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Public–private partnership (PPP) projects often end in early termination and the governments must compensate private-sector partners and take over project assets. Based on multicountry experience, this article proposes a systematic approach on when and how to compensate efficiently and fairly. A compensation model was first developed to quantify the amount paid to the private-sector partners when early termination occurs, and built upon that, an incentive model was proposed to analyze the incentives of both contracting parties. We then testified our propositions through two realistic cases. In line with the incomplete contract theory and the reference point theory, the findings demonstrate that the proposed compensation method increases the the private sector's incentives of relationship-specific investments, but discourages its efforts to prevent early termination in serious risk scenarios. This article not only contributes to the theoretical development of PPPs on contract design and incentive mechanisms, but also offers solutions for practitioners in the early termination of PPP projects.

This article addresses the distributed model-free adaptive control (DMFAC) problem for learning nonlinear multiagent systems (MASs) subjected to denial-of-service (DoS) attacks. An improved dynamic linearization method is proposed to obtain an equivalent linear data model for learning systems. To alleviate the influence of DoS attacks, an attack compensation mechanism is developed. Based on the equivalent linear data model and the attack compensation mechanism, a novel learning-based DMFAC algorithm is developed to resist DoS attacks, which provides a unified framework to solve the leaderless consensus control, the leader-following consensus control, and the containment control problems. Finally, simulation examples are shown to illustrate the effectiveness of the developed DMFAC algorithm.

In this article, we focus on the problems of consensus control for nonlinear uncertain multiagent systems (MASs) with both unknown state delays and unknown external disturbances. First, a nonlinear function approximator is proposed for the system uncertainties deriving from unknown nonlinearity for each agent according to adaptive radial basis function neural networks (RBFNNs). By taking advantage of the Lyapunov-Krasovskii functionals (LKFs) approach, we develop a compensation control strategy to eliminate the effects of state delays. Considering the combination of adaptive RBFNNs, LKFs, and backstepping techniques, an adaptive output-feedback approach is raised to construct consensus tracking control protocols and adaptive laws. Then, the proposed consensus tracking scheme can steer the nonlinear MAS synchronizing to the predefined reference signal on account of the Lyapunov stability theory and inequality properties. Finally, simulation results are carried out to verify the validity of the presented theoretical approach.

The objective of this study was to describe and classify common variations and compensation mechanisms in the sagittal alignment of the spine with lumbar degenerative disease.A total of 230 patients over 18 years old who underwent whole-spine X-rays to evaluate lower back pain were enrolled in this study. C7 slope, pelvic tilt (PT), sacral slope (SS), pelvic incidence (PI), thoracic kyphosis (TK), lumbar lordosis (LL), cervical lordosis (CL), thoracolumbar kyphosis (TLK), and sagittal vertical axis (SVA) were measured. Patients were divided into Group A (balance without compensation), B (balance with compensation), C (unbalance with compensation), and D (unbalance without compensation) according to spinopelvic balance and thoracic compensation.Group A had the largest LL, smallest PT, largest SS, and best clinical parameters of the four groups (p 0.001, p 0.001, p 0.001, p 0.001). The age increased gradually from Group B to Group D. Group B had an increased TK compared with Group A (p 0.001). Group C had an increased TK compared with Group A (p 0.001). Group D had an increased C7 slope compared with Group A (p = 0.022).This classification is shown four different regional and global alignments of the spine. Compensation took place to keep the balance of the spine. Classification types were consistent with age, compensation abilities, and clinical parameters. This classification potentially represents a valuable tool for comprehensive analysis of lumbar degenerative before surgical treatment considering sagittal balance.

This paper presents, a three-phase grid interfaced charging station (CS) for electrical vehicle (EV). It interacts with the grid to compensate for the reactive power. The charging station operates in various modes (i) charging/discharging of EV battery, (ii) compensation of reactive power (iii) both concurrent charging and compensation of harmonics current and (iv) concurrent discharging and compensation of harmonics current. The CS while in grid connected mode, operates under distorted and unbalance grid conditions. The control of the charging station is designed such that the reference grid currents synchronize with the phase voltages at PCC (Point of Common Coupling). If the grid losses synchronism then the charging station works in islanded mode and PV source charges the EV battery. The performance of the charging station is tested under various dynamic conditions and the grid currents distortion levels are in the limits as recommended by the standard IEEE-519.

In this paper, Sliding Mode Controller-based Distribution Static Compensator (DSTATCOM) is proposed for enhancement of power quality in the distribution network. The DSTATCOM plays a vital role to enhance the quality of power in the distribution network with linear and nonlinear loads under non-stiff sources. During the load disturbance in the systems, there is a sudden variation of voltage in DC link capacitor voltage connected with compensating device. The performance of DSTATCOM purely depends on the capacitor voltage level during load variation. It should be maintained within the prescribed limits. In general, the conventional controller is used in the converter to control dc-link capacitor voltage. Through, the conventional controller like PI transient response is still slow. Due to this reason, the harmonic elimination, load balancing, and reactive power compensation process are not satisfactory during different load variations in the distribution systems. To overcome these problems sliding mode controller is proposed in the control circuit for the proper operation of the compensator. The sliding mode controller regulates the DC link capacitor voltage to generate required reference currents. The reference currents play a vital role for switching pulse generation and control of DSTATCOM during various load disturbances. Sliding mode controller is designed to limit variation of DC-link voltage within limits. The proposed technique is modelled and its performance is simulated in MATLAB/SIMULINK platform and results are shown to validate the design and control of DSTATCOM under various load disturbance.

An innovative control method for 1-phase DSTATCOM incorporating communication network is discussed in this paper to obtain the coordinated control between the Distributed Generators and Compensators. The methodology is intended for micro grid supplying loads with feeders traversed physically distant apart from each other. The anticipated reactive compensation is constructed on confined measurement and the transmitted power through the cables. It ensures that the discussed approach minimizes the voltage level more efficiently while sustaining the voltage control even after a high-level dissemination of the DGs. The MATLAB simulations carried over thearbitary network confirm the DSTATCOM outstanding performances with different operating situations like utility side, mid of the feeder and end of the feeder. The impact of communication node breakdown is analyzed at various nodes and the significance of communication in loop control is validated through an arbitrary 5-bus system.

In this article, the finite-time consensus problem is investigated for a group of heterogeneous nonlinear multiagent systems with input delays. Different from the existing results, input delays are assumed to be nonidentical and time-varying. To overcome the difficulty of nonidentical input delays, a novel compensation mechanism is introduced. Moreover, in order to save communication resources, a distributed finite-time self-triggered observer is constructed. By employing the observer and the dynamic surface control strategy, the finite-time adaptive neural control protocol is proposed. It is proved that not only the followers’ outputs can be synchronized with the leader in finite time, but also continuous communication among followers is avoided. Finally, two simulation examples are provided to illustrate the validity of the proposed control strategy.

Pulse width modulation (PWM) based power electronics inverters are being widely used for various applications, including motor drives. However, the common-mode voltage (CMV) resulting from switching operations in the PWM inverters causes significant performance degradation of the system and can cause potential damage to motors. Since the effects of the CMV can be more severe in wide bandgap (WBG) and high switching frequency-based converter systems, various methods have been proposed to mitigate the CM noise issues. This work presents a multi-level inverter system composed of a multi-level inverter with a proposed multi-level active power filter (APF). For attenuating the CMV in multi-level inverters using multi carrier-based PWM methods, a novel PWM method is presented for the proposed multi-level APF. The three-phase five-level Active-Neutral-Point-Clamped (ANPC) II-type inverter using the Apparent Switching Frequency Doubling (ASFD) PWM is used as an example of the multi-level inverters and carrier-based PWM methods to analyze and verify the proposed CMV attenuation method. The APF generates and injects the APF voltage equal to the CMV to attenuate the CM noise accurately. Various key challenges, including the dead-time compensation, are addressed through the proposed advanced PWM techniques to improve the CMV attenuation performance. Simulation and experimental results are provided to verify the comparison and effectiveness of the proposed CMV attenuation method.

In this article, an adaptive sensor fault accommodation scheme is proposed for uncertain vehicle active suspensions via output-feedback control where vehicle body displacement is the only measurable output signal corrupted by sensor bias. An adaptive observer with variable gains is constructed to obtain state estimates whose design procedure involves parameter adaption of the uncertain system parameters and sensor bias, and an output-feedback controller is designed to attenuate the vehicle body displacement based on the partial measurement information, estimates of the states, and unknown parameters. Compensation for measurement error is made both in the design process of the adaptive observer and output-feedback controller in order to weaken the influence brought about by sensor bias fault. In order to guarantee system stability, the variable observer gains are determined in real time using a switching strategy where their values can be modified in finite times by monitoring the state estimates generated by the observer itself. It is proved that the vehicle body displacement will converge to a small neighborhood around zero, and all the signals of the closed-loop system are ensured to be bounded through selecting suitable control parameters. Simulation is carried out to show the effectiveness of the proposed method and results indicate that better stabilization of the suspension vertical motion can be achieved through adaptive compensation for sensor bias.

Navigation control of microrobots in vivo has great potential in precision medicine and has attracted considerable attention in recent years. The control performance of the existing methods is considerably affected by hysteresis nonlinearity. This article presents a robust control method that can overcome hysteresis influence in navigating a microrobot actuated by an electromagnetic coil system. A motion planner that combines the breadth-first search (BFS) method and genetic algorithm (GA) is used to plan a reliable and flexible trajectory for the microrobot navigation. To compensate for hysteresis nonlinearity existing in the system, the Prandtl-Ishlinskii (PI) model is introduced. A robust controller that integrates adaptive sliding mode control (ASMC) and nonlinear disturbance observer is designed to guarantee the stability and accuracy of the microrobot in motion. Experiments have been performed to demonstrate the effectiveness of the proposed approach. The success of this research will advance the microrobot navigation for in vivo applications.

Dc-link oscillation in electromechanical equipment drive system with film capacitor is a common problem when system impedance mismatch. For this problem, an inverter voltage compensation (IVC) strategy is proposed in this article to suppresses the oscillation of dc-link voltage. This method improves the motor input impedance by designing a damping compensation link so that the input and output impedances of the system can meet the stability conditions. It injects the damping signal into the inverter reference voltage of PWM modulation, which avoids the influence of current loop bandwidth and does not directly affect the motor speed or motor current. Moreover, the compensation impedance of this method is related to the motor voltage, which can compensate system damping dynamically according to the motor operating conditions, and the effect of the compensation link on the motor dynamic performance is reduced. Furthermore, the selection of compensation coefficients in this method is more intuitive and it simplifies the system design. Finally, experimental results demonstrate the effectiveness of the proposed method after building an experimental platform.

Robot force-controlled task executions require an accurate perception of the contact force/torque. When a six-axis force/torque (F/T) sensor is attached to the robot wrist, the compensation precision is affected by many non-contact features, such as the end-effector gravity, inertial, centrifugal, Coriolis forces, and the mechanical errors of the sensor. However, it is complicated to identify all parameters at the same time. Some features will be ignored in practice applications, e.g., surface finishing, human-robot interaction, and haptic applications. In this paper, a novel end-effector gravity compensation method for the F/T sensor is proposed, which identifies the end-effector gravity, its center, and the biases (the rotation between the sensor and robot, the robot installation declination, the bias of sensor). Our key is the rotation calibration while the transformation between the F/T sensor and robot is unknown. Simulation and experimental results show that the proposed method works effectively. In a wrist-mounted F/T sensor system, compared to the previous limited method, the compensation error in common force control channel Fz by our method diminishes 1.0% of the end-effector gravity (i.e., 21.7% relative improvement).

This article is concerned with the secure state estimation problem for cyber-physical systems under intermittent denial-of-service (DoS) attacks. Based on a switching scheme and the cascade observer technique, a novel resilient state observer with a switched compensation mechanism is designed. Moreover, a quantitative relationship between the resilience against DoS attacks and the design parameters is revealed. Compared with the existing results, where only the boundedness of the estimation error is guaranteed under DoS attacks, the exponential convergence of the estimation error is achieved by employing the proposed observer scheme, such that the estimation performance is improved. More specifically, in the disturbance-free case, it is proven that the state estimation error converges exponentially to 0 despite the existence of DoS attacks. Finally, simulation results are provided to illustrate the effectiveness and merits of the proposed methods.

The hysteresis of the piezoelectric actuator (PEA) exhibits obvious rate dependence, especially in fast scanning or tracking. This paper proposes an adaptive hysteresis compensation method that integrates the direct inverse modeling (DIM) method and an adaptive Kalman filter (AKF). DIM is adopted to directly obtain the inverse hysteresis model and use it as the hysteresis compensator. AKF is utilized to dynamically update the weights of the inverse hysteresis model so as to eliminate the manual tuning of control parameters. Further, a forgetting factor is adopted in AKF to reduce the influence of the old data. Experimental results on tracking of step, sinusoidal and triangular trajectories demonstrate the effectiveness of DIM+AKF in hysteresis compensation. The transient and steady state performances of the closed-loop system are significantly improved. A closed-loop bandwidth higher than 200 Hz is achieved. The robustness of DIM+AKF against the rate dependence is further verified using a 0-200 Hz swept sinusoidal trajectory. As the on-site tuning is successfully eliminated, DIM+AKF is easy to follow for experienced users.

In the presence of system coupling and dynamic uncertainties, extensive research has been conducted on the precise motion control of industrial manipulators with general reference trajectories. Since repetitive operations are common tasks in industrial applications, it is an essential and practical problem to further improve the control accuracy by taking advantage of the periodicity of the reference trajectory. In this paper, a desired compensation adaptive robust repetitive control is proposed for multi-DoFs industrial manipulators to perform repetitive tasks. Specifically, the link dynamics identified offline is compensated directly to decouple the system and capture the main characteristics of the link effect. Then, the uncertain friction is dealt with through an online adaptation scheme, in which the desired compensation is utilized to avoid measurement noise and chattering at low speed. And periodic disturbances are approximated by Fourier series expansion with unknown Fourier coefficients, which will be learned online. Finally, the robust feedback is designed to guarantee transient control accuracy and robustness against dynamic uncertainties. Comparative experiments on an industrial manipulator show that the proposed controller possesses better transient and steady-state control accuracy and error convergence rate.

Since the observed angle of a phase-locked loop (PLL) is relatively accurate even under distorted grid conditions, the mathematical model of the voltage errors caused by the switching modulation and the dead-time effect are derived as a function of the grid voltage angle in this paper. Based on the model analysis, an adaptive compensation algorithm is proposed to suppress the grid-side current harmonics in three-phase converters. The proposed algorithm fits the unmeasurable voltage errors by a truncated Fourier series expansion, and then takes it as an equivalent disturbance in the current control loop to achieve harmonic compensation. By the feed-forward compensation, the design and tuning of the controller parameters are simplified and separated from the dynamic performance. In addition, the controller can adapt to the grid frequency variation by updating the grid voltage angle with the PLL block. To reduce the computational burden, a simplified version of the proposed method is also presented. Simulation and experiment results show that the proposed methods can suppress the current harmonics and achieve better performance in terms of total harmonic distortion, strong robustness and insensitivity to the grid frequency variations, compared with the traditional PI control or repetitive control strategy.

The nonlinearity of the voltage source inverter (VSI) leads to the error between output voltage and reference voltage, and causes the phase current harmonics. It is necessary to compensate its influence in the fields such as parameter identification, sensorless control and servo drives. In this paper, an industrial solution for VSI nonlinear compensation method based on lookup table (LUT) is introduced. The characteristics of semiconductor devices, equivalent dead-time and influence of parasitic capacitance effects are calculated quantitatively though injecting increase and decrease current during self-commissioning process. The critical current value for parasitic capacitor and the variation of equivalent dead time are verified through different distorted voltage curves. Considering dc-link voltage variation is irresistible for industrial products, three-dimensional linear interpolation is adopted to compensate the variation of VSI nonlinearity under different voltage conditions. Proposed LUT method does not require VSI datasheet and complicated calculation formula during implementation. Experiments are carried out though a commercial permanent magnet synchronous motor drive system to verify the proposed LUT method.

This article presents a programmable multiple frequencies clock generator with a process and temperature compensation circuit design. The proposed clock generator can achieve a stable and wide frequency range output for a single input frequency by using digital control codes as well as process and temperature compensation mechanisms. In our approach, the first step is to adjust the duty-cycle of the input clock by using a digitally controlled pulsewidth modulator (DCPWM) to generate an output clock signal with a duty-cycle of 20% to 80%. Second, the various duty-cycle clock outputs of the DCPWM are integrated by the duty-cycle-to-voltage converter to generate analog voltage signals to control the succeeding voltage-controlled ring oscillator (VCO). Through the use of various control voltages, different VCO output frequencies are generated. Finally, by using the process and temperature compensation circuit, the proposed clock generator can provide a stable and wide frequency range. The proposed chip is fabricated in a 180-nm CMOS process and has an output frequency range of 35–138 MHz at a supply voltage of 0.9 V. At 120 MHz, the power dissipation and rms jitter are 224.3 μW and 7.84 ps, respectively. The active area of the chip is 0.62 mm × 0.76 mm.

This paper presents a novel hierarchical cooperative control strategy to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable bus voltage for battery storage system (BSS) in islanded DC microgrid. In the communication layer, a neighbor-to-neighbor communication network architecture is constructed in which each battery storage unit (BSU) only communicates information with neighboring nodes, and a multi-agent consensus algorithm is used to iteratively estimate the relevant average global variables. In the main control layer, the droop coefficient is dynamically adjusted by constructing a fast SoC convergence function to ensure that the load current is reasonably distributed based on the rated capacity of each BSU. In the secondary control layer, a virtual voltage drop equalization controller and an average bus voltage compensation controller are designed to eliminate the impact of line impedance mismatch and compensate the average bus voltage. Furthermore, an optimized factor is designed to accelerate the later stage of SoC convergence. Finally, a DC microgrid experimental platform based on StarSim HIL is built, and the results demonstrate that the proposed strategy can achieve the control objectives of fast SoC balance, proportional load current sharing, and bus voltage stability.

Affine nonlinear systems are special kinds of non-linear systems, and they can represent many practical systems. Dealing with affine nonlinear system based on T-S fuzzy model has drawn much attention in literature recently. In this paper, a robust control method is proposed for affine nonlinear system with disturbance based on T-S fuzzy model. First, an optimization T-S fuzzy model is constructed focusing on optimizing the parameters of the weight functions by using differential evolution algorithm (DEA). Second, in order to reconstruct the disturbance, an interval observer is designed for the affine nonlinear system, and then a novelty disturbance reconstruction method based on the interval observer is developed. The disturbance reconstruction value can asymptotically approach the actual disturbance value, and furthermore, it decouples the control input. Third, by taking the optimization T-S fuzzy model as design model and by introducing the reconstruction of disturbance into controller, a feedback robust controller with disturbance compensation is designed to stabilize the affine nonlinear system. Finally, a simulation example of the crane model is given and some comparisons are provided to verify the effectiveness and show the advantages of the proposed method.

This paper presents an elliptical target encircling control policy of quadrotors subject to uncertainties and aperiodic signals updating based on pure bearing measurements. At the translational level, by resorting to bearing-only data, rather than prior position and velocity information of target, a position estimator is constructed for locating the unknown target. Utilizing the localization result from position estimator, compared to the existing circular surrounding alternatives, a planar elliptical guidance law capable of adapting more sophisticated operational environment, and a longitudinal control law are synchronously established to generate the velocity reference. At the rotational level, an unknown system dynamics estimator (USDE) is introduced to online neutralize total adverse effect induced by exogenous disturbances and internal uncertainties, where high precision estimation and low computational complexity can be guaranteed with only one tuning argument, then an event-triggered robust attitude controller carrying a sampling deviation compensation item is synthesized accomplishing elliptical encircling for a dynamic target without involving Zeno behavior. Finally, stability of closed-loop system is analyzed via input-to-state stable principle, while simulations are given to verify the efficacy of suggested approach.

This paper proposes a primary-side linear control strategy to realize the constant current (CC)/voltage (CV) charging for the wireless power transfer (WPT) system, based on the LCC-N circuit. Different from the conventional compensation topology used in control strategies, this paper combines magnetic integration structure on the primary side and non-compensation topology on the secondary side. Firstly, the LCC-N magnetic integration and non-compensation topology is introduced. An improved parameters identification method considering the non-pure resistive input impedance characteristics of the rectifier is proposed to identify the current, voltage and equivalent resistance of the load, based on the LCC-N topology. In the process of identification, the relationship between the input impedance of the rectifier and the load is needless. Then, according to the LCC-N output characteristics and identified load parameters, the relationship between the input voltage and load current and voltage is simplified to linear through the linear superposition of fundamental wave and third harmonic. A linear control strategy on the primary side is proposed to achieve CC/CV output. Finally, a 1 kW WPT prototype is built. The experimental results show that the maximum error of the output current and voltage are 1.8% and 1.2% during the CC and CV charging, respectively.

The insulation impedance monitoring methods such as capacitance/dissipation factor (C/DF) monitoring methods have been proposed for the online stator insulation condition monitoring. By measuring the insulation leakage currents and the phase-to-ground voltages, the groundwall and phase-to-phase insulation impedances can be calculated in frequency domain. In the existing methods, the calculation is based on the assumption that the differential mode phase-to-ground voltage decreases linearly along the stator winding and no phase angle deviation is considered. However, the phase angles of the induced electromagnetic forces in stator winding in different slots depend on the slot positions. The assumption in the existing methods neglects this phase deviation and causes errors in the monitoring results. In order to eliminate this effect, the effect of the phase angle deviation on monitoring results is analyzed in this paper. Its dependency on the turn number, the winding configuration and the frequency of the selected monitoring signals is studied. A compensation method is proposed and the compensation coefficients are calculated for different winding cases for the demonstration purpose. The online experimental results prove that the accuracy of the online monitoring results is improved after the compensation.

The simulation of the target capture process of space manipulator is of great significance for the manipulator and task verification. By integrating the physical and numerical simulation, the hardware-in-the-loop (HIL) simulation is very suitable to simulate the complicated contact dynamics of the target capture process of the multi-body manipulator in 3D space. However, the time delays in the system loop lead to HIL simulation error and even system instability. In this study, a distributed delay compensation approach is proposed for the hybrid simulation system of space manipulator capture. The force delay, calculation delay, actuation delay and mechanism delay in the system loop are compensated in situ. Compared with lumped compensation, distributed compensation has stronger robustness to the signal noise and better adaptability to the varying contact natural frequency. Simulations and experiments show that the proposed compensation approach can guarantee the system stability and satisfactory simulation accuracy.

In this study, we propose an adaptive fuzzy eventtriggered control scheme for an autonomous aerial refueling hose system involving uncertainty, an event-triggered mechanism, and actuator failures. The unknown nonlinear function is approximated using the designed fuzzy logic systems. Through introduction of the adaptive compensation scheme, the problem of an infinite number of actuator failures, including partial and complete failures, is solved. In addition, the event-triggered control strategy is designed to achieve vibration suppression while decreasing the communication burden between the controllers and actuators. The stability of the closed-loop system is demonstrated via the Lyapunov direct method. Finally, simulation examples are presented to confirm the validity of the proposed control scheme.

In this article, an online RNN-based finite-time formation tracking control (ORNN-FTFTC) is designed to quickly accomplish an assigned formation of nonlinear generalized and heterogeneous multiagent systems with input fault and saturation. Each agent, including the leader and the followers, can possess different relative degrees and control input numbers but the same output for easy task planning. At least one agent must communicate with the leader and the information of neighborhood agents is required to accomplish the assigned formation task. To fulfill the task under the uncertain environment, the proposed ORNN-FTFTC possesses nonlinear filtering formation error with dynamic fractional exponent, nonlinear filtering gain, and the RNN learning compensation of the aggregately uncertain dynamics in each agent. Not only does the nonlinear filtering gain increase as the nonlinear filtering formation error is in the vicinity of zero to achieve its finite-time convergence, but also the new e-modification learning can cover all the value of formation error such that learning weights are stabilized even in an uncertain environment. Finally, an application to a 3D pose from take-off to a steady-formation of hexa-copter unmanned aerial vehicles and unmanned helicopters with initial formation error certifies the feasibility and robustness of the proposed control.

Although rich collection of research results on event-triggered control exist, no effort has ever been made in integrating state/output triggering and controller triggering simultaneously with backstepping control design. The primary objective of this work is, by using intermittent output signal only, to build a backstepping adaptive event-triggered feedback control for a class of uncertain nonlinear systems. To do so we need to tackle three technical obstacles. Firstly, the nature of the event-triggering makes the transmitted output signal discontinuous. Secondly, the effects arisen from event-triggering action must be properly accommodated, but the current compensating method only works for systems in normal form. Thirdly, as only intermittent output signal is available and at the same time the impacts of certain terms containing unknown parameters (arising from event-triggering) need to be compensated, it is rather challenging to design a suitable state observer. To circumvent these difficulties, we employ the dynamic filtering technique to avoid the differentiation of virtual control signals in backstepping design, construct a new compensation scheme to deal with the effects o

The robust iterative learning control (RILC) can deal with the systems with unknown time-varying uncertainty to track a repeated reference signal. However, the existing robust designs consider all the possibilities of uncertainty, which makes the design conservative and causes the controlled process converging to the reference trajectory slowly. To eliminate this weakness, a data-driven method is proposed. The new design intends to employ more information from the past input-output data to compensate for the robust control law and then to improve performance. The proposed control law is proved to guarantee convergence and accelerate the convergence rate. Ultimately, the experiments on a robot manipulator have been conducted to verify the good convergence of the trajectory errors under the control of the proposed method.

In this article, an adaptive output feedback compensation scheme is proposed for a class of uncertain nonlinear systems with a set of redundant actuators and a sensor. The sensor output is the only information available for output feedback. Both the actuators and the sensor may suffer from failures during operation and, therefore, all the system states are not available. To estimate the unmeasured states, a modified high-gain observer is designed which can not only ensure the closed-loop system stability but also improve the tracking performance. In the adaptive controller design, to overcome the complexity due to the unknown actuator and sensor failures coupled with the nonlinear functions and unknown parameters, an upper bound estimation method is adopted, which greatly simplifies the design procedure. It is proved that with the proposed scheme, the actuator and sensor failures can be compensated simultaneously, the reconfiguration can be adaptively updated without fault detection and isolation, and the real-tracking error can converge to a residual set, that is, mainly proportional to the sensor gain variation and measurement error.

As one of the core components of high-end manufacturing equipment, linear motor (LM) plays an important role in high efficiency and high quality production of the equipment. In this paper, a high-precision robust control method with periodic dynamic compensation is proposed for the most common repetitive trajectory tracking task in the manufacturing industry. To overcome the influence of unknown periodic dynamics on the control accuracy, a B-spline wavelet neural network (BSWNN) observer is designed to estimate the uncertainties. Moreover, the control framework in the form of robust control is employed to ensure the stability of the closed-loop system under other unknown aperiodic disturbance. Finally, the high-precision control for LM-driven stage in high-speed environment is realized, and the comparative experiments show that the control accuracy of the proposed method is significantly improved at least 28.9% compared with the other three existing control methods.

The flotation industrial process is a strong nonlinear and coupling, multivariable cascade process with device and operational layers structrue. To address its operational control problem, this paper describes two layers nonlinear dynamic characteristics and disturbances as the previous sample unmodeled dynamics and its change rate and proposes a compensation signal based dual-rate operational feedback adaptive decoupling control approach. First, a device layer controller is designed consisting of a controller driven model, a PI controller, an unmodeled dynamics compensator (UDC) and an unmodeled dynamics change rate compensator (UDCRC). Then, the device layer closed-loop system and the operational layer system are unified in the same timescale and hence a controlled plant model is obatianed. A system identification algorithm is proposed to obtain the parameters of this model. With these parameters, an operational layer controller is designed consisting of a controller driven model, a PID controller, a feedback decoupling controller, UCD and UDCRC. Finally, convergence proofs of the proposed identification algorithm and the closed-loop system stability analysis are given, and emulation compared experiments in a hardware-in-the-loop system are used to verify the effectiveness of the proposed approach.

A 24 GHz self-calibrated all-digital frequency-modulated continuous-wave (FMCW) synthesizer is presented in this article. A multi-bank digitally controlled oscillator (DCO) is employed to provide adequate frequency tuning range and high frequency resolution. A full background self-calibration scheme is proposed to linearize the DCO tuning curve for highly linear and fast chirp generation. An overlap compensator based on an adaptive lookup table (LUT) is utilized to eliminate the frequency overlaps between adjacent DCO tuning bands. The compensation words in the LUT are altered by least-mean-square (LMS) algorithm for robust and precise matching. A ramp tracker, which features real-time ramp tracking with zero steady-state phase error, is employed to estimate and stabilize the frequency ramp. Implemented in 40 nm bulk CMOS, the FMCW synthesizer prototype consumes 28 mW with a 0.26 mm² core area. The maximum chirp bandwidth is 3.2 GHz, corresponding to 13.33% of the center frequency. Measurement results show that the root-mean-square (RMS) frequency error is reduced by 1/10 with self-calibration after 2 ms convergence time. The maximum chirp slope is up to 320 MHz/μs with 309 kHz RMS frequency error. The minimum RMS frequency error is 7.35 kHz under 5 MHz/μs chirp slope, corresponding to 0.0002% of the chirp bandwidth.

This paper deals with a cooperative control of multiple distributed generation (DG) systems with power quality (PQ) enhancing capabilities. This control algorithm is realized using an adaptive harmonic signals extraction method based on variable weight mixed norm least mean fourth (LMF)-least mean square (LMS) adaptive detection method. This adaptive technique extracts all the necessary information required for the development of the proposed cooperative control algorithm. With this control algorithm, the voltage source inverters (VSIs) of the DG systems contribute to PQ improvement by mitigating harmonics and reactive currents in the distribution system. This algorithm operates the VSIs in maximum power generation and total harmonic distortion (THD) improvement modes. In maximum power generation mode, the algorithm utilizes the remaining capacity of the VSIs for compensation of nonactive currents drawn by the dedicated loads. Upon finishing the dedicated loads' compensation, the remaining capacity is spent for compensation of the loads dedicated to other DG systems that are not in the position to render full compensation services. In THD improvement mode, the algorithm prioritizes compensation of harmonic currents generated by the loads. The efficacy of the proposed cooperative control algorithm for multiple DG systems is demonstrated via simulation and hardware-in-the-loop (HIL)-based experimental results.

This brief considers the security control problem for nonlinear cyber-physical systems (CPSs) against jamming attacks. First, a novel event-based model-free adaptive control (MFAC) framework is established. Second, a multistep predictive compensation algorithm (PCA) is developed to make compensation for the lost data caused by jamming attacks, even consecutive attacks. Then, an event-triggering mechanism with the dead-zone operator is introduced in the adaptive controller, which can effectively save communication resources and reduce the calculation burden of the controller without affecting the control performance of systems. Moreover, the boundedness of the tracking error is ensured in the mean-square sense, and only the input/output (I/O) data are used in the whole design process. Finally, simulation comparisons are provided to show the effectiveness of our method.

The mode transition process (MTP) from electric mode to hybrid electric mode (EM-to-HM) will cause the deterioration in occupant comfort of PHEV, to tickle this issue, a torsional oscillation-considered mode transition coordinated control strategy and a novel general evaluation index for MTP are developed in this research, the quality of mode transition and transient torsional oscillation of gears (TTOGs) during MTP are taken into consideration comprehensively. An action dependent heuristic dynamic programming algorithm which takes the vehicle jerk, friction loss and TTOGs as evaluation index is used to optimize the pressure curve of clutch oil and the compensation torque of motor in the entire EM-to-HM process. Finally, the simulation results and hardware-in-the-loop tests show that vehicle jerk and TTOGs are suppressed, and the driving comfort can be improved accordingly.

This paper proposes an adaptive sliding mode control (ASMC) with a modified reduced-order proportional integral observer (MROPIO) to provide speed control for a permanent magnet synchronous motor against unknown disturbances, such as system parameter uncertainties and external load torque variation. The ASMC method, based on a new sliding mode reaching law, improves chattering in the control signal and reduces the time required for the system trajectory to reach the sliding mode surface. The MROPIO estimates unknown disturbances and provides feedforward compensation for the ASMC, thus overcoming incorrect estimations of unknown disturbances during speed jumps can cause overshoots in the speed response. All the proposed methods were implemented on an industrial motor drive. The experimental results confirm the validity of the proposed method for practical applications.

Disturbance rejection and time-delay compensation are important for control systems in practice. This article presents an observer-and-predictor-based method to reject an unknown exogenous disturbance for an input-delay system in which only delayed output is available. First, the equivalent-input-disturbance method is employed to reconstruct the system state and to estimate the disturbance. A prediction of the disturbance is calculated to reduce the effect of a phase lag caused by the delays. A new predictive scheme is designed for feedback control. Next, the system is divided into two subsystems for analysis and design: one for reference tracking and the other for disturbance rejection. Sufficient conditions are derived to guarantee the system's stability. An analysis of the method reveals that the disturbance rejection can be viewed as a patch to the predictor-based feedback control. Finally, two case studies are used to show the validity and superiority of the method.

To assist different styles of drivers to maintain vehicle stability in the event of actuator function failures, this paper proposes a cooperative game-based robust fault-tolerant control (FTC) strategy for four-wheel independent actuated electric vehicles. The Takagi-Sugeno fuzzy structure is used to model a driver-vehicle system to describe driver characteristics in the FTC scheme and deal with the nonlinearity among states of the complex system. Viewing the FTC process as a dynamic cooperative game so that the actuators of the driver-vehicle system are described as the players. The interactions among players are modeled by the distributed model predictive control scheme. Finally, an adaptive compensation control mechanism is developed to make the cooperative game paradigm more robust. Simulation verification is used to reveal the influence and the inherent characteristics of task weights in the cooperative game. Besides, two severe failure cases are studied via the hardware-in-the-loop test to prove that the proposed method can maintain the stability of the failed vehicle driving by different drivers.

Capacitor-current active damping has been widely used in voltage source inverters with LC or LCL filters. However, the time delay poses an adverse impact on the damping performance, causing a negative-resistance behavior, and thus constraints the system stability. To address this issue, this letter proposes a compensation method, which eliminates the adverse impact by removing the time delay out of the capacitor-current loop. Consequently, the damping performance behaves as a constant positive resistance, and thereby the stable region of the damping gain is notably enlarged. Experimental results verify the effectiveness of the proposed method.

The analysis and design problems of formation-containment control for high-order linear time-invariant (LTI) multiagent systems (MASs) on directed graphs with observer-based output-feedback protocols are given in this work. To expand the feasibility of state formation configuration, two well-structured compensation signals are introduced for the leaders and followers in the protocols, respectively. Benefitting from the compensation signal of followers, the decoupling between formation control of leaders and containment control of followers is achieved. Thus, a necessary and sufficient condition is first established such that the formation-containment control for high-order LTI MASs can be achieved. Moreover, a heuristic iterative algorithm is developed to compute the controller gains, observer gains, as well as the compensation signals. Finally, two numerical examples are implemented to illustrate the time-varying formation-containment control of high-order MASs, which shows the validity and practicability of the theoretical results and algorithm.

In this paper, an online optimization control (OPC) scheme is proposed for the angle control of MEMS scanning micro-mirror actuated via electromagnetic method. In order to avoid complicated process of building precise model of the MEMS micro-mirror, a control structure not relying on precise model is developed. In this structure, a simplified linear dynamic model is used to describe the basic dynamic behavior of the micro-mirror. Then, a model error compensation mechanism (MECM) is introduced to compensate for the model uncertainty caused by un-modelled dynamics and nonlinear factors, such as hysteresis. Moreover, a predictive gradient descent (PGD) based optimization mechanism is proposed to compensate the effect of time-delay and speed up the convergence of on-line optimization process. Then, the stability analysis of the proposed control system is implemented. Finally, the proposed control scheme is applied to the angle control of electromagnetically driven scanning micro-mirror (EDSMM) and the corresponding experimental results are presented.

In the application of wireless power transfer system, parameter drift of resonant tank is a general situation which induces that natural frequency of primary side or secondary side deviates from switching frequency. This frequency deviating phenomenon will deteriorate load-independent constant current characteristic and decrease output power capacity for a S/S compensation system. This paper illustrates the problems caused by frequency deviating through output characteristic analysis and addresses them by a self-tuning method based on switched capacitors (SCs). The proposed self-tuning method requires no resonant parameters such as compensation capacitance and coil self-inductance in advance. Primary and secondary natural frequencies can be both tuned to switching frequency continuously by SCs. The proposed method is verified by a simulation and a 500W S/S compensation experimental prototype. After the completion of self-tuning process, load-independent constant current characteristic is recovered and the output power capacity is boosted which are in consistence with the theoretical analysis of system output characteristic. The proposed method is also applicable to LCC/S and LCC/LCC topologies.

This article considers the problem of finite-time (FT) tracking control for a class of uncertain multi-input-multioutput (MIMO) nonlinear systems with input backlash. A modified FT command filter is designed in each step of backstepping, which ensures the output of the filter can faster approximate the derivatives of virtual signals, suppress chattering, and relax the input signal limit of the Levant differentiator. Then, the corresponding improved FT error compensation mechanism is adopted to reduce the negative impact of filtering errors. Furthermore, a neural-network-adaptive technology is proposed for MIMO systems with input backlash via FT convergence. It is shown that desired tracking performance can be implemented in finite time. The simulation example is presented to illustrate the effectiveness and advantages of the new design method.