A new advanced third-order sliding mode control with adaptive gain adjustment using fuzzy logic technique for standalone photovoltaic systems

In this paper we consider convergence of iterative learning control (ILC) algorithms. We use a multiloop control interpretation of the signal flow in ILC to derive a necessary and sufficient condition for convergence of discrete-time, linear, time-invariant systems. We then use our multiloop approach to develop an iterative learning control algorithm that can converge in as few as four trials. The scheme uses an adaptive (in trial number) gain adjustment that does not have to be tuned. This is combined with the use of feedforward correction terms (in time) to produce the complete algorithm. A simulation illustrates the effectiveness of the strategy. The paper concludes with comments on how the multiloop approach can be used to address (i) higher-order ILC schemes for dealing with noise in the process and with initial state uncertainty (using a Kalman filter in trial number); (ii) ILC convergence for nonlinear and time-varying systems; and (iii) the adaptive gain adjustment rule.

The continuous development of spacecraft with large flexible structures has resulted in an increase in the mass and aspect ratio of launch vehicles, while the wide application of lightweight materials in the aerospace field has increased the flexible modes of launch vehicles. In order to solve the problem of deviation from the nominal control or even destabilization of the system caused by uncertainties such as unknown or unmodelled dynamics, frequency perturbation of the flexible mode, changes in its own parameters, and external environmental disturbances during the flight of such large-scale flexible launch vehicles with simultaneous structural deformation, rigid-elastic coupling and multimodal vibrations, an improved adaptive augmentation control method based on model reference adaption, and spectral damping is proposed in this paper, including a basic PD controller, a reference model, and an adaptive gain adjustment based on spectral damping. The baseline PD controller was used for flight attitude control in the nominal state. In the non-nominal state, the spectral dampers in the adaptive gain adjustment law extracted and processed the high-frequency signal from the tracking error and control-command error between the reference model and the actual system to generate the adaptive gain. The adjustment gain was multiplied by the baseline controller gain to increase/decrease the overall gain of the system to improve the system’s performance and robust stability, so that the system had the ability to return to the nominal state when it was affected by various uncertainties and deviated from the nominal state, or even destabilized.

This paper presents a distributed consensus-based voltage and frequency control (VFC) strategy for isolated microgrids with distributed energy resources (DERs) and induction motor loads. The proposed controller coordinates the DERs to regulate microgrid frequency and voltage while mitigating fault-induced delayed voltage recovery (FIDVR), a phenomenon where system voltage remains depressed for several seconds after fault clearance due to induction motor stalling. The VFC loop adjusts DER voltage setpoints based on frequency deviation and voltage level to regulate voltage and mitigate FIDVR events, while the active power control loop maintains frequency stability by coordinating active power sharing among DERs and compensating for the constant power load behavior of stalled induction motors. A proximity-based reactive power support prioritization and a distributed voltage estimator enhance the controller’s response to FIDVR events. Coordination between the VFC and active power control loops is achieved through adaptive gain adjustment and a voltage recovery coordination term. Simulation results demonstrate the effectiveness of the proposed controller in maintaining microgrid stability, ensuring fast voltage recovery, and providing robust performance under various operating conditions, including communication delays and different fault durations.

P. Bondi et al. (IEEE Journal of Robotics and Autom., vol.4, p.14-22, Feb. 1988) proposed a high-gain feedback method for learning control and showed that there exist gains which ensure trajectory convergence to a desired response. An adaptive gain-adjustment technique is suggested that enables the system to choose adaptively the gains which yield convergence. The technique is illustrated with the results of a simulation. >

The authors investigate the performance and reliability improvement of multiple relay cooperative free space optical (FSO) communication over direct link. Multiple gain combiner (MGC) method has been introduced as a diversity combining method which assures to provide a close to optimum performance as compared to maximal ratio combining (MRC). As compared to MRC, the proposed MGC technique does not require prior channel information and adaptive gain adjustment. Bit error rate (BER) performance improvement with different combining techniques, including MGC, in cooperative FSO system for different channel environments has been included in this study. BER performance for multiple relays for various combining techniques: selection combining, equal gain combining, MRC and MGC have been compared and it is seen that the performance of MGC is close to optimum MRC. High availability of the system is achieved by using multiple relays in the cooperative system. Markov model analysis for availability and mean time between failures of FSO systems in multiple relays cooperative communication has been done to verify the reliability improvement of a cooperative system with increasing number of relays.

The plasma vertical position at JET is stabilised using the Fast Radial Field Amplifier (FRFA). This amplifier applies voltage to the radial field coils in steps of 2.5 kV from -10 kV to 10 kV. It has a maximum current capability of 2.5 kA. The amplifier is controlled in a closed loop by the Vertical Stabilisation controller. The best settings of the gains in this controller depend on the plasma growth rate, which varies in an unpredictable manner during a JET pulse. An adaptive control algorithm based on measurements of the switching activity of the FRFA amplifier is used to adjust these settings in real time.

Multi-Input UV Communication With Adaptive Gain Adjustment

In many practical implementations of adaptive control laws it is of interest to limit the aggressiveness of the adaptive control law until it is needed in cases of abnormal operation. Many approaches have been taken in an ad hoc manner such as gain scheduling the adaptive gains or using switching mechanisms. However, none of these techniques offer a theoretically justified means of adjusting the adaptive control law in response to abnormal conditions. This paper presents a state feedback method for smoothly adjusting the adaptive gain of an adaptive law in response to increased levels of tracking error. This method allows a control designer to specify how the adaptive law adjusts its gain in response to increased tracking error. The effect of the gain adjustment process is reflected in an analysis of system tracking bounds. As the system tracking error increases, the gain adjustment mechanism warps the Lyapunov level sets in a manner that ensures tracking error remains small. The tracking bound analysis allows the theoretically guaranteed tracking bounds to be made small without necessarily requiring high adaptation gain. This offers a significant improvement over existing theoretical performance bounds.

Optimization of grid power quality using third order sliding mode controller in PV systems with multilevel inverter

Blue economy industries, such as aquaculture or deep sea mining, are moving further offshore to take advantage of the vast scale of the ocean, but moving further offshore requires access to consistent, reliable power untethered to land-based power grids. With a high potential for low cost power generation in locations otherwise isolated from the grid, marine hydrokinetic turbines could serve to help meet this growing power demand. This paper presents a novel adaptive super-twisting sliding mode control strategy for permanent magnet synchronous generators (PMSG) driven by ocean current turbines (OCT). To ensure robustness and mitigate chattering during maximum power point tracking (MPPT), an adaptive gain adjustment technique is proposed for super-twisting sliding mode control. This technique does not require knowledge of the upper bounds of uncertainties, such as external marine environment variability or unmodeled dynamics. More specifically, the adaptive gain rate can vary with a sliding variable when system states are approaching or on the sliding mode, which constitutes the novelty of this paper. The adaptive dynamic gain enables the rapid establishment of the real 2-sliding mode, and this is accomplished without overestimating or underestimating the disturbance boundary. The Lyapunov function technique is used to analyze the finite time convergence of the closed-loop system. A numerical model of a 720-kW PMSG-based OCT is utilized for validating the effectiveness of the proposed control strategy, with simulated operating environmental conditions based on ocean current data collected from the Gulf Stream off Southeast Florida.

In the presence of large uncertainty, a controller needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. As the adaptive gain increases, the time delay margin for a standard model-reference adaptive control decreases, hence loss of robustness. Optimal control modification is a new adaptive control method developed recently to achieve fast adaptation with robustness. Its formulation is based on the minimization of the L2 norm of the tracking error, posed as an optimal control problem. Computer simulations as well as pilot-in-the-loop high-fidelity simulations in a motion-based flight simulator demonstrate the effectiveness of the new adaptive law. In this study, we extend the optimal control modification to include a covariance-like adjustment mechanism of a time-varying adaptive gain to prevent persistent learning which can reduce robustness. The covariance update law can also include a forgetting factor in a similar context as a standard recursive least-squares estimation algorithm. The covariance adaptive gain adjustment allows an initial large adaptive gain to be set arbitrarily and provides the ability to drive the adaptive gain to a lower value as the adaptation has achieved sufficiently the desired tracking performance. Alternatively, a normalized adaptive gain may be used to reduce adaptation when the amplitude of an input basis function becomes large. Flight control simulation results demonstrate that both approaches can achieve significant robustness as measured by the time delay margin. Furthermore, a recent flight test program of the optimal control modification with normalization on a NASA F-18 aircraft demonstrates the effectiveness of the adaptive law.

The article designs a new kind of power function exponential reaching law based on exponential reaching law. It associates the speed of the trajectory and the distance of velocity to the sliding mode surface and uses intelligence features of the exponential function. The reaching law suppresses the chattering phenomenon and overcomes the exponential reaching law through a switch sliding mode surface. The power function exponential reaching law is applied to the Buck converter, and presents a specific Matlab/Simulink module, the simulation verified the effectiveness of this method. Introduction Sliding mode control is a kind of variable structure control method, it is not sensitive to the internal parameters and external disturbance, and has good robustness. Dynamic response is relatively excellent, suitable for engineering practice. Under ideal conditions, the switching frequency is infinite and won't produce the chattering. But in the real cases, chattering is unable to avoid. Chattering can cause high frequency oscillation in the system, it also put forward a great challenge for its application in the engineering practice. Scholars at home and abroad focus on a lot of problem of chattering on the sliding mode control method. Our scientists founded near rate method to reduce the chattering in the sliding mode movement problems and got the ideal effect . The literature [2] proposed variable speed reaching law for the first time. It produced the fan switch area, gived the fan switch area and the mathematical model of quasi sliding mode. The literature [3] combined fuzzy control with sliding mode control, adjusted the coefficient of exponential reaching law through the fuzzy rules. It settled the input fuzzy rules to the absolute value s of the switch function, the output of the fuzzy rules for coefficient and the exponential reaching law e and k , which could further improve the dynamic performance of the sliding mode, reduced the high frequency vibration of the system. The literature [4] designed a kind of adaptive variable speed reaching law in front of the track to sliding mode, used the adaptive exponential reaching law. It reached the sliding mode surface and used variable speed reaching law, effectively reduced the chattering. The literature [5] was based on power frequency approach Rate and integral reaching law. It designed a number of power points near rate and power frequency near rate index of integral sliding mode observer. The simulation results showed that the sliding mode observer had played a very good effect on inhibition of jitter. The literature [6] proposed a double exponential reaching law and increased the convergence speed of the system, the system had better dynamic quality. The literature [7] proposed a new discrete reaching law for the uncertain part of the system. Disturbance predictor was designed and made the system stable in the origin, had very high estimation precision, wreaked the chattering effectively. The literature [8] used fuzzy control for International Conference on Information Sciences, Machinery, Materials and Energy (ICISMME 2015) © 2015. The authors Published by Atlantis Press 962 on-line estimation in view of the uncertainties in the system, fuzzed adaptive adjustment of the switch gain and reduced the switch gain as far as possible, in order to reduce chattering. This paper designs a new kind of sliding mode reaching law the exponential function on the second order the Buck converter, the reaching law is based on sliding mode variable index reaching law. It adapts the design of the exponential function of symbols instead of sliding mode variable structure control switch function and a larger scale has the effect of adaptive adjustment, effectively suppress the chattering phenomenon. The mathematical model of Buck converter Buck converter is a DC Buck converter. It is also known as DC chopper, it is a kind of output voltage which is less than or equal to the average of the input voltage of the switch tube DC voltage converter. Fig.1 Buck converter topology structure diagram Fig.1 is Buck converter topology structure. U1 stands for input DC voltage, Vg stands for switch tube which is responsible for the entire circuit on and off, D stands for the fly-wheel diode, L, C stands for inductance and capacitance, RL stands for the load resistance. When the switch tube Vg conducts, charges current through the inductor L load; when switch tube Vg shuts off, the load current through the inductor L discharge. Buck converter maintains the stability of the load voltage by rapid on-off switch tube. Keeping the switch tube Vg on and off cycle can adjust the size of the load on both ends of the output current and voltage. If load is the impedance load, we consider iL inductor current and capacitor voltage vc as state variables, ignore the inductance and capacitance of the parasitic resistance. We can get the state space equation of the Buck converter:

Application of third-order sliding mode controller to improve the maximum power point for the photovoltaic system

Macro fiber composite (MFC) has been widely investigated in the active vibration control. Yet, the actuation performance of MFC is a function of temperature. For the active vibration control system using MFC based on the linear piezoelectric equation, if the actuation parameters of MFC are variable, it is easy to cause insufficient control force or control spillover, which degrades the performance of control system. Therefore, an adaptive gain adjustment approach for the active vibration control system is developed, which ensures that the active control system can maintain the expected performance of vibration suppression under the time-varying ambient temperatures. The variation of actuation performance of MFC with temperature is measured by the experiment. The polynomial fitting method is utilized to obtain the functional relationship between the regulator parameters and ambient temperature. The performance of the proposed adaptive gain regulator is verified by the experiment in the temperature environment chamber. In the experiment, a scaled vertical tail model attaching the MFC actuator is as an example, and the fractional order positive position feedback control system is as a representative of the control system without temperature adaptability. When the temperature is −60°C, compared with the control system without regulator, the reduction ratio of response RMS of the control system with adaptive gain regulator is increased by 17.26%.The results indicate that the proposed adaptive gain regulator can avoid the adverse influence of the time.varying ambient temperature on the performance of the control system.

In this paper, an image stabilization control inspired by biological gaze stabilization mechanism is addressed. An image taken from the camera mounted on a mobile robot undergoes undesirable fluctuation that leads to poor system performance in autonomous or manual operation. Therefore, image stabilization of such camera system is essential and has been received much attention in the machine vision literature. On the other hand, a human is capable of stabilizing visual input, and this biological image stabilization mechanism is generally known as vestibulo-ocular reflex (VOR) in physiology. A particular interest of this paper is to realize this VOR features to image stabilization control problem. The mathematical interpretation of VOR in terms of the stabilization control is derived and a VOR adaptation rule is newly proposed. In the proposed method, the reference to control system is adaptively modulated by an adaptive gain to minimize residual vibration of the camera as the VOR gain converges to optimal state. To verify the proposed method, the linear shaft actuator-based image stabilization device is briefly introduced first, and it is utilized for the simulation model and experiments. Simulink simulation and experiments were conducted to demonstrate the proposed method, and results showed the proposed scheme contributes to image stabilizing effect. The image stabilization performance were validated from the vibration measurements and interframe transformation fidelity of the image sequence. From simulation and experimental results, it will be shown that the proposed method has a high potential to be applied in image stabilization control under significant system variation and uncertainties.