturbances, and angular velocity measurement noise. A computationally low-cost control scheme consisting of a model-free baseline controller and a module capable of learning from previous control input is designed. The proposed controller does not require precise inertial parameters and does not involve feedforward terms that use these parameters and true system states. This ensures that the approach can protect the control effort from sensor noise as well as parameter uncertainty. We also show that all the signals in the closed-loop system are uniformly ultimately bounded. Comparative simulations and real-world experiments are conducted for validation, which demonstrate the effectiveness and fine performance of the proposed scheme.

LuGre model–based robust adaptive control for a pump-controlled hydraulic actuator experiencing friction

In this paper, a LuGre model–based robust adaptive control (RAC) approach is presented for a pump-controlled hydraulic actuator. We first decompose the LuGre friction model into its steady-state model and a lumped dynamic part applying the mean value theorem, which are compensated by a feedforward term and a robust adaptive term, respectively. The robust adaptive term also plays a part in mismatched disturbance attenuation. In addition, parametric uncertainties and matched disturbances are handled by σ-modified adaptation laws and a robust control law, respectively. The stability of the closed-loop system is proved via the Lyapunov analysis. The efficacy and robustness of the proposed approach are validated by comparative experiments. Compared with common adaptive friction compensation methods, the proposed method has a simpler structure, less computational burden, better control performance, and stronger robustness. Moreover, since the available information is separated from the LuGre model and acts as a model-based compensation term, the design conservativeness of RAC is effectively reduced.

Seamless PID–MPC Hybrid Control

It is common that PID control loops function satisfactorily most of the time, but that they have issues with violating input, state, or output constraints. While MPC solves this problem in principle, it is in practice not straightforward to replace a functioning PID controller with an MPC implementation. This is particularly true for loops that are critical to plant operation, where stops associated with controller replacement and tuning can turn out costly. We propose a novel configuration where an MPC controller is designed based on the PID closed-loop, and provides a feed-forward term to its control signal. This configuration enables a smooth transition between unconstrained PID operation and MPC-dominated control, governed by a single scalar parameter α. We demonstrate the approach using a relevant process industrial application: flotation level control in mineral enrichment. Using a practical example, we show how our approach results in a structure where the PID control loop can be kept, while leveraging the constraint-honoring advantage of MPC control.

Hybrid Flatness-Based Control of Dual Star Induction Machine Drive System for More Electrical Aircraft

Abstract This paper develops a precise method control system for tracking control of a power drive system based on a multi-phase machine under motor parameter and load torque variations. By adding a simple feedforward term based on the flatness theory, a conventional flux oriented control (FOC) can be enforced to have a perfect tracking performance under model parameter and load torque variations. Hence, a hybrid flatness-based control (HFBC) technique is applied to the control of a dual star induction machine (DSIM) and compared to a classical vector control strategy regarding tracking behaviour, robustness, and perturbations rejection. Finally, the simulation and experimental results are provided to verify the effectiveness of the proposed HFBC under uncertainties such as motor parameter and load torque variations. Furthermore, an enhancement of the drive system’s control performances is demonstrated by the improvement of the technique of separation of the objectives of tracking and disturbance rejection. The simulation and experimental results are presented, demonstrating the superiority of the HFBC.

2-DOF Preview Feedforward Sliding Mode Controller for the Control of Multivariable Process with Dead Time

This paper proposes a 2-DOF preview feedforward sliding mode controller (PFFSMC), which has a combination of feedback and feedforward terms in the sliding surface, for controlling the multivariable process with dead time, for both set point tracking and disturbance rejection. The proposed controller is applied for the control of the Wood and Berry binary distillation column having the composition of top and bottom products. The performance of the 2-DOF PFFSMC is compared with that of the 1-DOF preview sliding mode controller. The proposed controller delivered better responses for set point tracking and for disturbance rejection. The performance of the proposed 2-DOF PFFSMC is compared with the other controllers reported in the literature and, it was found that there was a significant reduction in the settling time by more than 76%, without any overshoot in the closed loop response. The proposed controller was robust against ±5% parametric uncertainties in gain, time constant, and dead time when these uncertainties were considered alone and together. The stability of the proposed controller was verified using the Lyapunov stability criterion.

Internal boundary control in lane-free automated vehicle traffic: Comparison of approaches via microscopic simulation

The recently introduced TrafficFluid concept proposes that automated vehicles drive lane-free, thus enabling capacity sharing between the two opposite road directions via real-time Internal Boundary Control (IBC). This novel traffic control measure was demonstrated, using macroscopic traffic flow models, to deliver unprecedented improvements of traffic flow efficiency. The present study completes and validates the IBC concept in a much more realistic way via microscopic simulation and active internal boundary moving, using the SUMO-based TrafficFluid-Sim simulation tool. To effectuate IBC, a Linear Quadratic Regulator (LQR), which is a feedback control scheme, is employed. In addition, to enhance the performance of the LQR controller, a feedforward term, accounting for external disturbances, i.e. entering flow and on-ramp flows, is also designed, leading to an augmented LQR-FF control scheme. The LQR and LQR-FF controllers are tested and compared in the created realistic environment, demonstrating how IBC may operate in practice to combat traffic congestion on highways.

Improved active disturbance rejection speed control for autonomous driving of high-speed train based on feedforward compensation.

Due to the complex and changeable train operation environment and the unstable and time-varying parameters, accurate modeling is limited. Therefore, a modified active disturbance rejection control algorithm based on feedforward compensation (FC-MADRC) is proposed targeting the speed control problem of trains under the circumstances of external disturbances, which reduces the dependence on the train model. Firstly, the state space equation is established based on the single-particle mathematical model of the train, and all the running resistances are regarded as disturbances. Secondly, the FC-MADRC algorithm is designed. Based on the terminal attractor function and the novel Sigmoid function, an improved tracking differentiator (ITD) is designed. An improved fal (nsfal) function with better smoothness is constructed by using the properties of the Dirac δ function, and an ameliorative nonlinear state error feedback (ANLSEF) and a modified extended state observer (IESO) are designed based on the nsfal function. Furthermore, based on the thought of PID, the integral term of error is introduced into ANLSEF for the nonlinear operation to reduce the steady-state error of train speed tracking. In order to promote the robustness and control accuracy of the system, the feedforward compensation term and disturbance compensation term are combined to perform dynamic compensation for disturbances in real time. Finally, the simulation is carried out with CRH380A train data. The results indicate that compared with conventional ADRC and 2DOF-PID, FC-MADRC has the more vital anti-disturbance ability and higher tracking accuracy. FC-MADRC has the advantages of solid anti-disturbance, fast response, and high tracking accuracy. Under the premise of external disturbance, it can still achieve accurate speed tracking under different road conditions.

Adaptive Second-Order Fixed-Time Sliding Mode Controller with a Disturbance Observer for Electronic Throttle Valves.

In order to enhance the precision and speed of control for electronic throttle valves (ETVs) in the face of disturbance and parameter uncertainties, an adaptive second-order fixed-time sliding mode (ASOFxTSM) controller is developed, along with disturbance observer compensation techniques. Initially, a control-oriented model specifically considering lumped disturbances within the ETV is established. Secondly, to address the contradiction between fast response and heavy chattering of conventional fixed-time sliding mode, a hierarchical sliding surface approach is introduced. This approach proficiently alleviates chattering effects while preserving the fixed convergence properties of the controller. Furthermore, to enhance the anti-disturbance performance of the ETV control system, an innovative fixed-time sliding mode observer is incorporated to estimate lumped disturbances and apply them as a feed-forward compensation term to the ASOFxTSM controller output. Building upon this, a parameter adaptive mechanism is introduced to optimize control gains. Subsequently, a rigorous stability proof is conducted, accompanied by the derivation of the expression for system convergence time. Finally, a comparison is drawn between the proposed controller and fixed-time sliding mode and super-twisting controllers through simulations and experiments. The results demonstrate the superiority of the proposed method in terms of chattering suppression, rapid dynamic response, and disturbance rejection capability.

Impact of Voltage-Loop Feedforward Terms on the Stability of Grid-Forming Inverters and Remedial Actions

This paper reveals the impact of voltage control loop feedforward terms on the stability of grid-forming inverters (GFMIs) connected to a grid. By deriving a mathematical model, this paper shows that unless the GFMI current control loop is fast enough, the feedforward terms in the voltage control loop may threaten the GFMI small-signal stability. To this end, a necessary and sufficient condition for GFMI stability is proposed, provided that the grid impedance at the point of connection is known. Furthermore, two easy-to-implement yet effective remedial actions are proposed to enhance stability. Aiming to preserve the control structure, the first remedial action re-tunes the voltage controller to satisfy the obtained stability condition, while the second remedial action incorporates simple gains to attenuate the feedforward terms. Moreover, to demonstrate the effectiveness of the second remedial action, the obtained necessary and sufficient stability condition is modified to include the proposed attenuation gain. Eventually, the accuracy of the stability analysis and the effectiveness of the proposed remedial actions are evaluated in simulation and experiment.

Particle-Based Optimization Algorithms for Longitudinal Control of Autonomous Vehicle: A Comparative Study

In order to improve the stability and performance of an autonomous vehicle, optimization needs to be explicitly performed in the controllers, which has an essential part in the tracking system. This work proposes a novel longitudinal control optimization scheme and a novel longitudinal controller consisting of a feed-forward and feedback term. The feed-forward term is inspired by the vehicle’s steady-state response, whereas the feedback term is a proportional-integral-derivative (PID) controller. Also, a model representing the longitudinal vehicle dynamics is designed based on physical phenomena affecting the vehicle. Besides, some nature-inspired optimization algorithms are used to determine the optimal model parameters and optimize the controller parameters, i.e., Particle Swarm Optimization (PSO), Accelerated PSO (APSO), Flower Pollination Algorithm (FPA), and Modified FPA (MFPA). The algorithms are compared in optimizing the longitudinal vehicle model and controller using the CARLA simulator, and stability tests are also done for each algorithm. In addition, the characteristics of several cost functions in controller optimization are inspected. The results show that the MFPA is the most stable algorithm, the proposed model represents the system satisfactorily, and optimizing the controller using a regularized cost function leads to better overall performance. Our code is available in https://github.com/fadamsyah/Particle-Based-Optimization-for-Longitudinal-Control.

FeedForward Super-Twisting Sliding Mode Control for Robotic Manipulators: Application to PKMs

This article deals with the development and implementation of a novel feedforward super-twisting sliding mode controller for robotic manipulators. A full stability analysis based on a Lyapunov candidate is established showing a local asymptotic finite-time convergence of the proposed controller in the presence of upper bounded disturbances. Its robustness toward parametric uncertainties and system disturbances, thanks to the super-twisting approach, is pointed out. In addition, the feedforward dynamic term of the proposed controller that can compensate for the model nonlinearities is not sensitive to measurement noise. Real-time experiments have been conducted on two parallel manipulators: a 5-DOF SPIDER4 PKM and a 3-DOF Delta PKM. The effectiveness of the proposed controller is validated in different scenarios, including the nominal case and robustness toward parametric variations (payload) and speed changes

Flocking and formation control for a group of nonholonomic wheeled mobile robots

The problem of flocking and formation of a group of nonholonomic wheeled mobile robot is addressed in this paper. Based on the cascade structure of the kinematic model, two kinematic controllers are proposed to achieve formation and flocking behaviors. The proposed control laws present a P and PI-like structure plus a feedforward term and do not require complex calculations. The interaction between the robots is modeled using graph theory. The performance of the proposed control laws is validated by experimental tests on a group of four differential-drive wheeled mobile robots.