Fast Tracking Performance Research Articles

Modified active disturbance rejection control based on gain scheduling for circulating fluidized bed units

Circulating fluidized bed (CFB) units are extensively operated in China due to their wide fuel adaptability, low emissions and high combustion efficiency. Nevertheless, CFB units are facing many control challenges due to their strong nonlinearity and large lag characteristics. To handle these control challenges, a modified active disturbance rejection control based on gain scheduling is structured in this paper. Firstly, a decentralized active disturbance rejection control strategy based on gain scheduling is designed by analyzing control difficulties of CFB units. Then, the parameter tuning and scheduling methods are provided, and the convergence of the extended state observer during the scheduling process is derived theoretically. The advantages of the proposed method in tracking performance, disturbance rejection performance, and ability to reject fuel quality fluctuation and uncertain heat transfer coefficients are illustrated by comparative simulations. Finally, the proposed control strategy is practically applied to the main steam pressure system of a 300 MW CFB unit. Running data demonstrate that it has a faster tracking performance and better disturbance rejection ability in [50∼100]% of the rated load, where the hourly average integral absolute error index has decreased obviously, and it shows a good field application prospect.

Adaptive predefined-time tracking control of uncertain permanent-magnet synchronous motor drive chaotic system

A predefined-time tracking control algorithm is formulated for the Permanent Magnet Synchronous Motor(PMSM) driver system subjected to chaotic oscillations and undeterministic parameters, which can determine the upper bound of settling-time by controller gains. Radial Basis Function Neural Networks(RBFNNs) are employed to approximate the unknown nonlinear functions as universal approximators. The innovative predefined-time tracking differentiators are constructed to estimate the derivatives of the virtual inputs, resolving “the explosion of complexity” in traditional backstepping method. Then, an adaptive predefined-time controller is proposed in the backstepping framework. Lyapunov’s theoretical analysis proves that all signals in the closed-loop systems are uniformly ultimately bounded and the output tracking errors can converge to a small neighborhood of the origin within the predefined-time. Finally, simulation studies are performed to demonstrate that the proposed control scheme can quash the chaotic behaviors of the PMSM drive system and ensure fast-tracking performance even under unknown parameters.

Frequency analysis of a discrete-time fast nonlinear tracking differentiator algorithm based on isochronic region method

<p>In fault detection, feedback control, and other fields, real-time differential estimation of a given signal in a complex noise environment is an important but challenging task. In this paper, a discrete-time fast nonlinear tracking differentiator (FNTD) based on hyperbolic tangent functions was proposed. To start, the differential signal acquisition problem was equated to the time-optimal control (TOC) law for constructing a double-integral system using a state feedback approach. Next, the FNTD algorithm based on the hyperbolic tangent function was presented by utilizing the isochronic region (IR) method in the discrete time domain. Then, the frequency-domain characteristics of the FNTD were analyzed and the rule for tuning the parameters was provided by the frequency scan test method. Finally, the simulation results demonstrated that the proposed FNTD had fast and accurate tracking performance, as well as excellent filtering and differential extraction capability compared with other differentiators.</p>

Model predictive current control with a finite set of novel voltages and modulator in permanent magnet synchronous motor drives

AbstractFinite control set model predictive control (FCS–MPC) has been deployed extensively in electric motor drives and power electronics applications. Many advantages, including fast transient response, have been reported. However, the improvement of its steady‐state performance, that is, suppression of current ripple, is one of the main problems of a conventional FCS–MPC strategy. This article presents a current control strategy based on FCS–MPC using the concept of variable voltage smoothing. In the proposed method, a finite set of novel voltage vectors, produced by the smoothing process, are introduced as candidate control input candidates, and the controller generates the optimum output voltage using a modulator integrated with the FCS–MPC scheme. Thus, the voltage candidates are generated flexibly, and a suitable voltage for acceptable steady‐state performance is determined as the control input. In addition, the smoothness in the proposed concept can be updated automatically depending on the drive situation, that is, transient, or steady‐state operation, thus avoiding degradation of dynamic performance. Simulation and experimental results obtained with a permanent magnet synchronous motor drive system demonstrate that the proposed control strategy is effective to achieve current control with fast tracking performance while suppressing current ripple.

FSTSMC Compliance Control for Dual-Arm Space Robot With SDBD Capture Satellite Operation

Abstract A space robot inevitably impacts a satellite in a capture operation. If its fragile joints are not protected, they may be damaged, resulting in failure of the capture operation. Thus, a spring damper buffer device (SDBD) is added between the joint motors and manipulators to absorb the impact energy, and provide a compliance strategy matched with the SDBD for stable control of the hybrid system. The dynamic modes of the dual-arm space robot open-loop system and target satellite system are established by the Lagrange function before capture. From the momentum theorem, velocity constraints, closed-chain geometric constraints, and Newton's third law, the closed-chain dynamic model of the hybrid system after capture is obtained, and the impact effect and impact force are calculated. For stable control of the hybrid system while limiting joint? impact torque within the safe range, an adaptive fractional-order super-twisting sliding mode compliance control strategy matching the SDBD is proposed. It can effectively improve the fast convergence and trajectory tracking performance of the system whose velocity and acceleration cannot be measured. The stability of the hybrid system is demonstrated by the Lyapunov theorem, and the anti-impact performance of the SDBD and the effectiveness of the compliance strategy are demonstrated through numerical simulation.

Data-Driven Nonlinear Iterative Inversion Suspension Control

The commercial operation of the maglev train has strict requirements for the reliability and safety of the suspension control system. However, due to a large number of unmodeled dynamics of the suspension system, it is difficult to obtain the precise mathematical model of the suspension system. After the suspension system has been operated for a long time with high load, the system model will change due to the wear, aging and failure of components, as well as the settlement of the line and track. The control performance is degraded. Therefore, this paper proposes a data-driven nonlinear iterative inversion suspension control algorithm, which can achieve high-precision tracking performance recovery control after control performance degradation without depending on the suspension system model. The control performance of the suspension system is improved by learning the measured data of the historical suspension system, and the fast convergence of the tracking error and high-precision stable suspension control are realized in the presence of unmodeled dynamics and external noise interference. Based on the historical suspension data of the maglev train suspension control system, the inverse dynamics model of the suspension system is identified by iterative inversion learning based on data drive, and the suspension control framework based on iterative inversion is designed. Then, the nonlinear input update strategy is used to realize the rapid convergence of the learning process. Finally, the simulation experiment of the maglev train suspension system and the physical experiment of the maglev system experimental platform are combined. It is verified that the proposed levitation control algorithm can achieve high-precision fast tracking performance recovery control after the system control performance degrades under noise environment.

Design of Missile Guidance Law Using Takagi-Sugeno-Kang (TSK) Elliptic Type-2 Fuzzy Brain Imitated Neural Networks

The exploiting of missile guidance law is one of the most important issue of defense systems. However, it is a complex nonlinear guidance control problem. In recent years, several intelligent algorithms have been employed for the missile guidance law design. This paper aims to provide a more effective intelligent neural network, and then apply it to missile guidance control. An elliptic type-2 function (ET2F) combined with a Takagi-Sugeno-Kang (TSK) fuzzy system (FS) based on a wavelet function and a brain imitated neural network (BINN) is proposed to produce a new Takagi-Sugeno-Kang elliptic type-2 fuzzy brain imitated neural network (TSKET2FBINN). The proposed TSKET2FBINN is then incorporated into the missile guidance law. The proposed missile guidance control system includes the TSKET2FBINN controller and a robust compensation controller. A Lyapunov function is used to generate parameter adjustment adaptive laws so as to guarantee system stability with fast tracking performance of missile guidance control system. By presenting three missile control scenarios, the effectiveness of the proposed method is then demonstrated. The miss-distance (MD) of the proposed method is calculated and compared to other recent guidance methods to demonstrate its superior performance.

Mirror-Descent Inverse Kinematics with Box-constrained Joint Space⋆

To control humanoid robots, the reference pose of end effector(s) is planned in task space, then mapped into the reference joints by IK. By viewing that problem as approximate quadratic programming (QP), recent QP solvers can be applied to solve it precisely, but iterative numerical IK solvers based on Jacobian are still in high demand due to their low computational cost. However, the conventional Jacobian-based IK usually clamps the obtained joints during iteration according to the constraints in practice, causing numerical instability due to non-smoothed objective function. To alleviate the clamping problem, this study explicitly considers the joint constraints, especially the box constraints in this paper, inside the new IK solver. Specifically, instead of clamping, a mirror descent (MD) method with box-constrained real joint space and no-constrained mirror space is integrated with the Jacobian-based IK, so-called MD-IK. In addition, to escape local optima nearly on the boundaries of constraints, a heuristic technique, called ϵ-clamping, is implemented as margin in software level. Finally, to increase convergence speed, the acceleration method for MD is integrated assuming continuity of solutions at each time. As a result, the accelerated MD-IK achieved more stable and enough fast tracking performance compared to the conventional IK solvers. The low computational cost of the proposed method mitigated the time delay until the solution is obtained in real-time humanoid gait control, achieving a more stable gait.

Adaptive Control Strategy for Three-Phase Three-Level T-Type Rectifier Based on Online Disturbance Estimation and Compensation

This paper proposes an adaptive control technique (ACT) for a three-phase, three-level, T-type rectifier based on online disturbance estimation and compensation. The proposed solution also regulates the DC-link voltage and grid currents under uncertainties, disturbances, measurement noises, and unbalanced grid voltages without cascaded control. The proposed controller consists of two layers; the first one is responsible for estimating nonlinearities and model uncertainties based on Kalman Filter Algorithm (KFA). The second layer is responsible for controlling both grid currents and DC link voltage using Linear Quadratic Regulator (LQR). The proposed controller is analyzed theoretically, validated experimentally, and the performance of the proposed controller is compared with two other controllers. The simulation and experimental results prove the superiority of the proposed controller and show that the proposed controller can ensure fast-tracking performance with almost zero steady-state error. The proposed controller has the ability to overcome severe disturbances such as AC and DC side disturbances, measurement noises, and mathematical model’s uncertainties even up to 400%.

Adaptive SMC based cascaded control of the grid-forming inverter

ABSTRACT The grid-forming inverter (GFI) plays an indispensable role in the microgrid (MG). Thus, it is critical for a microgrid to control the GFI flexibly and accurately, because of its voltage-forming and frequency regulation capabilities. The conventional proportional integral (PI) control strategy is usually used to control the GFI. However, the conventional PI control strategy has a high output voltage total harmonic distortion (THD) and deteriorative performance under external disturbances, which results in several problems in system flexibility, reliability and stability. This paper proposed a novel adaptive sliding mode control (ASMC) based cascaded control of the GFI system, which involves an ASMC-based inner current loop and outer voltage loop, and shows some superior performances of low THD, fast dynamic tracking performance and good robustness. Both the MATLAB/SIMULINK-based simulation and StarSim Modelling Tech-based semi-physical experimental results were presented to validate a perspective: the control strategy proposed by this paper has a better performance than the conventional PI control strategy under transient and steady-state condition.

Communication-Efficient Event-Triggered Time-Delay Control and Its Application to Robot Manipulators

This article proposes a communication-efficient event-triggered time-delay control (ET-TDC) scheme, which is more intelligent, consumes fewer network resources, and is more suitable for practical applications, such as network control systems over bandwidth-limited communication channels. The proposed controller ensures a fast convergence rate and high tracking performance because it is based on TDCs that are well known for achieving high tracking performance. To maintain these properties, the proposed control scheme adopts a performance-preserving ET strategy, whereby the communication effort between the controllers and actuators can be significantly reduced. The ET condition of the proposed controller is devised to ensure system stability by using a Lyapunov function. Finally, the performance of the proposed ET-TDC is demonstrated through a numerical simulation and an experiment using a two-link robot manipulator.

Linear parameter-varying gain-scheduled preview-based robust attitude control design for a staring-mode satellite

It is challenging to precisely control the attitude of a satellite when performing a fast and large-angle maneuver, for instance, in the staring mode. To solve this issue, this paper investigates a gain-scheduled preview-based robust attitude control method in the framework of linear parameter-varying control theory. Firstly, the linear parameter-varying model of an observation satellite with large-angle rotations is developed by choosing the attitude angles as scheduling parameters to take the dynamics variation into consideration. In order to ease the implementation in practical engineering applications, the structure of the linear parameter-varying controller is in the form of modified proportional-integral-derivative control. To simultaneously satisfy the requirements of fast rotational speed and high dynamic tracking performance, a gain-scheduled proportional-integral-derivative controller is designed with the future information of desired attitude signals included in the feedforward path. The proposed controller is synthesized within the framework of H∞ robust control to enhance the robustness against inaccurate previewed information and external disturbances. The corresponding control synthesis condition is derived as an optimization problem with linear matrix inequality constraints. Monte Carlo simulation results demonstrate that the dynamic tracking accuracy of the proposed control algorithm can be guaranteed to be less than 0.01 deg in the face of fast large-angle commands, inaccurate previewed information and external disturbances.

Design and control of an x-y-θz parallel piezoelectric nanopositioning stage with a large moving platform

This paper introduces the design and control of a new type of x- y-θ z parallel piezoelectric nanopositioning stage. Using the spatial cross-distributed double parallel four-bar linkage (DPFL), the mirror symmetrically distributed driving unit and auxiliary unit are designed. Then, a parallel piezoelectric nanopositioning stage with a large moving platform and good guidance and decoupling performance are designed. The workspace and frequency response characteristics of the stage are analyzed based on the stiffness and dynamic models. To improve the static and dynamic characteristics of the stage, the structural size is optimized, and the optimization results are verified by Finite Element Analysis (FEA). To reduce the response time, hysteresis nonlinearity, and external disturbance of the stage, a compound controller combining a rate-dependent Prandtl–Ishlinskii (PI) hysteresis compensator and a proportional-integral controller is designed. Finally, the prototype of the stage is made by Wire Electro-Discharge Machining (WEDM) technology. The open-loop performance of the stage is tested experimentally. The results show that the maximum relative coupling error between x and y directions is less than 0.5%. Also, the experimental control results show that the designed compound controller has a fast response speed, good positioning, and tracking performance.

Nonsingular Fast Terminal Sliding Mode Control for Permanent Magnet Linear Synchronous Motor via High-Order Super-Twisting Observer

In this article, a nonsingular fast terminal sliding mode (NFTSM) control strategy is proposed based on the high-order super-twisting observer (HOSTO) to acquire a fast and precise tracking performance for position regulation of permanent magnet linear synchronous motor. First, the NFTSM control is introduced to achieve fast convergence of the position tracking error. However, the lumped disturbances result in incompleteness of the system state information, and the robustness of the system is guaranteed through a large switching gain for the NFTSM, which causes system chattering. Therefore, the HOSTO is utilized to estimate the state information. Then, the NFTSM controller is designed based on the estimated state variables. The system’s stability under the proposed control is demonstrated using Lyapunov stability theory. Finally, real-time experiments are carried out to illustrate the efficiency and superiority of the proposed control strategy.

An Adaptive Nonsingular Fast Terminal Sliding Mode Controller for Dynamic Walking of a 5-Link Planar Biped Robot in Both Single and Double Support Phases

This paper aims to design an improved adaptive nonsingular fast terminal sliding mode controller for a fully actuated planar biped robot with five degrees of freedom in the single support (SSP) and double support (DSP) phases in the presence of external perturbation and uncertainties. A new sliding surface was proposed to avoid singularities and the chattering phenomenon. The proposed controller guarantees fast convergence of error signals in finite time. Unlike similar studies, the presented method considers a whole cycle of one step of walking, including SSP, double impact, and DSP phases. Also, the proposed approach does not require a predefined upper limit to estimate uncertainty using an adaptive law. Notably, dynamic walking was preferred over static walking to achieve more similarity to human walking. The designed trajectories were determined according to the position of the waist and swinging legs ankle, which could then be converted into the position of joints using inverse kinematics equations. The simulation results were used to approve the proposed controller's fast and robust tracking performance in the presence of external disturbances, mass, and inertia uncertainties without predefined knowledge of their upper bounds.

Adaptive finite-time disturbance observer-based recursive fractional-order sliding mode control of redundantly actuated cable driving parallel robots under disturbances and input saturation

This paper proposed a novel finite-time disturbance observer-based recursive fractional-order sliding mode control (FTRFOSMC) algorithm under disturbances and input saturation for redundantly actuated cable driving parallel robots (RCDPRs). A recursive fractional-order sliding mode surface composed of the fractional-order non-singular fast terminal sliding mode function and an integral term is constructed, and the fast response convergence and high precision tracking performance can be obtained for the recursive characteristics of the proposed sliding mode surface; meanwhile, an auxiliary system is designed to overcome the adverse effects of the input saturation. Then, to compensate the model uncertainty and external disturbances, an adaptive finite-time disturbance observer is developed, and the estimation error can be stabilized in finite-time for unknown bound of the disturbance and its derivative. The stability of the proposed controller was investigated by the Lyapunov stability theory. Finally, numerical simulations with the software of the MATLAB/Simuink are conducted to verify the effectiveness of the proposed controller.

Feedback Linearization Control Design for Battery/SMES Hybrid Energy Storage Systems Used in Distribution Network

A battery/superconducting magnetic energy storage (SMES) hybrid energy storage system (BSM-HESS) is designed for a power system. Meanwhile, a nonlinear feedback control (FLC) is adopted to achieve smooth and fast-tracking performance, and a rule-based strategy (RBS) is applied for power demand allocation. FLC can effectively compensate for the system’s nonlinearity to obtain the global consistent control performance; thus, it can properly solve the nonlinearity and modeling uncertainty of BSM-HESS. The effectiveness and advantages of FLC are evaluated via three cases, namely, heavy load condition, light load condition, and robustness with uncertain BSM-HESS parameters. Simulation results show that compared with proportional–integral–derivative (PID) control, FLC can achieve the best dynamic performance under various working conditions, which is beneficial for the system to quickly restore stable operation after large disturbance. In addition, the control cost of FLC is lower than that of PID control under both heavy load and light load conditions.

3Φ4W Grid-Connected Hybrid-Frequency Parallel Inverter System With Ripple Compensation to Achieve Fast Response and Low Current Distortion

Based on the comparisons of several inverter configurations in the aspects of efficiency, response, volume, current distortion, and price, in this article, we present a feasible three-phase four-wire (3Φ4W) grid-connected hybrid-frequency parallel inverter system (HbFPIS) with ripple compensation to achieve low current distortion and fast response. An HbFPIS consists of a low-frequency-high-power inverter (LFHPI) and a high-frequency-low-power inverter (HFLPI) connected in parallel. An LFHPI design results in higher power output with lower frequency (LF) switching devices, such as insulated gate bipolar transistors (IGBTs) being more cost-effective. An HFLPI design can reduce switching loss by lowering the power requirement of high-frequency (HF) switching devices while increasing dynamic response. With the direct digital control and ripple compensation, LF current ripples are attenuated by the HFLPI to a smaller level, remaining mainly HF current ripples and, thus, resulting in smaller filter size and weight. The design of an HbFPIS ensures that the system has high power output with cost-effective devices, fast response, and smaller output filters. Ripple attenuation, current tracking capability, and inverter stability are analyzed in the article. Low current distortion and fast current tracking performance are validated by the 300-kW simulated and the 10-kW experimental results of a 3Φ4W HbFPIS in grid-connected and active power filter modes.

A compound control strategy of three‐phase Vienna rectifier under unbalanced grid voltage

When traditional finite-set predictive power control is applied to Vienna rectifier, the input current will produce a large number of third harmonics under unbalanced power network, which will seriously affect the normal operation of Vienna rectifier. This paper proposes a compound control strategy for three-phase Vienna rectifier based on grid imbalance. And the new finite control set-model predictive direct power control (N-FCS-MPDPC) is used in the inner current loop. By introducing a redefined reactive power, this method can effectively control the second harmonic of instantaneous active power and the second harmonic of instantaneous reactive power at the same time, and realizes the normal operation of Vienna rectifier under the condition of unbalanced power grid. Linear auto disturbance rejection control (LADRC) is adopted in the outer voltage loop, which overcomes the problem of voltage overshoot and slow dynamic response in PI control. Furthermore, in order to solve the difficulty of grid-side voltage acquisition when the grid is unbalanced, a virtual flux based no-grid voltage sensor is introduced to measure the grid voltage. Simulation, along with experimental results, is presented to show that the proposed control strategy has good robustness and fast tracking performance under the condition of power grid imbalance.

Composite Velocity-Tracking Control for Flexible Gimbal System With Multi-Frequency-Band Disturbances

In this paper, a composite velocity-tracking control scheme is presented for improving dynamics response and control accuracy of the flexible gimbal system in the control moment gyro (CMG). Specifically, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${H}_{\infty } $ </tex-math></inline-formula> optimal vibration controller (HOVC) is developed to weigh multi-performance of the gimbal system, such as stability, fast-tracking performance, and attenuation ability of multi-frequency-band disturbances. Meanwhile, a robust disturbance observer (RDO) designed on optimization technology is utilized to improve the nonlinear friction rejection ability of the gimbal system. Moreover, rigorous theoretical analysis based on the small-gain theory is provided to demonstrate the stability of the closed-loop gimbal system under multiple disturbances. Finally, experimental studies are presented to verify the effectiveness of the proposed method.