SMC Method Research Articles

Adaptive neural network-based sliding mode control of rotary inverted pendulum system

This paper introduces a new adaptive neural network-based sliding mode control of rotary inverted pendulum system (RIPS) subject to model uncertainties and disturbances. First, the sliding mode control is designed using the double power rate reaching law. Second, an adaptive neural network (ANN) is exploited to deal with model uncertainties and disturbances. The weight matrices of the neural network are adaptively tuned. In the proposed control method the exact dynamic model of the RIPS is not required due to the exploitation of the universal property of the neural network. Moreover, the implementation of a double power-reaching law can greatly suppress the undesirable chattering. The convergence and stability analysis is validated using Lyapunov stability theory. Finally, the robustness and excellence of the proposed control strategy are verified by comparing the system performance with the existing SMC method and improved super-twisting SMC method.

Modified Three-Element Modeling and Robust Tracking Control for a Planar Pneumatic Soft Actuator

In pneumatic soft robotics systems, pneumatic soft actuators (PSAs) are the most important components, so it is necessary to study the precise modeling and control over PSAs for application. This paper focuses on a self-designed planar PSA, named pneumatic bellow actuator (PBA), and proposes a modified three-element model (MTEM) and a nonlinear disturbance observer-based sliding mode control (NDO-based SMC) method to achieve the robust tracking control objective of the PBA with multiple uncertainties. Firstly, the dynamic characteristics of the PBA are analyzed based on experimental data obtained from open-loop experiments of the PBA. Then, based on these dynamic characteristics, a semi-phenomenological MTEM is established considering coupling between the dynamics of the PBA and load as well as friction, which can describe the dynamics of the PBA with changing loads in the rough horizontal plane precisely. Model parameters are then identified by Levenberg-Marquardt (LM) algorithm. Next, identification errors, device disturbances and external disturbances are regarded as the multiple uncertainties of the PBA, and the NDO-based SMC method is proposed based on the MTEM to realize the robust tracking control objective of the PBA. The stability of the control system is proved. The effectiveness of the proposed method is verified by experiments.

Modeling and control of wastewater treatment process with time delay based on event-triggered recursive least squares

Accurate control of dissolved oxygen (DO) concentration is the key to ensuring the quality of effluent from the wastewater treatment process (WWTP). However, the delay disturbance caused by the hydraulic retention time (HRT) hinders the accurate control of DO concentration. To solve this problem, an event-triggered recursive least squares-based sliding mode control (ETRLS-SMC) is proposed to overcome the obstacles caused by the delay disturbance for accurate control of DO concentration. First, a differential equation with a delay disturbance term is established to describe the dynamic process of the system. Then, the delay disturbance is explicitly depicted to lay the foundation for the controller design considering delay disturbance variables. Second, an RLS identification algorithm is used to online obtain the model parameters of the system. In particular, an event-triggered mechanism is designed to reduce the number of model updates with guaranteed accuracy. Third, combined with the ETRLS identification algorithm, an SMC method is introduced to control the DO concentration with delay disturbance variables. Then, the control law is computed to achieve stable control of the system. Finally, the performance of ETRLS-SMC is verified on the benchmark simulation model 1 (BSM1). The results show that the proposed method can reduce ISE by 0.0014 and 0.0128 when the threshold is 2.5% in two cases, including the reference value being fixed and changed, compared with the case without considering the delay disturbance. The results of trigger mechanism test further demonstrate the effectiveness of event-triggered mechanism.

Spin-symmetry broken ground-state of UO2 in DFT+U approach: the SMC method

Spin-symmetry broken ground-state of UO2 in DFT+U approach: the SMC method

Continuous output feedback sliding mode control for underactuated flexible-joint robot

The tracking control based on output feedback for a category of flexible-joint robot (FJR) systems is investigated in this brief. Control performance of the systems is inevitably bearing the brunt of various unknown time-varying disturbances, which can be categorized to be matched and mismatched and generally cover internal parameter uncertainties, couplings, unmodelled dynamics, and external load or changing operating environments. To cope with these disturbances, the mismatched disturbances are first transferred to the matched ones by a flatness method, which eliminates the computational cost of estimating mismatched disturbances. Then, a generalized proportional integral observer (GPIO) is constructed to estimate the unavailable states and disturbances. By integrating the estimated disturbance and states provided by the GPIO, a novel dynamic sliding surface is constructed. Finally, a continuous sliding mode control (CSMC)-based output feedback control framework is further designed. The presented control strategy only requires link position information and is continuous, which can effectively reduce the chattering driven by the high-frequency switching item in the traditional SMC method. Asymptotic convergence of output tracking error is guaranteed by theoretical analysis under some mild conditions. Comparative tests on a two-link FJR verify the claimed control performance.

Saturated PD-SMC method for suspension systems by exploiting beneficial nonlinearities for improved vibration reduction and energy-saving performance

In this paper, through purposely employing beneficial nonlinear stiffness and damping with a constructed bioinspired reference model, a novel saturated PD with sliding mode control method (referred to as saturated PD-SMC method), is designed for active suspension systems under saturated control input constraints. The designed control method has several distinct benefits, including the simple structure of PD control method, strong robustness of SMC method with respect to model uncertainties and external disturbances, without requirements of exact system parameters associated with traditional SMC method, as well as taking input constraints into consideration. In the designed control method, the PD part is employed to stabilize the controlled active suspension system, the SMC part is applied to provide strong robustness, and the saturation functions are introduced to prevent the violation of control input constraints. The corresponding stability analysis is provided by Lyapunov techniques. Several experimental results show that, the proposed control method dramatically improves transient performance in comparison with some existing methods, including significantly decreasing control energy by 30% for sinusoidal road profile, and decreasing control energy up to 66% for random road profile, which achieve a satisfactory trade-off between costs and results for suspension system control. As far as we know, it is the first time to combine PD control, SMC method, and saturation structures together, to achieve obvious performance improvements for suspension systems, and simultaneously, complete stability analysis is given.

Model-Based Safety Analysis of Movement Authority Scenario in TcCBTC system

Train-centric communication based train control (TcCBTC) system contains a variety of uncertain factors in the operation process, and the generation scenario of movement authority is a real-time process. In order to judge the impact of uncertain factors on system safety, it is necessary to conduct formal modeling and analysis for this implementation process. Aiming at the modeling and analysis of the system in an uncertain environment, firstly, the implementation process of TcCBTC movement authority was analyzed, and the hazard source identification is carried out by combining the hazard and operability study (HAZOP) method. Secondly, the movement authority generation process is modeled based on the stochastic hybrid automata theory, and the statistical sample data are simulated in UPPAAL-SMC. Finally, the statistical model checking algorithm was used to analyze the model quantitatively. The results showed that the model could meet the functional attribute requirements of movement authority generation in TcCBTC system, and describe the uncertain environment in the process of system operation. SMC method could quickly verify the impact of uncertain factors on the system, and provide a certain theoretical basis for subsequent TcCBTC system development and relevant specifications.

Fuzzy SMC Method for Active Suspension Systems with Non-ideal Inputs Based on a Bioinspired Reference Model

This paper copes with robust control of vehicle suspension in a simpler way, with guaranteed performance and less energy consumption. To this end, a fuzzy SMC method for active suspension system based on bionic nonlinear dynamics is designed. Unlike existing results, the proposed control method effectively exploits the beneficial nonlinear stiffness and damping of the biomimetic reference model, resulting in energy-saving performance. At the same time, some practical problems are fully considered, including input saturation, dead zone, unknown/uncertain dynamics, as well as external interference. Theoretical analysis and simulation results illustrate that the designed fuzzy SMC method based on bionic dynamics could effectively suppress the vibration of the active suspension system, improve ride comfort as well reduce energy consumption

Implementation of a PID Type Sliding-Mode Controller Design Based on Fractional Order Calculus for Industrial Process System

This paper is devoted to designing a fractional order Proportional Integral Derivative (PID) type sliding mode control method (FO-PIDSMC) for a non-linear liquid level coupled tank process system. By considering the individual advantages of the FO calculus and PID type SMC method, this proposed FO-PIDSMC technique is designed to integrate the FO calculus method with PID type SMC scheme to obtain an accurate and robust liquid level tracking in terms of the predefined reference trajectory. The real-time experimental results of the proposed controller suggest a dramatic improvement over the traditional process system controller methods in both trajectory tracking and required control action.

Finite control set model predictive torque control using sliding model control for induction motors

Finite control set model predictive torque control (FCS-MPTC) has become increasingly prevalent for induction motors (IM) owing to its simple concept, easy incorporation of constraints and strong flexibility. In traditional FCS-MPTC speed controller design, a classical proportional integral (PI) controller is typically chosen to generate the torque reference. However, the PI controller is dependent on system parameters and sensitive to the load torque variation, which seriously affects control performance. In this paper, a model predictive torque control using sliding mode control (MPTC + SMC) for IM is proposed to enhance the robust performance of the drive system. First, the influence of the parameter mismatches for FCS-MPTC is analyzed. Second, the shortcomings of traditional PI controller are derived. Then, the proposed MPTC + SMC method is designed, and the MPTC + PI and MPTC + SMC are compared theoretically. Finally, experimental results demonstrate the correctness and effectiveness of the proposed MPTC + SMC. In comparison with MPTC + PI, MPTC + SMC has the better dynamic performance and stronger robust performance against parameter variations and load disturbance.

EM-based algorithms for single particle tracking of Ornstein-Uhlenbeck motion from sCMOS camera data.

Single particle tracking plays an important role in studying physical and kinetic properties of biomolecules. In this work, we introduce the application of Expectation Maximization (EM) based algorithms for solving localization and parameter estimation problems in SPT using data captured from scientific complementary metal-oxide semiconductor (sCMOS) camera sensors. Two representative methods are considered for generating the filtered and smoothed distributions needed by EM: Sequential Monte Carlo - EM, and Unscented - EM. The SMC method uses particle filtering and particle smoothing to handle general distributions, while the U scheme reduces the computational burden through the use of an unscented Kalman Filter and an unscented Rauch-Tung Striebel Smoother. We also investigate the influence of the number of images in the dataset on the final estimates through intensive simulations as well as the computational efficiency of the two methods.

Back-stepping Active Disturbance Rejection Control for Attitude Control of Aircraft Systems Based on Extended State Observer

Robust flight control laws based on back-stepping technology and ADRC method are designed for attitude control of a non-linear aircraft system. First, non-linear aircraft model is introduced and converted to standard equation of state. Then, the extended state observer is applied to estimate the unknown variables, the homologous ADRC is designed to ensure the state variables of the CLS to astringe to the reference state. Next, the stability of ESO and ADRC are analyzed and proven theoretically. At last, the effectiveness of this method is illustrated by extensive comparative simulations. The results acquired from simulation attest that ADRC can achieve better control performance than PID and SMC method.

A Bioinspired Dynamics-Based Adaptive Fuzzy SMC Method for Half-Car Active Suspension Systems With Input Dead Zones and Saturations

Active suspension systems are widely used in vehicles to improve ride comfort and handling performance. However, existing control strategies may be limited by various factors, including insufficient consideration of different operation conditions, such as changing in vehicle mass, defects in strategy design leading to incapability for guaranteeing finite-time stability, lack of considering input effects of dead zone and saturation, excessive energy cost, etc. Importantly, very few results considered the energy-saving performance of active suspension systems although a well-perceived issue in practice. An adaptive fuzzy SMC method based on a bioinspired reference model is established in this article, which is to purposely address these problems and be able to provide finite-time convergence and energy-saving performance simultaneously. The proposed control method effectively utilizes beneficial nonlinear stiffness and nonlinear damping properties that the bioinspired reference model could provide. Therefore, superior vibration suppression performance with less energy consumption and improved ride comfort can all be obtained readily. By using a fuzzy-logic system (FLS), the proposed method is beneficial in compensating for system parameter uncertainties, external disturbances, input dead zones, and saturations. Furthermore, based on the adaptive PD-SMC method, the tracking errors can converge to zeros in finite time. The stability of the equilibrium point of all the states in active suspension systems is theoretically proven by Lyapunov techniques. Finally, simulation results are provided to verify the correctness and effectiveness of the proposed control scheme.

Nonlinear Disturbance Observer-Based Sliding Mode Control for the PMSM with Matched and Mismatched Disturbances

High-efficiency permanent-magnet synchronous motor (PMSM) is a key technology to improve the driving range of batteries in electric vehicles, while the mismatched disturbance that is caused by external disturbances and parameter perturbation may easily result in speed fluctuations and overshoot of the PMSM, which further deteriorate the performance and efficiency of batteries. To solve the problem, a novel nonlinear disturbance observer-based sliding mode control (NDO-SMC) is proposed. Compared with the traditional SMC method, the NDO-SMC scheme has better disturbance rejection ability in the presence of matched and mismatched uncertainties and disturbances by introducing the estimation value of the nonlinear disturbance observer in the sliding surface. Furthermore, owing to the compensation of the disturbance observer, the switching gain is only required to be greater than the bound of the disturbance estimation error rather than that of the disturbance; thus, the chattering problem is substantially alleviated. A rigorous stability proof of the whole closed-loop system is given in detail using Lyapunov theory by designing an appropriate Lyapunov function. The simulation results demonstrate the feasibility and superiority of the proposed NDO-SMC strategy.

Active disturbance rejection sliding mode control for robot manipulation

PurposeIn recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.Design/methodology/approachThe main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.FindingsThe employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.Originality/valueHigh-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

Sliding mode control design for autonomous surface vehicle motion under the influence of environmental factor

Autonomous Surface Vehicle (ASV) is a vehicle that is operated in the water surface without any person in the vehicle. Since there is no person in the ASV, a motion controller is essentially needed. The control system is used to make sure that the water vehicle is moving at the desired speed. In this paper, we use a Touristant ASV with the following specifications: the length is 4 meters, the diameter is 1.625 meters, and the height is 1.027 meters. The main contribution of this paper is applying the Sliding Mode Control system to the Touristant ASV model under the influence of environmental factors. The environmental factors considered in this work are wind speed and wave height. The Touristant ASV model is nonlinear and uses three degree of freedom (DOF), namely surge, sway and yaw. The simulation results show that the performance of the closed-loop system by using the SMC method depends on the environmental factors. If environmental factors are higher, then the resulting error is also higher. The average error difference between those resulted from the simulation without environmental factors and those with the influence of environmental factors is 0.05% for surge, sway and yaw motions.

Chattering-Free Adaptive Finite-Time Sliding Mode Control for Trajectory Tracking of MEMS Gyroscope

One of the inevitable problems with real-time control systems is the presence of the uncertainties and external disturbances. The existence of these uncertainties in the fabrication processes of the MEMS Gyroscope devices can deeply impact the performance of the devices. In this paper, five adaptive finite time robust control methods are employed based on SMC method for a Micro-Electro-Mechanical System (MEMS) Gyroscope with mismatched uncertainties and external disturbances to achieve trajectory tracking goal. A new Stepping SMC method is proposed in this study to improve some deficiencies of conventional and existing methods including Simple SMC, Classical SMC, Cubic SMC, and Hexagonal SMC. The upper bound of mismatched uncertainties is estimated in finite time and their estimation is utilized in the control inputs for all five control methods. The elimination of chattering phenomenon is considered in this paper. The system finite time stability proof is obtained using Lyapunov stability theory. The numerical simulation is performed in Simulink/MATLAB for the MEMS gyroscope system to demonstrate the effectiveness of our proposed control method, Stepping SMC, compared with four other methods. To make an extensive comparison among results, the performance criterion, Integral of the square value (ISV), is used.

Nutritional assessment of compost by SMC method for white button mushroom cultivation in Maharashtra

Like human beings and animals, White Button Mushroom (WBM) also require food, for growth and development of its fruit body. This fruit body is composed of certain chemical elements frequently referred to as plant nutrients or plant diet elements. Carbon, hydrogen, oxygen, nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, iron, manganese, boron, zinc and copper. Mushroom cultivated on the compost. Compost prepared for WBM was formulated without any addition of inorganic fertilizer. Samples were collected and dispatched to a research laboratory for analysis to determine the nutrient content of compost. The fresh compost had varied, with carbon: nitrogen ratio of 26.13 to 20.24% and carbon:phosphorus ratio of 49.95 to 34.92% and carbon:potassium ratio of 62.83 to 82.84%. Organic matter content between 31.65 to 24.49% and carbon between 39.79 to 17.81%. For the primary macronutrients, average total nitrogen content 1.25%, phosphorus measured 0.68%, and potassium was 0.414%. Boron 9.51 ppm, Mn 145.70 ppm, Fe 3515.58 ppm, Cu 10.17 ppm and Zn 25.53 ppm. Overall, fresh prepared compost is suitable for WBM cultivation.

Statistical Based Algorithm for Reducing Residual Error in Embedded Systems Implemented Using the Controller Area Network

In this paper, a new approach is introduced to reduce bit stuffing and consequently residual error probability in the controller area network (CAN). The proposed method is based on XOR masking. Unlike the XOR method, the proposed approach does not use a fixed mask for all IDs. Using statistical parameters of data, a proper mask for each CAN ID is generated and applied to the messages before transmitting. The performance of the method to reduce bit stuffing and residual error probability has been evaluated by considering a real data set. Results show that the method can significantly reduce bit stuffing and residual error probability. A comparison has been also conducted with previously reported methods. The results show the superiority of the SMC method in reducing residual error without payload and data transfer rate reduction.

Study on vehicle active suspension system control method based on homogeneous domination approach

AbstractIn an active suspension system, there is an actuator mounted between the sprung mass and the unsprung mass to change the stiffness and damp of the suspension for ride comfort and handling stability. Because the active suspension control system is an under‐actuated system, the control problem of the active suspension is challenging but interesting. In order to solve this issue, a novel vehicle active suspension control method based on homogeneous domination approach is proposed in this paper. Firstly, a groundhook control model is constructed according to the general active suspension dynamic model. In order to deal with the additional terms of the control system which are harmful for convergence, a homogeneous domination approach is used to construct an active suspension homogeneous controller (ASHC). A useful technical theorem is proposed in the stability analysis to show that the proposed ASHC can guarantee the states of the active suspension system being stabilized. Compared with the SMC method and without any controller (passive suspension), the simulation results indicate that the proposed ASHC is effective.