Feedforward Gain Research Articles

Identification and compensation method for unbalance error in signal detection chain of Rate-Integrating hemispherical resonator gyro

In this work, a notable effective method is proposed to actualize the identification and compensation for unbalance error in signal detection chain of Rate-Integrating Hemispherical Resonator Gyro (RI-HRG). RI-HRG has excellent dynamic performance and measuring range, which has been verified in multiple field applications. Firstly, the unbalance error model is established with equivalent electrode-misalignment-angle and equivalent relative-chain-gain-deviation, considering about the effect of the inevitable signal coupling, assembly error and electronic components parameter inconsistency error. Then, a high-efficient and high-accuracy identification method is proposed based on the parameter estimation of the free vibration signal envelope, by which the adverse effect of gyro circumferential asymmetry is effectively suppressed. Finally, the compensation method based on feedforward gain controller is designed and implemented with digital control circuit. The experimental results show that the zero bias stability of RI-HRG is improved from 1.0461°/h to 0.0494°/h, which strongly prove the effectiveness of the proposed methods.

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.

Disturbance rejection design for Gaussian process-based model predictive control using extended state observer

Gaussian process (GP) regression has gained significant popularity in machine learning because it has the intrinsic capability to capture uncertainty in function prediction and requires a limited number of hyperparameters to be optimized. In this study, a Gaussian process model predictive control (GPMPC) algorithm is proposed to model the unknown dynamics of the process using Gaussian process regression. The GPMPC incorporates the expected variance of the GP model to account for the model's uncertainty and to achieve prudent control. Meanwhile, the extended state observer (ESO) is introduced for the GPMPC, which can estimate the unmodeled dynamics and unknown disturbance. With the designed feedforward gain, the proposed extended state observer-based GPMPC (GPMPC-ESO) method can achieve offset-free performance. Theoretical analysis is conducted to evaluate the stability and disturbance rejection performance of the control system. Finally, the algorithms are validated by simulation in continuous stirred tank reactor (CSTR) process control.

Research on nuclear reactor power control system of VVER-1000 with thermal energy supply system

Cogeneration nuclear power plants (NPP) can reduce carbon emissions and improve the economy to deal with climate problems. However, after adding the thermal energy supply system (TESS), the nuclear reactor power control system (NRPCS) is affected by the change in the relationship between energy supply and load. Therefore, the NRPCS of VVER-1000 with TESS (Ts-VVER) is studied. In this paper, first, the simulation model of Ts-VVER is established, with the extraction of steam from the main steam header. Second, dynamic characteristic analysis, coupling characteristic analysis, and energy balance relationship analysis are studied to evaluate the influence of Ts-VVER. Then, the NRPCS modified scheme is designed, and the new nonlinear feedforward gain curve is gotten from the original curve by translation. Finally, the designed NRPCS modified scheme is verified by typical conditions simulation. The modified scheme can offer a reference for the design of the NRPCS of other cogeneration NPPs.

Sampled-Data Cooperative Output Regulation: An Adaptive Distributed Continuous-Discrete Observer Approach

This paper studies the sampled-data cooperative output regulation problem for linear multi-agent systems. Firstly, a novel adaptive distributed continuous-discrete observer is established to recover the leader's state, which, on one hand, only relies on the sampling output of the leader, and on the other hand, does not need to store the sampled message from neighbors. Secondly, by solely making use of the digital states of both the agent and the distributed observer, a certainty equivalence control law is synthesized featuring a time-varying feedforward gain. It is rigorously proven that, with this time-varying feedforward gain, the proposed control approach can achieve exponential convergence of the tracking errors given arbitrary time-varying leader's signal, and the upper bound for the sampling intervals is explicitly given. Thirdly, for the class of chain-integrator multi-agent systems, the proposed control approach does not need any restriction on the upper bound of the sampling intervals, and thus would be more practical in certain application scenarios from the perspective of energy saving. The performance of the proposed control approach is validated by the simulation results of inverter-based distributed generation systems.

Pneumatic Bellows Actuated Parallel Platform Control with Adjustable Stiffness Using a Hybrid Feed-Forward and Variable Gain Integral Controller

Redundant cascade manipulators actuated by pneumatic bellows actuators are passively compliant, rugged and dexterous, making them exceptionally well suited for application in agriculture. Unfortunately, the bellows are notoriously difficult to precisely position. This paper presents a novel control algorithm for the control of a parallel platform actuated by pneumatic bellows, which serves as a module of a cascade manipulator. The algorithm combines a feed-forward controller and a variable-gain I-controller. The mathematical model of the module, which serves as the feed-forward controller, was created by applying two simple regression steps on experimentally acquired data. The gain of the I-controller is linearly dependent on the total reference error, thereby addressing the prevalent problem of “a slow response or excessive overshoot”, which, in the described case, the simple combination of a feed-forward and constant-gain I-controller tends to suffer from. The proposed algorithm was experimentally verified and its performance was compared with two controllers: an ANFIS controller and a constant gain PID controller. The proposed controller has outperformed the PID controller in the three calculated criteria: IAE, ISE and ITAE by more than 40%. The controller was also tested under dynamic loading conditions, showing promising results.

Data-driven optimal output regulation for unknown linear discrete-time systems based on parameterization approach

The output regulation problem has been studied based on a parameterization approach. Different from existing literature, the proposed method does not rely on prior knowledge of the system dynamics. Instead, it leverages state and input data to address the absence of information regarding unmodeled dynamics. Firstly, the output regulation problem is transformed into a stabilization problem by using coordination transformation. The feedback control gain is computed directly by solving an optimization problem using input and state data. The feedforward control gain is obtained by using data-based solutions of regulator equations. Secondly, the design of a dynamic feedback controller is also explored within the framework of a data-driven strategy. Thirdly, two algorithms corresponding to the optimal and dynamic data-driven output regulation problems are developed to implement the proposed data-driven method. Finally, a simulation example is carried out to illustrate the effectiveness of the developed data-driven approach.

Non-Predictive Model-Free Control of Nonlinear Systems with Unknown Input Time Delay.

This study presents a general framework for the control of unknown dynamic systems with unknown input delay. A concise output feedback control system is structured with tuning stabilization/dynamic response by an output feedback low gain, removing steady state error against step reference with a feedforward gain. A series of stability analyses are presented for the designed control systems, (1) a gain/phase margin theorem is proposed for stability analysis by regulating the feedback gain, and (2) a stability theorem based on rational function approximation of the time delay is presented for dealing with the transcendental polynomial characteristic equations, which is equivalent to the analysis from the algebraic polynomial characteristic equation. Both approaches give coherent results for stability analysis by regulating the feedback gain. The approaches are applicable to nonlinear systems, which are linearizable in the neighborhood of the operating points. The low complexity of the controllers does not require hard analytical derivation/numerical calculations to produce an acceptable control performance for the considered systems. Several representative simulation case studies provide demonstrations of computational experiments against those analytically derived and guidance for potential applications.

Voltage Control Strategy for Improving Disturbance Rejection Performance in Stationary Reference Frame During Parallel Operation of Multimodular UPS

This paper proposes a voltage control strategy to improve the disturbance rejection performance during the parallel operation of multi-modular uninterruptible power supply (UPS). In the standalone operation of UPS, feed-forward control can improve the dynamic performance of output voltage regulation. However, a circulating current can occur when feedforward control is applied in the parallel operation of UPS modules, causing uneven load sharing among the modules. In this study, the reason for the occurrence of the circulating current was analyzed using a circulating current impedance model. A partial feedforward control technique was proposed, which compensates for a portion of the load current by considering the circulating current impedance in the parallel operation of the UPS. However, this reduced the disturbance rejection performance compared with the standalone operation of the UPS, which uses full feedforward compensation gain. Therefore, an additional feedforward control technique was proposed to enhance the disturbance rejection performance. The effectiveness of the proposed control strategy was verified through the experimental result of the parallel operation of 500 W modular double-conversion UPSs.

Positioning Control of Robotic Manipulators Subject to Excitation from Non-Ideal Sources

The present work proposes the use of a hybrid controller combining concepts of a PID controller with LQR and a feedforward gain to control the positioning of a 2 DOF robotic arm with flexible joints subject to non-ideal excitations. To characterize the performance of the controls, two cases were studied. The first case considered the positioning control of the two links in fixed positions, while the second case considered the situation in which the second link is in rotational movement and the first one stays in a fixed position, representing a system with a non-ideal excitation source. In addition to the second case, the sensitivity of the proposed controls for changes in the length and mass of the second link in the rotational movement was analyzed. The results of the simulations showed the effectiveness of the controls, demonstrating that the PID control combined with feedforward gain provides the lowest error for both cases studied; however, it is sensitive to variations in the mass of the second link, in the case of rotational movements. The numerical results also revealed the effectiveness of the PD control obtained by LQR, presenting results similar to the PID control combined with feedforward gain, demonstrating the importance of the optimal control design.

Model‐Free Cooperative Optimal Output Regulation for Linear Discrete‐Time Multi‐Agent Systems Using Reinforcement Learning

In this paper, an off‐policy model‐free algorithm is presented for solving the cooperative optimal output regulation problem for linear discrete‐time multi‐agent systems. First, an adaptive distributed observer is designed for each follower to estimate the leader’s information. Then, a distributed feedback‐feedforward controller is developed for each follower to solve the cooperative optimal output regulation problem utilizing the follower’s state information and the adaptive distributed observer. Based on the reinforcement learning method, an adaptive algorithm is presented to find the optimal feedback gains via online data collection from system trajectory. By designing a Sylvester map, the solution to the regulator equations is calculated via data collected from the optimal feedback gain design steps, and the feedforward control gain is found. Finally, an off‐policy model‐free algorithm is proposed to design the distributed feedback‐feedforward controller for each follower to solve the cooperative optimal output regulation problem. A numerical example is given to verify the effectiveness of this proposed approach.

Reinforcement learning and cooperative [formula omitted] output regulation of linear continuous-time multi-agent systems

This paper proposes a novel control approach to solve the cooperative H∞ output regulation problem for linear continuous-time multi-agent systems (MASs). Different from existing solutions to cooperative output regulation problems, a distributed feedforward-feedback controller is developed to achieve asymptotic tracking and reject both modeled and unmodeled disturbances. The feedforward control policy is computed via solving regulator equations, and the optimal feedback control policy is obtained through handling a zero-sum game. Instead of relying on the knowledge of system matrices in the state equations of the followers’ dynamics and initial stabilizing feedback control gains, a value iteration (VI) algorithm is proposed to learn the optimal feedback control gain and feedforward control gain using online data. To the best of our knowledge, this paper is the first to show that the proposed VI algorithm can approximate the solution to continuous-time game algebraic Riccati equations with guaranteed convergence. Finally, the numerical analysis is provided to show the effectiveness of the proposed approach.

Component-Level Semiconductor Loss Balancing for IGBT Based High Power MMC Through Insertion Index Modification

Modular multilevel converter (MMC) is the state-of-the-art converter topology in HVdc transmission applications. The reliability and lifetime of MMCs are strongly dependent on the health of the internal power semiconductors. The operating loss of power semiconductors, which is one of the dominant factors affecting component aging, is not uniformly distributed between the top and bottom switches in the same submodule (SM) due to the dc bias in the arm current. Such loss imbalance leads to differences in lifetime of semiconductors and reduces the reliability of SM. Especially under inverter conditions, the bottom insulated gate bipolar transistor (IGBT) in SM is subjected to a severe thermal stress and has a relatively high failure rate for the thermal vulnerability of IGBT. To extend the lifetime and improve the reliability, this article proposes a component-level loss balancing method. It is achieved by insertion index modification based on a feed-forward gain controller. The proposed method can improve the loss distribution among the top and bottom semiconductors without side effects on ac and dc outputs. Its effectiveness and feasibility are validated through simulation and experimental results.

Sensing Design, Trajectory Planning, and Motion Control of a Cable-Driven Redundant Manipulator Composed of Quaternion Joints

Abstract A cable-driven redundant manipulator (CDRM) composed of quaternion joints has important applications in confined space, including minimal invasive surgery, aircraft parts assembly, environment exploring, and so on. Benefitting from the unique joint characteristic and cable routing, it can achieve a larger workspace with fewer driving modules than traditional universal joint CDRM. However, the positioning accuracy of the end-effector suffers from the lack of joint feedback information and the delay effect of cable driving mechanisms. In this paper, we propose an equivalent sensing method and design corresponding sensors for each quaternion joint, and develop a high precision controller for the whole manipulator. The motion sensing of the quaternion joint is achieved by establishing the kinematics between its bending pose and middle limb joints. To realize real-time estimation, the fitting technique is adopted. To improve the efficiency of path planning, a geometric iterative inverse kinematics approach for quaternion joint CDRM is proposed based on the isosceles trapezoid simplified model. Furthermore, an accurate controller is designed by combining the feedforward gain and modified PID feedback control. Finally, an 8DOF CDRM prototype with four quaternion joints is developed, and the experiment verifies the effectiveness of the proposed method.

LQ optimal robust multivariable PID control for dynamic positioning of ships with norm-bounded parametric uncertainties

The design of a suitable controller for dynamic positioning (DP) of ships is a challenging task keeping the hydrodynamic uncertainties in mind. The magnitude and rate constraints on the actuators make the problem more difficult. The present work employs a two-degree-of-freedom (2-DOF), multivariable, proportional–integral–derivative (PID) control for DP of a ship. To design the controller, first, the ship dynamics with hydrodynamic parameter uncertainties is represented in an uncertain state-space descriptor form. Then, the design of feedback gains of 2-DOF PID controller for the uncertain descriptor plant is converted into a state feedback design for an augmented uncertain descriptor plant. Next, a linear matrix inequality-based condition is obtained to solve this state feedback problem in order to ensure a desired linear quadratic (LQ) performance, even in presence of uncertainties. Finally, to further improve the tracking performance, the feedforward gain of the 2-DOF PID controller is designed using H∞ approach. The DP performance of the proposed controller is tested for the considered ship model along with uncertainties, actuator constraints, and environmental disturbances. A comparison with the existing PID controllers is also carried out to show superiority of the proposed controller.

Optimal Output Regulation for General Linear Systems via Adaptive Dynamic Programming.

In this article, we consider an adaptive optimal output regulation problem for general linear systems. The purpose of the optimal output regulation problem is to guarantee the stability of the closed-loop system and disturbance rejection, as well by minimizing some predefined performance indices. It can be realized by using an optimal controller, in which both optimal feedback control gain and optimal feedforward control gain are included. First, an adaptive dynamic programming (ADP) technique is used to solve the optimal feedback control gain. Next, the unknown system matrices of the plant are explicitly computed. In addition, based on the property of the minimal polynomial, the coefficient of the exogenous disturbance in the expression of the regulated output can also be calculated. Finally, according to the regulator equation, an extra cost function is given, which aims to obtain the optimal feedforward control gain. The linear vector space optimization methods are used to solve the optimal problem. As a result, the linear optimal output regulation problem can be solved by the approximately optimal feedback and feedforward control gains.

Fixed‐time output regulation of linear delay systems by smooth time‐varying control

AbstractThis article investigates the fixed‐time output regulation problem (FxTORP) for linear systems in the presence of input delay. A linear controller consisting of the linear periodic delayed feedback (PDF) gain and the feedforward gain obtained by solving regulator equations is designed, such that FxTORP is addressed. If only the measurable output can be used for feedback, a linear observer with periodic coefficient and artificial delay is designed so that its state converges to the state of the augmented system at a prescribed finite time. Based on the estimated state, the output regulation problem can also be solved by using observer‐based output feedback. The most significant advantages of this article are that the PDF gain can be taken as smooth and the output regulation problem is achieved within a prespecified regulation time. Finally, a simulation example is given to substantiate the validity of the proposed approaches.

Generation of Three-Mode Entanglement Based on Parametric Amplifiers Using Quantum Entanglement Swapping

Quantum entanglement swapping is one of the most promising quantum techniques to create or manipulate large-scale multi-mode entanglement between two distant quantum entangled systems. In this work, a scheme for the generation of three-mode entanglement based on parametric amplifiers using quantum entanglement swapping has been proposed. The newly generated three-mode entanglement is always present in the whole power gain region from parametric amplifiers and its dependence on transmission loss and feedforward gain is also investigated. In addition, the effects of power gain, transmission loss, and feedforward gain on the two-mode entanglement of the three pairs in the newly generated three-mode entanglement have also been analysed in detail. The results presented here may find some practical applications in quantum secure communication.

High-Performance Digital Multiloop Control of LLC Resonant Converters for EV Fast Charging With LUT-Based Feedforward and Adaptive Gain

The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> resonant converter is typically adopted in battery charging applications due to its excellent performance in terms of efficiency, power density, and wide input/output voltage regulation. However, this converter is a complex high-order system characterized by a strong nonlinear behavior, featuring large variations of the small-signal gain/phase and pole location depending on the operating point. Consequently, these features pose substantial challenges in designing a closed-loop controller and providing constant dynamical performance over a wide operating range. Therefore, this article proposes a digital multiloop control strategy for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> resonant converters ensuring constant closed-loop bandwidth and excellent disturbance rejection performance across the complete converter operating region. The control scheme consists of two cascaded voltage and current loops. To design and tune these controllers, a simplified <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> dual first-order small-signal model is proposed. The system nonlinear behavior affecting the current control loop is counteracted by a real-time controller gain adaptation process, which ensures constant control bandwidth. In particular, the adaptive gain values are provided by a static switching frequency lookup table obtained experimentally. Moreover, the steady-state switching frequency value is fed forward at the output of the current loop regulator, providing a further dynamical performance enhancement. The proposed control strategy and the controller design procedure are verified both in simulation and experimentally on a 15-kW <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> converter prototype. The results demonstrate the superior reference tracking and disturbance rejection performance of the proposed control strategy with respect to a state-of-the-art solution based on a proportional–integral regulator.

Stability Improvement and Overshoot Damping of SS-Compensated EV Wireless Charging Systems With User-End Buck Converters

The multiple fluctuations, such as grid DC input voltage, mutual inductance and the plug-in and plug-out of battery, may lead to instability and deterioration of dynamic performance of electric vehicle (EV) wireless power transfer (WPT) system. The overshoot issue can bring great current stress to EV WPT system, and may induce potential disastrous malfunction of the lithium-ion (Li-ion) battery. This study theoretically reveals the slow dynamic response and large overshoot of a traditional WPT system. For solving these issues, a reliable adaptive feedforward control scheme is proposed and applied in the user-side DC-DC converter, where the communication unit is eliminated. The feedforward loop is proved theoretically to suppress overshoot and system dynamic response. Besides, the feedforward control increases the selective range of control parameters, which can improve the system dynamics. Experiment results verifies that the proposed adaptive feedforward gain allows faster dynamics, and the aforementioned disturbances in EV WPT system can be solved while the system performance is not affected.