Sliding Mode Extremum Seeking Control Research Articles

Disturbance Rejection Extremum Seeking: A Sliding Mode Control Approach

This paper investigates the sliding mode extremum seeking control problem for nonlinear systems with disturbances to improve the disturbance rejection capability, delivering promising searching accuracy and efficiency under disturbances. The existing results in sliding mode extremum seeking control suffer from the drawback of unsatisfactory transient performance and slow convergence speed when disturbances, especially unmatched disturbances, are injected into the system. To this end, a disturbance rejection sliding mode extremum seeking control approach is proposed in this paper. A nonlinear disturbance observer is developed for disturbance estimation, and then a disturbance rejection sliding mode extremum seeking control algorithm is proposed by exploiting the disturbance estimation. Under the proposed approach, the disturbances can be online estimated and compensated. As a result, the cost function is less disturbed by unknown disturbances, and faster convergence speed as well as shorter recovery time can be obtained. The proposed method is applied for directional antenna automatic tracking system. Simulation results show that the newly proposed searching control approach outperforms the baseline extremum searching approaches in terms of much more reliable and high efficiency searching performance under disturbances.

A novel speed optimisation scheme for unmanned sailboats by sliding mode extremum seeking control without steady-state oscillation

AbstractThis paper proposes a novel speed optimisation scheme for unmanned sailboats by sliding mode extremum seeking control (SMESC) without steady-state oscillation. In the sailing speed optimisation scheme, an initial sail angle of attack is first computed by a piecewise constant function in the feed forward block, which ensures a small deviation between sailing speed and the maximum speed. Second, the sailing speed approaches to maximum gradually by extremum search control (ESC) in the feedback block. In SMESC without steady-state oscillation, a switching law is designed to carry out the control transformation, so that the speed optimisation system carries out SMESC in the first convergence phase and ESC without steady-state oscillation in the second stability phase. This scheme combines the advantages of both control algorithms to maintain a faster convergence rate and to eliminate steady-state oscillation. Furthermore, the strict stability of the speed optimisation system is proved in this paper. Finally, we test a 12-m mathematical model of an unmanned sailboat in the simulation to demonstrate the effectiveness and robustness of this speed optimisation scheme.

Automation of the peripheral resistance valve in a hydro-mechanical cardiovascular pulse duplicator system

This paper considers the modernization of an existing non-commercial Pulse Duplicator in use at the Healing Research Laboratory at the University of Padova, Italy. The system reproduces human systemic circulation and it is used to test heart medical devices. The focus of this study is the full automation of a crucial system component that is the peripheral resistance manual valve that is replaced by a motorized one. First, under certain technological constraints, the problem of the automatic setting adjustment of the valve is tackled by using a Sliding Mode Extremum Seeking Control (ESC) method. This approach guarantees the system fundamental pressure drop to simulate the peripheral resistance to flow in the human systemic circulation in various system configurations and operating conditions. Then, the Sliding Mode ESC algorithm is embedded in an Arduino board driving the motorized valve. Finally, experimental tests are performed to assess the effectiveness of the motorized valve.

A two-variable extremum seeking controller with application to self-tuned vibration energy harvesting∗∗This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada.

A new control strategy for sliding-mode extremum seeking in two-variables is proposed in this study. The controller converts the two-variable search problem into a single-variable problem in which the direction of changes on the two-dimensional phase plane is used as the sliding mode variable. Simulations are conducted to show that the proposed method is simpler, faster and more accurate than multi-variable sliding mode extremum seeking control methods in the current literature. The proposed controller is utilized for maximum power point tracking in vibration energy harvesters where both damping and stiffness of the harvester can be tuned using power electronic techniques. Experimental results show that the proposed controller is capable of tuning the variables for seeking the extremum point without using any model of the system.

Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system

The sliding mode extremum seeking control (SMESC) could track the maximum power point (MPP) of wind energy conversion system (WECS) without wind speed or wind turbine parameters. Inappropriate SMESC parameters would cause steady-state oscillation and increase tracking time. This paper proposed an improved invasive weed optimization (IIWO) to optimize the SMESC parameters. The algorithm developed a new stochastic reproductive strategy to enhance its robustness and simplify the coding. Meanwhile, IIWO optimized double parameters coordinately to replace traditional parameter setting methods of SMESC, which could make the parameters meet the different requirements simultaneously for high efficiency. Simulation results showed that proposed IIWO-SMESC method yielded a better transient response, steady-state stability, and robustness than traditional hill-climbing search (HCS) and SMESC method.

Twisting sliding mode extremum seeking control without steady-state oscillation

In this paper, a novel sliding mode extremum seeking control (SMESC) scheme is proposed to improve the performance of the classic SMESC. In this scheme, the twisting sliding mode is employed to alleviate the chattering at the sliding stage and a gradient-based parameter adjusting strategy is designed to eliminate the oscillation during steady-state stage. The convergence and stability of this scheme are proved in a rigorous way. Moreover, the principle of parameters selection is presented to facilitate the application of this scheme. Finally, the application in proton exchange membrane fuel cell system shows the effectiveness and advantages of the scheme.

IIWO Based Sliding Mode Extremum Seeking Control for MPPT in Wind Energy Conversion System

Abstract The sliding mode extremum seeking control (SMESC) could track the maximum power point (MPP) of wind energy conversion system (WECS) without wind speed or wind turbine parameters. Inappropriate SMESC parameters would cause steady-state oscillation and increase tracking time. This paper proposed an improved invasive weed optimization (IIWO) to optimize the SMESC parameters. The algorithm developed a new stochastic reproductive strategy to enhance its robustness and simplify the coding. Meanwhile, IIWO optimized double parameters coordinately to replace traditional parameter setting methods of SMESC, which could make the parameters meet the different requirements simultaneously for high efficiency. Simulation results showed that proposed IIWO-SMESC method yielded a better transient response, steady-state stability, and robustness than conventional hill-climbing search (HCS) and SMESC method.

A self-tuning vibration energy harvester with variable loads and maximum allowable displacement**This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada.

This paper presents a constrained model-free tuning algorithm for vibration energy harvesters. Ideally, a vibration energy harvester should operate such that it can absorb the maximum available power when the system undergoes changes in amplitude and frequency of the base excitation input. Furthermore, a vibration energy harvester may have restriction on the maximum allowable value of the displacement of its mass which should not be exceeded during operation. In this paper, we utilize an electromagnetic energy converter and power electronic circuitry to create the effect of an adjustable shunt resistive load. A constrained sliding mode extremum-seeking controller is utilized such that the average harvested power is maximized and the mass displacement is kept within an allowable range. Experimental results are presented, which show that the proposed controller can track the maximum power point without violating the constraint on displacement.

Resonance frequency tuning of an RF cavity through sliding mode extremum seeking

Tuning of the natural resonance frequency of an RF cavity is crucial to achieve maximum power transfer from the cavity to the beam, to reduce power requirements, and to guarantee a predictable particle speed gain within each accelerator structure. So far, most operational cavities are frequency tuned through a phase comparison technique, which is sensitive to temperature variations if the facility or signal transportation cables are not temperature controlled. Temperature induced phase errors render this technique labor and time intensive. This paper presents an RF cavity tuning scheme, based on reflected power measurements and sliding mode extremum seeking control, to eliminate the phase measurement related difficulties. A stability analysis provides conditions on how to choose the controller parameters to guarantee stable system operation up to twice the cavity bandwidth, which is a controllable bandwidth improvement of a factor of two. The system has been implemented in two of TRIUMF’s (Canada’s particle accelerator centre) room temperature resonators and long term measurements show that the system effectively counteracts the RF heating effect as well as diurnal temperature variations.

Blade Fault Diagnosis in Small Wind Power Systems Using MPPT with Optimized Control Parameters

A systematic experiment verification of Chaos Embedded Sliding Mode Extremum Seeking Control for maximum power point tracking and a method for detecting possible faults in small wind turbine systems in advance are proposed in this paper. The chaotic logistic map is used to replace the random function in the particle swarm optimization algorithm for faster searching the optimal control parameter . From the experimental results, it is verified that the Chaos Embedded Sliding Mode Extremum Seeking Control scheme has a better dynamic response than traditional Extremum Seeking Control scheme and Hill-Climbing Search scheme for maximum power point tracking. In the proposed scheme for fault detection, a chaotic synchronization method is used to transform the maximum power point tracking signal into a chaos synchronization error distribution diagram. It is then taken as the characteristic for fault diagnosis purposes. Finally, an extension theory pattern recognition technique is applied to diagnose the fault. Notably, the use of the chaotic dynamic errors as the fault diagnosis characteristic reduces the number of extracted features required, and therefore greatly reduces both the computation time and the hardware implementation cost. From the experimental results, it is shown that the fault diagnosis rate of the proposed method exceeds 98% not only in non-real-time but also in real-time of faults detection of the blades.

Design and Study on Sliding Mode Extremum Seeking Control of the Chaos Embedded Particle Swarm Optimization for Maximum Power Point Tracking in Wind Power Systems

This paper proposes a sliding mode extremum seeking control (SMESC) of chaos embedded particle swarm optimization (CEPSO) Algorithm, applied to the design of maximum power point tracking in wind power systems. Its features are that the control parameters in SMESC are optimized by CEPSO, making it unnecessary to change the output power of different wind turbines, the designed in-repetition rate is reduced, and the system control efficiency is increased. The wind power system control is designed by simulation, in comparison with the traditional wind power control method, and the simulated dynamic response obtained by the SMESC algorithm proposed in this paper is better than the traditional hill-climbing search (HCS) and extremum seeking control (ESC) algorithms in the transient or steady states, validating the advantages and practicability of the method proposed in this paper.

EXPERIMENTAL INVESTIGATIONS OF MPPT IN A SMALL SCALE PHOTOVOLTAIC ENERGY SYSTEM BASED ON EXTREMUM SEEKING CONTROL

This study carried out experimental validation based on the simulation analysis results of Yau and Wu [1], and compared the MPPT situations of three kinds of extremum seeking control. It was proved that the sliding mode extremum seeking control has better transient response and steady-state characteristic, and changes the sunshine intensity to test the performance of algorithm, thus proving that the system can track the maximum power point rapidly in the environment with rapid atmospheric changes.

Sliding Mode Extremum Seeking Control Scheme Based on PSO for Maximum Power Point Tracking in Photovoltaic Systems

An extremum seeking control (ESC) scheme is proposed for maximum power point tracking (MPPT) in photovoltaic power generation systems. The robustness of the proposed scheme toward irradiance changes is enhanced by implementing the ESC scheme using a sliding mode control (SMC) law. In the proposed approach, the chattering phenomenon caused by high frequency switching is suppressed by means of a sliding layer concept. Moreover, in implementing the proposed controller, the optimal value of the gain constant <svg style="vertical-align:-3.3907pt;width:31.1875px;" id="M1" height="16.4125" version="1.1" viewBox="0 0 31.1875 16.4125" width="31.1875" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(.017,-0,0,-.017,.062,12.138)"><path id="x28" d="M300 -147l-18 -23q-106 71 -159 185.5t-53 254.5v1q0 139 53 252.5t159 186.5l18 -24q-74 -62 -115.5 -173.5t-41.5 -242.5q0 -130 41.5 -242.5t115.5 -174.5z" /></g><g transform="matrix(.017,-0,0,-.017,5.944,12.138)"><path id="x1D448" d="M751 650l-6 -28q-53 -1 -69 -12.5t-24 -38.5q-23 -85 -43 -192l-13 -69q-34 -181 -130 -262q-79 -65 -185 -65t-171 57q-87 77 -54 258l42 232q12 58 0.5 73t-75.5 19l8 28h263l-6 -28q-63 -5 -78 -18t-26 -74l-41 -226q-25 -135 22 -201t139 -66q99 0 161.5 68t91.5 217&#xA;l11 57q28 149 28 193q0 28 -19 38t-79 12l6 28h247z" /></g> <g transform="matrix(.012,-0,0,-.012,18.912,16.212)"><path id="x30" d="M241 635q53 0 94 -28.5t63.5 -76t33.5 -102.5t11 -116q0 -58 -11 -112.5t-34 -103.5t-63.5 -78.5t-94.5 -29.5t-95 28t-64.5 75t-34.5 102.5t-11 118.5q0 58 11.5 112.5t34.5 103t64.5 78t95.5 29.5zM238 602q-32 0 -55.5 -25t-35.5 -68t-17.5 -91t-5.5 -105&#xA;q0 -76 10 -138.5t37 -107.5t69 -45q32 0 55.5 25t35.5 68.5t17.5 91.5t5.5 105t-5.5 105.5t-18 92t-36 68t-56.5 24.5z" /></g> <g transform="matrix(.017,-0,0,-.017,25.25,12.138)"><path id="x29" d="M275 270q0 -296 -211 -440l-19 23q75 62 116.5 174t41.5 243t-42 243t-116 173l19 24q211 -144 211 -440z" /></g> </svg> is determined using a particle swarm optimization (PSO) algorithm. The experimental and simulation results show that the proposed PSO-based sliding mode ESC (SMESC) control scheme yields a better transient response, steady-state stability, and robustness than traditional MPPT schemes based on gradient detection methods.

Comparison of Extremum-Seeking Control Techniques for Maximum Power Point Tracking in Photovoltaic Systems

Due to Japan’s recent nuclear crisis and petroleum price hikes, the search for renewable energy sources has become an issue of immediate concern. A promising candidate attracting much global attention is solar energy, as it is green and also inexhaustible. A maximum power point tracking (MPPT) controller is employed in such a way that the output power provided by a photovoltaic (PV) system is boosted to its maximum level. However, in the context of abrupt changes in irradiance, conventional MPPT controller approaches suffer from insufficient robustness against ambient variation, inferior transient response and a loss of output power as a consequence of the long duration required of tracking procedures. Accordingly, in this work the maximum power point tracking is carried out successfully using a sliding mode extremum-seeking control (SMESC) method, and the tracking performances of three controllers are compared by simulations, that is, an extremum-seeking controller, a sinusoidal extremum-seeking controller and a sliding mode extremum-seeking controller. Being able to track the maximum power point promptly in the case of an abrupt change in irradiance, the SMESC approach is proven by simulations to be superior in terms of system dynamic and steady state responses, and an excellent robustness along with system stability is demonstrated as well.