Feedforward Term Research Articles

Quantitative Tracking Error Analysis and Feedforward Compensation Under Different Model-Based Feedforward Controllers in Different Control Architectures

This article presents quantitative analysis on the tracking error under different model-based feedforward controllers, such as zero-phase-error tracking control, zero-magnitude-error tracking control, nonminimum-phase-zero-ignore tracking control, in different two-degree-of-freedom control architectures. Analysis shows that, even there is no model uncertainty, extra feedforward terms like velocity, acceleration, jerk, and snap feedforward are required for further compensation, and that noncausal and causal implementation of these model-based feedforward strategies will lead to different tracking errors and require different extra compensation. Based on the analysis, an algorithm to tune the extra feedforward terms is proposed. Simulation and experiment on an ultraprecision motion system both well validate the theoretical analysis and the proposed algorithm.

Permanent magnet synchronous motor algorithms based on nonlinear identification generalized predictive and Intelligent fuzzy control system

A control strategy of permanent magnet-oriented field synchronous motor based on intelligent fuzzy control system and generalized predictive control with non-linear identification is proposed to develop the effectiveness of the controlling method of constant magnet-oriented field synchronous motor, the accessor can be split into stabilization control part and intelligent control part. The input of traditional feedback control is used as the stabilization control part, while the feed-forward is incorporated into the intelligent part to compensate for the uncertainties of repetitive load torque and model parameters. The proposed feed forward compensation term uses simple learning rules without any load torque disturbance observer. The additional learning feed forward term does not require information about motor parameters and load torque values, it is insensitive to load torque uncertainty and model parameters, and does not need to identify the system model. With that, the solidness and intermingling confirmation of the proposed control framework reaction is given. The exploratory outcomes demonstrate that the proposed technique has littler speed overshoot list, and the heap torque against aggravation capacity list is improved by over 30%.

Distributed Incremental Adaptive Filter Controlled Grid Interactive Residential Photovoltaic-Battery Based Microgrid for Rural Electrification

In this article, a distributed incremental adaptive filter (DIAF) controlled utility interfaced photovoltaic (PV) - battery microgrid system is presented with power quality features. From protection aspects, grid tied solar inverters are required to shut down at loss of the utility. However, the multi-purpose PV-battery system is developed to provide energy to the critical loads, even at loss of distribution network. The bidirectional controlled converter with a battery also mitigates the intermittency of a PV array under rapid variations in the weather. The extracted maximum power is supplied to the voltage source converter (VSC), which is transferred to the nonlinear loads and the utility. The distributed incremental adaptive filter is used to control the VSC with contribution of PV power and the battery. In addition, the DIAF control provides harmonics mitigation, load balancing and power factor improvement functionalities in order to deal with system connected with nonlinear loads. A PV power feed-forward (PVFF) term is incorporated in the current control for injection of active power to the utility as well as to improve the dynamic operation of residential PV-battery microgrid. The battery energy storage (BES) reduces the fuel bills and it is also utilized to provide smoothing attributes to the microgrid. The effectiveness of PV-battery microgrid is validated experimentally developed in the laboratory.

Resolved-Acceleration Control of Serial Robotic Manipulators Using Unit Dual Quaternions

A new method for resolved-acceleration control of serial chain manipulators has been proposed which uses dual quaternion representation of screw-based motion variables, i.e. pose, velocity and acceleration. The corresponding coupled controller considers both translation and orientation errors simultaneously for trajectory tracking and utilizes spatial acceleration to compute the feedforward compensation term for feedback linearization. The proposed coupled control law was validated on a robotic arm along a pre-defined trajectory. The controller demonstrated an improved trajectory tracking performance as compared to the conventional decoupled resolved-acceleration controller which treats translation and orientation error separately.

Contact Force Estimation Method of Legged-Robot and Its Application in Impedance Control

Legged robots have extremely strong adaptability in different terrain environment and their stable walking in the wild is still a current research hotspot. Although they have shown great motion performance in recent years, most of them rely on high-performance sensors, especially force sensors settled on foot. However, it is impractical to select special forces sensors in the field environment, and the performance degradation and noise during the usage will bring fatal control defects. In order to solve this problem, we propose a foot contact force estimation method that does not require force sensors, and applies the estimated contact force to the impedance control of the legged robot to achieve the robot's active compliance control. The method of force estimation is based on the generalized momentum of the robot. It only needs to provide the position information of the joint and the information of the applied control torque. The designed feedforward and compensation terms effectively improve the speed and accuracy of the force estimation. We improved the response speed of the system to the contact force by improving the structure of the impedance control, and applied the estimated contact force to the impedance control to achieve the stable motion of the quadruped robot. Simulation experiments verify the effectiveness of the proposed force estimation method.

Gap Opening Controller Design to Accommodate Merges in Cooperative Autonomous Platoons

Abstract In this paper, a cooperative platoon-based gap opening controller is developed. The intended application is gap creation in cooperative platoons to accommodate merges with spatial restrictions. Therefore, the main objective is to execute the maneuver in a predefined time. The controller design is based on a regular cooperative adaptive cruise control algorithm with an additional feedforward term for a desired gap. Experimental validation of the controller is performed with small mobile robots. The proposed control strategy is capable of opening the gap in a predefined time. In future work, this strategy can be used in the design of a merging algorithm specifically for CACC platoons.

A Chattering-Free Sliding Mode Filter Enhanced by First Order Derivative Feedforward

Noise reduction is one of the important issues for feedback control systems. Toward this problem, this paper proposes a new sliding mode filter, which is an improvement of Lv et al. 's parabolic sliding mode filter. The proposed filter employs a first-order derivative feed-forward term for increasing both tracking and noise attenuating performances. Its discrete-time algorithm is derived by applying the implicit-Euler discretization, and it realizes exact convergence without producing chattering in discrete-time implementation. The effectiveness of the proposed filter is evaluated through an open-loop and a closed-loop numerical examples.

Controller structure for high response engine exhaust throttles

Exhaust throttles are widely used as cost-effective endurance brakes on commercial vehicle diesel engines. To fulfil the requirements as endurance brakes exhaust flaps have only two states: fully opened and fully closed. However, there are several possible new applications, suggested by the authors, in which exhaust throttles could be utilised. To provide these functionalities a backpressure controller that can adjust the exhaust manifold pressure arbitrarily is needed. In this paper, the design and performance evaluation of an exhaust pressure controller is described. A first engineering principle-based, mean-value, nonlinear model of the engine and the actuator is described and validated with test bench measurements. Based on the nonlinear model a feedforward term was obtained. As feedback, an LQ servo controller was designed. The controller performance and the compliance of requirements was evaluated in three different test cycles on a medium-duty diesel engine, simulating brake blending, thermomanagement, and EGR support operations.

Single Stage Autonomous Solar Water Pumping System Using PMSM Drive

This article presents a single stage standalone solar photovoltaic (SPV) array fed water pumping system using a permanent magnet synchronous motor (PMSM). The vital contribution of this work includes: 1) development of the novel modified vector control, which improves the torque response of the system, 2) development of a novel single stage variable step size incremental conductance technique, which provides a fast maximum power point tracking and eliminates the need of intermediate stage dc–dc converter, and 3) introduction of SPV power feed-forward term, which accelerates the overall response of the system under dynamic conditions. This system includes a SPV array, a three-phase voltage source inverter (VSI), a PMSM and a pump. The SPV array converts solar energy into electrical energy. The VSI acts as power processing unit, which supplies desired currents to drive the PMSM. As the PMSM rotates, the pump coupled to the motor accomplishes the objective of water pumping. This system is modeled and simulated using MATLAB/Simulink with available simpower system toolbox and the behavior of the system under varying atmospheric conditions are validated experimentally on a developed prototype in the laboratory.

Enhanced DVR Control System Based on the Harris Hawks Optimization Algorithm

The dynamic voltage restorer's (DVR) transient, steady-state, and dynamic responses are essential requirements for protecting sensitive loads against upstream voltage disturbances via the DVR's ride-through capabilities. DVRs also look after transient oscillation at the instant of entering, and /or exiting by the DVR. This paper presents an enhanced, optimized, and less complex DVR control system structure, which is capable of improving the transient, steady-state, and dynamic responses as well as eliminating inherent transient oscillations. The control system comprises a closed-loop feedback control signal and feedforward upstream disturbance detection signal. Incorporating the feedforward term helps, dramatically, in improving the system response and eliminating the transient oscillations in the load voltage. The error signals are adapted using a PI controller to make the load voltage faithfully track its predefined reference waveform. The controller is implemented in the dq synchronous rotating reference frame. The parameters of the PI controller are selected using modern population-based optimization called the Harris Hawks Optimization (HHO) technique. The results obtained using the HHO technique are compared with two other optimization algorithms, namely Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). The results show that the HHO gives the best system response. The system is simulated using MATLAB/Simulink and the validation via Typhoon HIL402 real-time emulator. Both HIL402 validation and simulation results show that the proposed control scheme recovers normal operation against voltage disturbance within approximately 1.2 milliseconds without overshoot with steady-state error near zero and significantly dampens the inherent voltage oscillation that occurs at the instant of DVR entrance and/or exit.

Observer‐based compensation control of servo systems with backlash

AbstractFor compensating backlash phenomenon in servo systems, the authors propose an observer method in this paper to estimate both system states and vibration torque before controller design. First, a systematic scheme is given to obtain plant parameters, which is very important in observing system states. This is a parameter estimation principle that gives a crude estimation and computes the differences between the crude and true values. As a result, the precise value of the parameters is obtained by adding together the crude value and the difference. Then, based on the precise estimated parameters, an extended state observer (ESO) is designed to obtain feedback and feedforward signals. Consequently, robust compensation control is achieved by designing an output feedback controller, consisting of a feedback term and a feedforward term. Finally, in order to validate the proposed approach, extensive experiments are performed on a practical servo system with backlash nonlinearity.

An Enhanced Linear Active Disturbance Rejection Rotor Position Sensorless Control for Permanent Magnet Synchronous Motors

An enhanced linear active disturbance rejection controller (ELADRC) based rotor position sensorless field-oriented control scheme for the permanent magnet synchronous motor (PMSM) drivers is proposed in this article. The ELADRC consists of two linear extended state observers (LESOs) and a proportional current controller. One LESO is designed to estimate the back electromotive force (EMF), which is treated as the external disturbance. Then, the rotor position and speed are obtained from the estimated back EMF without any phase delay or chattering problem. The other LESO is designed to estimate the internal disturbances, such as the parameter and current regulation quality variations. The estimated total disturbance is used as a feedforward compensation term in the current control loop to improve the current regulation quality of the plant, which further improves the rotor position estimation performance. The plant combined with the two LESOs is equivalent to an integrator with a unity gain, which is controlled by a simple proportional current controller to generate the desired voltage vector for the pulsewidth modulation operation. Finally, the stability of the closed-loop PMSM drive system with the ELADRC-based scheme is analyzed. Based on the analysis, the parameters of the ELADRC are designed. The proposed scheme is validated by the experimental results for a 275-W salient-pole PMSM drive in which the PMSM is similar to the traction motor used in Toyota Prius hybrid electric vehicles at a reduced scale.

Adaptive RISE Control of Hydraulic Systems With Multilayer Neural-Networks

This paper focuses on developing an advanced nonlinear controller for hydraulic system to achieve asymptotic tracking with various disturbances. To accomplish this study, a multilayer neural-networks (NNs) estimator is first developed to improve the compensation accuracy of model-based feedforward control terms, which can greatly reduce the uncompensated disturbance, then a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the multilayer NNs estimator to deal with the residual mismatched disturbance, in which the RISE feedback gain is adapted online to further decrease the high-gain feedback. At last, by considering the inwardness of matched disturbance in hydraulic systems, it is estimated by another multilayer NNs fully with the residual functional reconstruction inaccuracies handled by a novel adaptive term. As a result, theoretical analysis reveals that the proposed controller guarantees a semiglobal asymptotic stability. Extensively comparative experimental results verify the priority of the proposed control strategy, and a 0.2% dynamic tracking accuracy is achieved.

Output feedback reinforcement learning based optimal output synchronisation of heterogeneous discrete‐time multi‐agent systems

This study proposes a model-free distributed output feedback control scheme that achieves synchronisation of the outputs of the heterogeneous follower agents with that of the leader agent in a directed network. A distributed two degree of freedom approach is presented that separates the learning of the optimal output feedback and the feedforward terms of the local control law for each agent. The local feedback parameters are learned using the proposed off-policy Q-learning algorithm, whereas a gradient adaptive law is presented to learn the local feedforward control parameters to achieve asymptotic tracking of each agent. This learning scheme and the resulting distributed control laws neither require access to the local internal state of the agents nor do they need an additional distributed leader state observer. The proposed approach has the advantage over the previous state augmentation approaches as it circumvents the need of introducing a discounting factor in the local performance functions. It is shown that the proposed algorithm converges to the optimal solution of the algebraic Riccati equation and the output regulator equations without explicitly solving them as long as the leader agent is reachable directly or indirectly from all the follower agents. Simulation results validate the proposed scheme.

Deadbeat Predictive Current Control for Permanent Magnet Synchronous Machines With Closed-Form Error Compensation

Deadbeat predictive current regulator features fast dynamic responses. However, it suffers from the steady-state current tracking error in a practical system due to the plant uncertainties, particularly the inductances. Instead of using observer-based disturbance voltage feedforward methods, this article proposes a new closed-form method to directly compensate the current tracking errors with a simple feedforward term added to the voltage commands. Zero steady-state error is achieved with negligible computation compared to the observer-based methods. The new method is first derived to tackle the inductance mismatch in the surface-mount permanent magnet synchronous motor, then the system close-loop transfer function is established to prove that the proposed method guarantees the zero steady-state error even with mismatches of the stator resistance and rotor flux linkage. Furthermore, based on the proposed compensation method, noise suppression schemes are added and designed to reduce high-frequency noise sensitivities in practical systems. Finally, the proposed method is extended to the interior permanent magnet synchronous motor (IPMSM). IPMSM system simulation and 68.5-kW experimental results are provided to validate the proposed method.

Analysis and Suppression of Slotting and Cross-Coupling Effects on Current Control in PM Synchronous Motor Drives

This paper proposes a d–q cross-coupling current controller for permanent magnet synchronous motor (PMSM) drives. Slotting and cross-coupling effects in PMSMs cause the effective air-gap length to vary with the rotor angle and distort the distribution of the air-gap flux. Such distortions have a significant influence on the current control by changing the relationship between the stator currents and voltages. To investigate their effects, a d–q model is established in this paper, which is suitable for describing the voltage characteristics of the actual PMSMs. The model contains the angle-dependent parameters, the cross-coupling inductance between d–q axes, and the q -axis permanent magnet flux linkage, unlike the ideal d–q model. The transfer function matrix from the d–q currents to d–q voltages of PMSM is newly derived from the model. Based on that, the current controller with the feedback and feedforward terms of 2-by-2 matrix is proposed. It is designed so that the independent gains are in low-pass filter forms and the coupling control gains are zero with eliminating interference between d–q axes. The proposed controller contributes to providing the stable control performance by canceling the slotting and cross-coupling effects. The performance of the proposed current controller is verified by experimental results.

Self‐regulated DC‐link control of synchronous reluctance motor‐driven solar water pumping system

This study deals with a two-stage photovoltaic (PV) array-fed irrigation pump using a synchronous reluctance (SynREL) motor drive. In this scheme, a boost converter is utilised for harvesting maximum available power from a PV array through an incremental conductance-based maximum power point tracking algorithm. Here, it feeds power to a voltage source inverter through a DC-link capacitor. The prime objective of the proposed system is to provide water supply for domestic and irrigation purposes; therefore, to avoid complexity and for increased reliability, the speed/position sensor is eliminated. A speed/position observer is utilised for the estimation of angular position of SynREL motor. A PV feed-forward term is used to estimate the reference speed, which aids in enhancing the transient behaviour of proposed system. Moreover, the control is inherently resistant to the ageing-related variation in pump's constant. The applicability of proposed water pumping system is verified through test results, recorded on a developed prototype in the laboratory under varying atmospheric conditions.

Three-Phase Grid-Interactive Solar PV-Battery Microgrid Control Based on Normalized Gradient Adaptive Regularization Factor Neural Filter

In this article, a normalized gradient adaptive regularization factor neural filter based control is presented for a three-phase grid interfaced solar photovoltaic (PV)-battery energy storage microgrid system. An incremental conductance (INC) technique is utilized for the peak power extraction of a solar PV array. A battery is connected through a bidirectional converter at dc-link of voltage-source converter (VSC), and it charges and discharges as per load variation and enhances the reliability of the system. This dc–dc converter also regulates the dc-link voltage for maximum power point tracking (MPPT). This neural filter based current controller improves the dynamic behavior of the proposed system and feeds active power to the utility grid by utilizing the feed-forward term of solar PV power under variable atmospheric scenarios. A power electronics switch is used for VSC mode shifting operation between current control in the grid-connected mode and voltage control in an islanded mode to ensure continuous and adequate power to the nonlinear load. The discrete proportional and resonant (PR) controller is used for the voltage control in an islanded mode to reduce the steady-state error between sensed and reference load voltages. The voltage controller also regulates the frequency. Simulations of the microgrid system are carried out by utilizing MATLAB/Simulink software to show the effectiveness of control technique. The performance of the system is found satisfactory for various operating conditions such as load variation, load unbalancing, and solar insolation change, and validated through test results on a developed laboratory prototype.

Implementation of PMSM Drive for a Solar Water Pumping System

This paper proposes the design and experimental investigation of fuzzy precompensated hybrid proportional-integral (PI) controller for a permanent magnet synchronous motor (PMSM)-driven standalone solar water pumping system. A conventional PI controller usually has fixed gains, which makes them quite sensitive to the parameter variations. In order to improve its performance, both during dynamic and steady-state conditions, the presented controller introduces a fuzzy logic controller, which processes the speed error. The speed along with the processed output is inputted to the PI controller for speed control of PMSM. This topology uses a solar photovoltaic (PV) array to convert the solar power into electrical power. The energy obtained is utilized to rotate the PMSM using a 3- φ voltage-source inverter. The PMSM is coupled to a pump, which performs the water pumping. An intermediate stage dc–dc converter is utilized to maximize the power output using an incremental conductance algorithm. A PV feed-forward term is incorporated to provide an accelerated performance. This topology is modeled and its response is manifested through simulation studies using MATLAB/Simulink under different atmospheric conditions. A hardware validation of it is also carried out using a digital signal processor controller (dSPACE DS-1004) on a developed laboratory prototype.

Automated recovery of damaged audio files using deep neural networks

In this paper, we propose two methods to recover damaged audio files using deep neural networks. The presented audio file recovery methods differ from the conventional file carving-based recovery method because the former restore lost data, which are difficult to recover with the latter method. This research suggests that recovery tasks, which are essential yet very difficult or very time consuming, can be automated with the proposed recovery methods using deep neural networks. We apply feed-forward and Long Short Term Memory neural networks for the tasks. The experimental results show that deep neural networks can distinguish speech signals from non-speech signals, and can also identify the encoding methods of the audio files at the level of bits. This leads to successful recovery of the damaged audio files, which are otherwise difficult to recover using the conventional file-carving-based methods.