Top PDF Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots

Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots

Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots

The sliding mode control includes good robustness, which is widely applied in robot dynamics control [20]–[22]. A lot of sliding mode control approaches have been proposed in recent years, such as terminal sliding model [23], global sliding model [24], neural sliding model [25]. A steady state error may occurs if a certain external disturbance in trajectory, ordinary sliding mode variable structure happens, leading to a condition that the required performance or trajectory tracking can not be reached in the system. And the designed trajectory has no robustness at the time interval before the sliding mode. In order to solve this problem, an integral variable structure sliding mode control is proposed [26], [27]. The advantages of this method include fast response, superior transient per- formance and robustness with regard to parameter variations, solving the tracking problem to a certain degree.In the practi- cal tracking system, however, there will be much uncertainty factors or non-linearity, which may affect the performance of indicators and even lead the system unable to reach the steady state. In order to estimate the unknown disturbance, reduce the influence of external disturbance and improve the control precision and robustness, this paper designs a non-linear dis- turbance observer, which can estimate disturbance, in basis of feed-forward compensation with the characteristics of simple design and without disturbance model, so that there is no need to use additional sensors.
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Sliding mode control for a surgical teleoperation system via a disturbance observer

Sliding mode control for a surgical teleoperation system via a disturbance observer

systems with both packet dropouts and channel noises in the networked scenario. Literature [11] developed a distributed state estimation method based on MHE for a class of two- time-scale nonlinear systems. These works have contributed to the teleoperation system based on network communication which enhanced robustness of the networked control system. Advanced controllers, including sliding mode con- trollers (SMCs) and adaptive controllers, have recently been developed for teleoperation systems in order to obtain accu- rate trajectory tracking and faithful force feedback. One sliding mode approach, the three-mode control scheme, can implehent a position–position, force–force, or force–position scheme, and the results show good trajectory tracking per- forhance [12]. However, it does not consider time delay. To solve the problem of the adverse effects of parametric uncertainties, an adaptive sliding mode control scheme was proposed by Motamedi et al. [13]. The algorithm has been verified on a teleoperation system with a single degree of free- dom (DOF). Yang and Hua [14] proposed a novel nonsingular fast integral terminal sliding mode (NFITSM) for a teleoper- ation system, and practical experiments on one-DOF motion tracking have now been completed. A nonsingular terminal sliding mode and adaptive finite-time control method was proposed by Zhang et al. [15], and simulation results have verified the effectiveness of this method. These methods are useful attempts to design feedback controllers that improve the performance and stability of a teleoperation system.
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Sliding Mode Control for Flexible Joint using Uncertainty and Disturbance Estimation

Sliding Mode Control for Flexible Joint using Uncertainty and Disturbance Estimation

feedback controller for trajectory tracking control problem of robotic manipulators with flexible joints is proposed in [4]. The design requires position measurements on the link as well as the motor side and the velocities required in the controller are estimated through a reduced order observer. Further, robustness of the closed loop system is established by assuming that the uncertainties satisfy certain conditions. A singular perturbation approach is employed for the same task [5], wherein the controller needs measurements of position and elastic force. A nonlinear sliding mode state observer is used for estimating the link velocities and elastic force time derivatives. A Feedback Linearization (FL) based control law made implementable using extended state ob- server (ESO) is proposed for the trajectory tracking control of a flexible joint robotic system in [6]. Controller design based on the integral manifold formulation [7], adaptive control [8], adaptive sliding mode [9] and back-stepping approach [10] are some other approaches reported in the literature. Most of the schemes that appeared in literature have certain issues that require attention. Firstly many of them require measurements of all state variables or at least the position variables on link and motor side. Next robustness wherever guaranteed, is often highly model dependent. Also some need knowledge of certain characteristics of the uncertainties, such as its bounds. A variable structure observer that requires only measurement of link positions to estimate the full state of a flexible joint manipulator is proposed in [11]. Additionally a reduced adaptive observer that requires the measurement of link and motor positions is reported in [12] and a MIMO design for the strongly coupled joints in [13].
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Adaptive observer based non linear stochastic system control with sliding mode schemes

Adaptive observer based non linear stochastic system control with sliding mode schemes

Up to now, considerable research work has been done in the control system design for many classes of nonlinear deterministic systems with uncertainties in the literature. The types of uncertainties include external disturbances, lack of knowledge of the system dynamics and time varying of system parameters. Generally, the main objective of the control system design is to set up a control strategy to eliminate or attenuate the influence of the uncertainty on the overall performance of the systems. The uncertainties in the dynamic systems could also be modelled as random noise. Recently, the global stabilization of nonlinear stochastic systems has gained increasing attraction, referring to Florchinger (1995), Deng and Krstic (1997a, 1997b and 1999) and the references therein. The widely employed concepts of stability in stochastic systems were introduced by Khas'minskii (1980) for boundedness in probability and asymptotical stability in the large in his classical work.
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A Dissipative Integral Sliding Mode Control Redesign Method

A Dissipative Integral Sliding Mode Control Redesign Method

In this paper, a redesigned robust integral sliding mode control is developed for a class of nonlinear dissipative switched systems with affine subsystems. The derived variable structure controllers guarantee the stability and convergence of the perturbed switched systems to the origin for norm bounded perturbations. The matched and unmatched perturbations are considered for the switched system, then the stable integral sliding surface is considered and the variable structure control is derived in Theorem 2. The redesigned variable structure controller preserves the stability of the closed-loop perturbed nonlinear switched system much similar to the unperturbed closed-loop switched system. Notice that, the existence of the dissipativity-based nominal control is required for the proposed redesign method. The simulation examples show the effectiveness of the proposed sliding method to dissipative nonlinear switched system in the presence of the matched and unmatched perturbations.
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Position Sensorless Control of a Permanent Magnet Stepping Motor Based on Sliding Mode Observer

Position Sensorless Control of a Permanent Magnet Stepping Motor Based on Sliding Mode Observer

Abstract This paper deals with a position sensorless control of a permanent magnet stepping motor. The proposed controller is designed to reduce the studied actuator oscillations and overshoot which can induce an erratic working. As the mechanical solutions are expensive and cumbersome, the control ones are considered to be the most suitable. Closed loop control of these motors offers significant performance advantages. But, the use of position sensors complicates the drive design and its control system. To avoid the use of position sensors which are costly and cumbersome, we propose in this paper a sliding mode observer allowing the estimation of the motor position from the statoric voltages and currents. It is proven that a sliding mode observer is robust against observed systems parametric uncertainties and well adapted to a large variety of nonlinear systems such as electrical motors. The performances of the sensorless position proportional derivative controller and the robustness of the sliding mode observer are tested by numerical simulations. The obtained results show the efficiency of the proposed control law.
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Nonlinear observer based PI sliding surface of adaptive sliding mode control for boost converter in PV system

Nonlinear observer based PI sliding surface of adaptive sliding mode control for boost converter in PV system

Due to nonlinear characteristics of boost converter, some researches have employed nonlinear controller such as sliding mode control. The robustness against parameter uncertainty and disturbance are the main reason why sliding mode control is utilized to control nonlinear system, including boost converter. Many sliding mode control methods [9-13] had been applied to boost converter. However, in practical, this control method requires to be fully known some variables, such as input voltage, inductor current, output voltage, and resistance load. As consequences, many sensors are needed to be installed to acquire those variables as input control. Implementing those methods causes increasing cost production and adding more space and weight in real system. Therefore, to reduce the number of sensors, nonlinear disturbance observer [13-15] is designed to estimate some variables, such as inductor current, output voltage, resistance load, and input voltage generated from solar array. The nonlinear disturbance observer accurately generates the estimated value of resistance load and input voltage such that when the variations of those variables exist, the proposed controller is still able to overcome those disturbances. In sliding mode control design, steady state error regulation needs to be considered. However, in [13], it is employed standard sliding surface and only use equivalent control signal to regulate boost converter. This can cause the output voltage response cannot track the varying desired output voltage and leads to steady state error. To enhance system performance, adaptive sliding mode control is applied to the boost converter for overcoming parameter uncertainty and disturbance [16-17]. Steady state error can be eliminated by constructing PI sliding surface, while ensuring sliding mode in finite time is employed reaching law dynamics and incorporates it to natural control signal. Therefore, nonlinear observer based adaptive sliding mode control with PI sliding surface is proposed for boost converter. The main contribution of this paper is to improve the system performance of voltage regulation boost converter using the combination of nonlinear observer and adaptive sliding mode control by modifying the conventional sliding surface into PI structure sliding surface. In addition, the stability of proposed method is proven by using direct Lyapunov method.
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Sliding Mode Control For Heartbeat Electrocardiogram Tracking Problem

Sliding Mode Control For Heartbeat Electrocardiogram Tracking Problem

In this paper, we have exploited the first-order sliding mode control method to track the ECG data of the human heart by three different nonlinear control laws. In order to lessen the intrinsic chattering of the classic sliding mode control system, smooth function approximations of the control input, by means of the hyperbolic tangent and the saturation function, were used. The fast Fourier transform was used to evaluate the average chattering frequency of the control inputs. The synthesized control schemes namely SMC-sign, SMC-tanh, and SMC-sat, were able to track the real-world ECG signal with an average root mean square error of 0.0306 and a chattering frequency of 92.7 Hz. The findings show that the sliding mode controllers can be implemented in electronic artificial pacemakers to provide the intended results successfully. Based on today's electronics, the involved frequency range (556.4 Hz for the worst case) is quite acceptable and practical.
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Vibration Control of Smart Structure Using Sliding Mode Control with Observer

Vibration Control of Smart Structure Using Sliding Mode Control with Observer

We aim here to deal with the active vibration reduction problem in flexible structure with uncertainties through designing reasonable sliding mode controller. The developed control strategy integrates the sliding mode control strategy and Kalman filter technique. In this paper, the vibration control of a flexible beam is investigated by using sliding mode control with observer and experimental modal test method, and taking into account the random disturbance uncertainty, modal parameter uncertainty and measurement noise. The paper is organized as follows. In section 2, a dynamic model of a flexible beam with piezoelectric actuators and strain gauge sensors is constructed by using finite element method. In section 3, the sliding mode controller with observer is proposed, and sliding surface is determined by using optimization method, and the sliding controller is designed by applying Lyapunov direct method. In section 4, experimental identification of the flexible cantilever beam is performed to obtain its modal parameters. And the experimental validation test is performed based on the dSPACE DS1103 platform. The conclusions are given in section 6.
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Fuzzy Based Trajectory Tracking Control of a Mobile Robot

Fuzzy Based Trajectory Tracking Control of a Mobile Robot

Although these methods have been proven to be efficient and provide good short term position estimates, they suffer from unbounded error growth due to the integration of minute measurements to obtain the final estimate [2]. In fact, there is a high demand for mobile robots to use in hard to reach and hazardous areas [3]. This approach involves two steps: first planning a feasible trajectory and second designing a control algorithm to follow this trajectory [4]. This method has a drawback the lack of reactivity. For more reactive navigation, kinematic constraints have been introduced in the spatial representation [5].
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Nonsingular fast terminal sliding-mode stabilizer for a class of uncertain nonlinear systems based on disturbance observer

Nonsingular fast terminal sliding-mode stabilizer for a class of uncertain nonlinear systems based on disturbance observer

Also, it is required in [14] that the external disturbance should be matched, that is, act in the channels of the inputs. To cope with these problems and attain higher accuracy, some new forms of SMC have been proposed. Moreover, SMC cannot guarantee the converging per- formance of the state trajectories to the origin in the nite time. To tackle the mentioned problem, the Terminal Sliding-Mode Control (TSMC) procedure has been suggested and performed in several control systems. TSMC technique proposes some excellent specications such as rapid response and nite-time stability in comparison with linear SMC [17]. TSMC is principally suitable for high-precision stabilization and control as it precipitates the convergence rate near the origin [18]. However, when the state trajectories of the system are far away from the origin, TSMC cannot present appropriate convergence eciency like SMC [19]. The Fast Terminal Sliding-Mode Control (FTSMC) idea guarantees fast transient convergence and strong robustness [20]. In the last decade, there has been more attention to the utilization of the mentioned technique for various control problems [21]. Neverthe- less, it should be mentioned that the FTSMC technique still requires to be further considered in robustness performances to tackle the system disturbances. 1.2. Literature review
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Back-Stepping Fuzzy Adaptive Sliding Mode Trajectory Tracking Control for Wall-Climbing Robot

Back-Stepping Fuzzy Adaptive Sliding Mode Trajectory Tracking Control for Wall-Climbing Robot

mode variable structure control is an important nonlinear control method with the advantages of being unaffected by parameter change and disturbances, quick to respond and without need for system on-line identification [15]-[18]. It is widely used in the field of robot control; however, the inevitable chattering effect that occurs in the process of a switching sliding surface influences the control performance of the system [19]. [20] proposed an adaptive sliding-mode controller based on the “Super-Twist” state observer (ASMC), the ASMC can provide a highly efficient control of nonlinear systems in the presence of nonmodeled dynamics and external perturbations. [21] proposed a sliding mode adaptive neural network tracking controller (SMANNC), the SMANNC can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. [22] proposed a novel adaptive dynamic sliding mode controller (ADSMC) with integrator in control loop for the trajectory tracking, for compensating uncertainties and disturbances, the equivalent control is augmented by a discontinuous control. [23] proposed a fuzzy adaptive multi-mode sliding mode control (FAMMSMC) for precision linear stage. Although the FAMSMC method can effectively reduce chattering, the control accuracy is relatively low and the pose error is relatively large. [24] proposed a back-stepping adaptive sliding mode (BASMC) trajectory tracking control for a quad- rotor. The BASMC simplifies the controller design by using intermediate virtual control variables and Lyapunov functions, but fails to suppress chattering effectively. [25] proposed a back-stepping sliding mode control (BSMC) for variable speed wind turbine, but it still doesn't solve the chattering problem.
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Analysis of Tracking Performance in Machine Tools for Disturbance Forces Compensation using Sliding Mode Control and PID Controller

Analysis of Tracking Performance in Machine Tools for Disturbance Forces Compensation using Sliding Mode Control and PID Controller

In order to study controllers performance in terms of cutting force compensation, different cutting force characteristics are collected for analysis and validation purpose. Sliding mode controller and PID controller are designed, implemented and validated numerically. Based on the results obtained, sliding mode controller exhibits better tracking accuracy than PID controller. Sliding mode controller is able to maintain tracking errors within ±25 µm and control input signals within ±1 V while PID controller recorded tracking errors within ±700 µm and control input signals within ±15 V. These results show that sliding mode controller is an effective and robust controller as it performed good tracking with variation in cutting force behaviors. It is also showed that the boundary layer solution, that is, the continuous approximation of signum function reduced the chattering phenomenon previously observed in ideal sliding mode controller. As future work, other approaches in solving the chattering phenomenon can be implemented such as observer-based solution and state-dependent gain method. Other than that, higher order sliding mode controller is an attractive approach to be implemented in the system as it is able to overcome the chattering and at the same time, provides high accuracy control, that is, improve the performance of system and reduction in positioning error.
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Fault detection for modular multilevel converters
based on sliding mode observer

Fault detection for modular multilevel converters based on sliding mode observer

This paper proposes a SMO-based fault detection method for a MMC. Simulations, which include device voltage drops and commutation delays, have shown that it is effective in locating the faulty switch and very robust against both parameter uncertainty and measurement error. This method is also independent of operation frequency of a MMC. With parallel execution, the open-circuit fault can be located within a very short time. The accuracy of the measurement may limit the application of this method–it is not able to locate the fault when the systematic measurement error is larger than 7%.
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Attitude Control using a Disturbance Observer Based Controller

Attitude Control using a Disturbance Observer Based Controller

The launch vehicles are broadly divided into two main types: Re-Usable Launch Vehicle and Extinguishable Launch vehicle. The general equations describing motion are initially obtained by ordinary differential equations [16]. These are equations of force and momentum incorporating flexibility and sloshing. These equations are valid only for short time periods-on the order of a few seconds. Vehicle properties such as mass, centre of gravity location, and moment of inertia are assumed constant in this interval. But while applying this assumptions, further complications are introduced because of the fact that the vehicle mass varies with time. The derivation of the equations of motion of a space launch vehicle-including the effects of elasticity, fuel sloshing and engine inertia maybe applied by Newton’s laws directly to the entire vehicle. The general equations of force and momentum are derived and by removing the sloshing, inertia and flexible terms, the equation of rigid body is obtained. Here, the longitudinal dynamics of an RLV in atmospheric phase is considered. The equations of motion of RLV are described by continuous non-linear differential equations. Some assumptions are taken to obtain a linearised model of a launch vehicle. The time varying mass and inertial properties are assumed to be invariant for a short period of time. The deviations from the reference trajectory are assumed to be small. The attitude dynamics are assumed to be de-coupled. The non-linearities of sensors and actuators are neglected.
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Sliding Mode Observer based Actuator Fault Reconstruction for a Continuous Reactor

Sliding Mode Observer based Actuator Fault Reconstruction for a Continuous Reactor

In some systems like CSTR reactors and other complex systems, some sensors cannot be placed in desirable location. There is not any reason for that, expect fault detection and isolation. Fault in sensors or actuators can cause process degradation even in the chemical plants. For instance lower product quality. Addition Fault cause fatal accidents (e.g. temperature run-away). Furthermore, for a group of variables no sensor exists. Concentrations and moles belong to this group. So the accurately monitoring process variables and interpreting their variations increases quickly with the increase in the range of instrumentation. For operating a process in normal situation used a set of tools and methods, called supervision. Two main activities of supervision are real Fault Detection and Isolation (FDI) and Fault Tolerant Control (FTC). The parts of the supervision scheme are shown in Fig. 1. FDI and FTC achieve safe operation of the system in the presence of faults. This paper is focused on FDI,
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Fault-tolerant individual pitch control using adaptive sliding mode observer

Fault-tolerant individual pitch control using adaptive sliding mode observer

It is well known that hydraulic pitch systems play a signifi- cant role in limiting the output power of wind turbines and reducing unbalanced blade loads by IPC system under high wind conditions (Lan et al. (2018)). Nevertheless, pitch systems often suffer from low pressure faults caused by oil leakage in the hydraulic supply system, resulting in slow pitch dynamics and further negative effects on operational stability and even accelerating the blade vibrations. Fault tolerant control (FTC) can compensate fault effects and maintain satisfactory system performance under faulty cases (Patton (2015)). There has been a few papers focus- ing on the detection and compensation of faults occurred in the pitch system. The fault detection and fault isolation (FDI) is used in the work of Sloth et al. (2011) to detect the occurrence of the actuator faults. Fault estimation (FE) observer-based FTC design has been demonstrated to be competent at obtaining the pitch actuator fault reconstruction compared with FDI (Chen et al. (2013), Shi and Patton (2015)). However, very little work has been reported to consider IPC cases, this can be a disadvantage. The remainder of this paper is organized as follows.
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Second Order Sliding Mode Observer-Based Control for Uncertain Nonlinear MEMS Optical Switch

Second Order Sliding Mode Observer-Based Control for Uncertain Nonlinear MEMS Optical Switch

Several control strategies have been proposed in the literature for the MEMS optical switch. Owusuet al. [3] designed a controller based on the feedback linearization to compensate the nonlinearity in the system dynamics, and succeeded in stabilizing theswitch position of the MEMS optical switch. However, the result was not acceptable by applying the disturbances/uncertainties to the plant. Ebrahimietal.[4] presented a robust controller based on the traditional sliding mode theory for a MEMS optical switch. Vali et al. [5] introduced the quantitative robust feedback theory to control a nonlinear MEMS optical switch in the presence of parameter variations and unknown disturbances. One of the most important differences between “macro-scale” and “micro-scale” control design is the added modeling uncertainties and nonlinearities in“micro-scale”. Hence, the implementation of the proposed controller is attenuated by increasing the inherent complexity of the system.
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Sliding Mode Load torque Observer based effective disturbance rejection for a 3 Phase BLDC drive

Sliding Mode Load torque Observer based effective disturbance rejection for a 3 Phase BLDC drive

In this work an Exponential reaching law based Sliding mode controller (SMC) controller has been proposed for the outer loop speed control of the 3-Phase Brushless DC(BLDC) motor drive. The robust hysteresis controller is employed to control the inner loop current performance of the drive. The developed SMC control scheme is simulated on MATLAB/SIMULINK platform under varying load torque disturbances up to the rated torque capability and the variable speed performance of the drive is tested. A sliding mode based load torque observer has also been designed for implementation of the scheme on real time basis. The efficient load torque rejection capabilities of the developed control scheme using the sliding mode load torque observer is then compared with a Proportional Integral (PI) based controller.
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A Current-Based Output Feedback Sliding Mode Control for Speed Sensorless Induction Machine Drive Using Adaptive Sliding Mode Flux Observer

A Current-Based Output Feedback Sliding Mode Control for Speed Sensorless Induction Machine Drive Using Adaptive Sliding Mode Flux Observer

Abstract This paper presents a new adaptive Sliding-Mode flux observer for speed sensorless and rotor flux control of three-phase induction motor (IM) drives. The motor drive is supplied by a three- level space vector modulation (SVM) inverter. Considering the three-phase IM Equations in a stator stationary two axis reference frame, using the partial feedback linearization control and Sliding-Mode (SM) control, the rotor speed and rotor flux controllers are derived first. These controllers are capable of making the drive system states follow the system nominal trajectories in spite of the motor parameter uncertainties and external load torque disturbance. Then, based on the Lyapunov theory, a SM observer is developed in order to estimate the rotor flux, rotor speed and rotor resistance simultaneously. In addition, in order to satisfy the persistent excitation (P.E) condition, a low frequency low amplitude ac signal is superimposed to the rotor flux reference command. Finally, the validity and effectiveness of proposed control approach is verified by computer simulation.
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