Sliding-mode control based on internal model principle

Linear feedback control based on internal model principle achieves asymptotic tracking for linear system with known linear exogenous signal dynamics. This paper investigates the case of rejecting exogenous chaotic signals with known nonlinear dynamics for linear systems in the discrete time domain. Feedback controllers based on the internal model principle and predictive internal model control respectively are proposed and investigated in this paper. Both control algorithms are based on inversion of the linear system. It is shown that asymptotic tracking performance is achieved when perfect plant inversion is possible and it cannot be achieved with either algorithm when inversion errors from unmodeled dynamics or plant nonminimum phase zeros exist. The closed loop stability and performance rely on the relative size of the linear system inversion errors to the exogenous signal's local growth rate.

H∞ gain-scheduled controller design for rejection of time-varying narrow-band disturbances applied to a benchmark problem

This work focuses on the model-free iterative learning control (ILC) design with good transient performance and fast convergence rate that is employed for precision control of a wafter stage. First, the experimental setup, the mathematical model, and the desired reference are introduced. Notice that the desired reference and its internal model (IM) are known in advance. Then, based on the internal model principle (IMP), a new ILC scheme, named as 1M-based ILC, is proposed by incorporating the 1M of the reference. The proposed 1M-based ILC is model-free, that is, independent on the system model of the controlled plant. The 1M -based ILC is carefully constructed to track the reference along the time axis while tracking/rejecting repetitive variations along the iteration axis. Precisely because of the tracking capability along the time axis in every iteration, the 1M-based ILC can achieve satisfactory performance even in the 0th iteration and improve the transient performance and the convergence speed. In addition, the 2-D $H_{\infty}$ theory is used to establish the design criterion for the 1M-based ILC. Finally, in the experiments, the efficiency of the 1M-based ILC is illustrated by comparing with a P-type ILC and a model-based one.

The underactuated autonomous underwater vehicle (AUV) depth‐tracking approach is presented in this research along with comparative field experiments. First, a model‐free ADRC‐SMC pitch autopilot method is proposed to eliminate dynamics‐related disturbances. The active disturbance rejection control (ADRC) framework is adopted to compensate the complicated and unknown pitch dynamics into an approximate integral series type. Sliding mode control (SMC) feedback law is designed to further compensate for dynamic feedback linearization inaccuracy of the ADRC framework. Second, the disturbance rejection double‐loop depth‐tracking approach is suggested in conjunction with adaptive line‐of‐sight (ALOS), which converts depth tracking into pitch tracking. The ALOS not only estimates the actual angle of attack but also compensates the pitch‐tracking inaccuracy from the ADRC‐SMC in the inner loop. Then, the uniformly semiglobally exponential stability of the closed‐loop depth controller is proved after a detailed analysis of the stability from the inner loop to the outer loop. Finally, comparative field experiments are conducted to verify the proposed method. The effectiveness and strong disturbance rejection capabilities of the ADRC‐SMC pitch autopilot method and the suggested depth‐tracking approach are demonstrated by experimental results.

To enhance the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor speed control system, a novel speed control method based on a novel sliding mode control (NSMC) and load torque observer is proposed on the basis of model predictive current control (MPCC) with a sliding mode disturbance observer. First, on the basis of MPCC, the influence of parameters such as resistance, inductance, and flux linkage on MPCC is analyzed. To address the aggregated disturbance caused by parameter mismatches, a piecewise square-root switching function sliding mode disturbance observer (SMDO) is designed to enhance the robustness of the parameters. To address the poor dynamic performance and inadequate robustness resulting from the proportional-integral-controller (PI) velocity loop control in the MPCC, a novel NSMC velocity control method is proposed. This method utilizes the hyperbolic sine function and fractional-order integral sliding mode surface, resolving the dilemma faced by traditional slide mode controllers (SMC) in balancing fast response and reduced vibration. Additionally, to enhance the system’s disturbance rejection capability, a sliding mode torque observer (SMTO) is designed to continuously update the observed load torque value into the NSMC controller, achieving speed compensation control. Finally, through comparative experiments among the proportional integral controller (PI), SMC, NSMC, and NSMC + SMTO, the results indicate that the proposed NSMC + SMTO exhibits the best speed response, steady-state characteristics, and disturbance rejection capability.

This paper proposes an improved digital voltage controller suitable for three-phase PWM inverters with output transformer for medium and high power uninterruptible power supplies (UPS). The proposed controller is derived from the internal model principle using a state-variable approach in stationary alphabeta frame. With this controller it is possible to obtain a high performance in both steady-state and load transients. In addition, with the selected internal model, DC components result from real circuit implementation non-idealities are not amplified avoiding in this way, the transformer saturation. The UPS output voltages have reduced total harmonic distortion (THD) for both balanced and unbalanced non-linear loads. Regarding the transient performance, load steps responses are improved with the proposed digital controller and as a result the UPS compliant with the classification 1 of the international standard IEC 62040-3. In order to validate the proposed digital controller and to demonstrate the steady-state and transient performance, experimental results from a 10 kVA space vector modulated three-phase inverter, fully controlled by a DSP TMS320F241, are presented

This paper presents an Artificial Intelligence (AI) based approach uniquely applied to Permanent Magnet DC motor actuator for position control. The AI method employed in this work is Fuzzy logic. A first order lag Sliding mode controller is tuned and combined with an Adaptive Fuzzy- PI controller architecture which operates in parallel. The controller architecture proposed in this study is aimed at improving the disturbance rejection capability, steady state as well as transient performance of the conventional Adaptive Fuzzy-PI controller and sliding mode controller. Hence, the robust control law of the proposed controller (SM+FZ-PI) consists of a discontinuous Sliding mode output added to a continuous Adaptive Fuzzy-PI controller output. The sliding mode controller switches on only when disturbance in the system is detected. The performance of the proposed controller architecture has been compared with a conventional PID and Adaptive Fuzzy-PI controllers for performance evaluation with respect to several operating conditions such as load torque disturbance injection, noise injection in feedback loop, motor non-linearity exhibited by parameters variation, and a step change in reference input demand. The proposed controller (SM+FZ-PI), had the best disturbance rejection and steady state error elimination.

Purpose The purpose of this paper aims to investigate an effective algorithm for different types of disturbances rejection. New dynamics are designed based on disturbance. Observer-based sliding mode control (SMC) technique is used for approximation the disturbances as well as to stabilize the system effectively in presence of uncertainties. Design/methodology/approach This research work investigates the disturbances rejection algorithm for fixed-wing unmanned aerial vehicle. An algorithm based on SMC is introduced for disturbances rejection. Two types of disturbances are considered, the constant disturbance and the sinusoidal disturbance. The comprehensive lateral and longitudinal models of the system are presented. Two types of dynamics, the dynamics without disturbance and the new dynamics with disturbance, are presented. An observer-based algorithm is presented for the estimation of the dynamics with disturbances. Intensive simulations and experiments have been performed; the results not only guarantee the robustness and stability of the system but the effectiveness of the proposed algorithm as well. Findings In previous research work, new dynamics based on disturbances rejection are not investigated in detail; in this research work both the lateral and longitudinal dynamics with different disturbances are investigated. Practical implications As the stability is always important for flight, so the algorithm proposed in this research guarantees the robustness and rejection of disturbances, which plays a vital role in practical life for avoiding any kind of damage. Originality/value In the previous research work, new dynamics based on disturbances rejection are not investigated in detail; in this research work both the lateral and longitudinal dynamics with different disturbances are investigated. An observer-based SMC not only approximates the different disturbances and also these disturbances are rejected in order to guarantee the effectiveness and robustness.

This paper presents a non-linear Sliding Mode Control (SMC) strategy based on continuous switching law for large-power (10MW) Permanent Magnet Synchronous Generator (PMSG) based Wind-Energy Conversion System (WECS). The WECS model consists of a wind turbine, PMSG, rectifier fed boost converter, PWM inverter and the filter. The controller is used to maintain the DC-link voltage constant and to generate controlled active and reactive power for grid. For verification of validity of proposed control scheme and model, the proposed system's dynamic model is simulated in MATLAB/Simulink. SMC has the promising features of: fast switching, insensitivity to parameter uncertainty, disturbance rejection quality, and more robustness than the conventional linear controllers. The proposed continuous control compelled the states trajectories of the system onto the surface in error space (sliding surface) for the system behavior to obtain design specifications. Simulation results demonstrate that the proposed SMC is effective and gives superior performance than conventionally tuned PI controller.

Harmonic disturbance rejection is an important field of control theory and applications. In this paper a discrete first and second order sliding mode control for multivariable systems are investigated. The necessary conditions of harmonic disturbances rejection using first and second order sliding mode control laws are elaborated. In order to improve the performances of sliding mode control in periodic disturbances rejection, a discrete repetitive sliding mode control is presented. A necessary condition for the choice of the discontinuous terms in discrete repetitive sliding mode control is then developed. The different proposed control strategies have been tested on numerical simulation example. The obtained results are very satisfactory in terms of compensation of periodic disturbances using discrete repetitive sliding mode control.

In complex industrial situations, modern permanent magnet synchronous motor (PMSM) servo drive system always face different kinds of disturbances, especially constant or slowly-varying disturbances (load disturbances) and periodic disturbances (torque ripples). Conventional disturbance rejection techniques, e.g., the extended state observer based control (ES-OBC) and the disturbance observer based control (DOBC), can only reject asymptotically single kind of disturbances (constant or slowly-varying disturbances). To this end, it is essential to extend the conventional disturbance rejection approach for multiple disturbances. Inspired by the internal model principle (IMP), appropriately embedding the model of disturbances into the design of disturbance observer, a composite disturbance observer based control is proposed for PMSM with multiple disturbances. The proposed disturbance observer (named as IMESO), consisting of the internal model principle (IMP) and the extended state observer (ESO), can reject multiple disturbances asymptotically. Thus, a composite control law consisting of proportional feedback and disturbance feedforward compensation is developed to control the speed loop. The proposed method is effective to reject the intricate multiple external disturbances and unmodeled dynamics. Simulations and experiments both verify the effectiveness of the proposed method.

The direct drive of the permanent magnet linear synchronous motor (PMLSM) requires excellent disturbance rejection capability to achieve precise position control. This article proposes an improved adaptive linear active disturbance rejection control (IALADRC) to improve trajectory tracking and disturbance rejection capability. First, we explain the difference between proportional–integral–derivative (PID) control and LADRC in terms of trajectory tracking and disturbance rejection. Unlike PID, which uses the integral controller to reject disturbances, LADRC uses the extended state observer (ESO) to decouple reference tracking and disturbance rejection. This simplifies the PMLSM control system to a second-order system, which in turn inspired the proposal of the improved LADRC (ILADRC). ILADRC reconstructs the disturbance from the position error using the inverse closed-loop model and injects it into the control output, resulting in better control performance. Due to the complex disturbance existing in the motion process of PMLSM, an improved adaptive ESO (AESO) is proposed to strike a balance between disturbance estimation and noise reduction. The ILADRC and the improved AESO are combined to form the IALADRC. Comparative experiments show that the IALADRC has excellent disturbance rejection capability and significantly improves the position control accuracy of the PMLSM system.

This paper shows the synthesis of a robust predictive controller from a process model that represents a good approximation for nonlinear chemical processes. The controller is designed using the internal model and sliding mode control concepts. This approach results in a fixed controller structure that depends on the characteristic parameters of the model. The controller performance is compared with internal model control and sliding mode control for different linear examples. All linear models present a controllability relationship (t0/U) of greater than 1. Simulation results indicate that the proposed controller can work for processes with elevated deadtime, despite modeling errors.

Inspite of so much research, key technical problem, naming chattering of conventional, simple and robust SMC is still a challenge to the researchers and hence limits its practical application. However, newly developed soft computing based techniques can provide solution. In order to have advantages of conventional and heuristic soft computing based control techniques, in this paper various commonly used intelligent techniques, neural network, fuzzy logic and adaptive neuro fuzzy inference system (ANFIS) have been combined with sliding mode controller (SMC). For validation, proposed hybrid control schemes have been implemented for tracking a predefined trajectory by robotic manipulator, incorporating structured and unstructured uncertainties in the system. After reviewing numerous papers, all the commonly occurring uncertainties like continuous disturbance, uniform random white noise, static friction like coulomb friction and viscous friction, dynamic friction like Dhal friction and LuGre friction have been inserted in the system. Various performance indices like norm of tracking error, chattering in control input, norm of input torque, disturbance rejection, chattering rejection have been used. Comparative results show that with almost eliminated chattering the intelligent SMC controllers are found to be more efficient over simple SMC. It has also been observed from results that ANFIS based controller has the best tracking performance with the reduced burden on the system. No paper in the literature has found to have all these structured and unstructured uncertainties together for motion control of robotic manipulator.

A fundamental problem of visuomotor adaptation research is to understand how the brain is capable to asymptotically remove a predictable exogenous disturbance from a visual error signal using limited sensor information by re-calibration of hand movement. From a control theory perspective, the most striking aspect of this problem is that it falls squarely in the realm of the internal model principle of control theory. Despite this fact, the relationship between the internal model principle and models of visuomotor adaptation is currently not well developed.This paper aims to close this gap by proposing an abstract discrete-time state space model of visuomotor adaptation based on the internal model principle. The proposed DO Model, a metonym for its most important component, a disturbance observer, addresses key modeling requirements: modular architecture, physically relevant signals, parameters tied to atomic behaviors, and capacity for abstraction. The two main computational modules are a disturbance observer, a recently developed class of internal models, and a feedforward system that learns from the disturbance observer to improve feedforward motor commands.