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In this paper, a two-layer stability control system based on output feedback is designed for electric vehicles with four in-wheel motors using super twisting sliding mode control and extended Kalman filter. The joint-extended Kalman filter method is used at the same time for estimating the state of the vehicle and the friction coefficients between the wheels and the road. In the upper layer controller, the control torque required to ensure the lateral stability of the vehicle is calculated. In the second layer, by using torque vectoring, the required traction forces for each wheel are determined so that the control torque calculated in the first layer is provided. Then the corresponding slip rates are calculated for the new adjusted longitudinal forces. Using the obtained slip rates as the desired slip rate for each wheel, the required wheel torques are computed by using appropriate longitudinal controller. Using the Kalman filter largely eliminates the effects of sensor noise and structural uncertainty on estimated parameters. The present algorithm can calculate the control inputs for the lateral and longitudinal control of the vehicle, as well as estimate the state of the system and estimate the friction coefficients between the wheels and the road at the same time. The results show the efficiency of the designed control system which is discussed on different maneuvers. [ABSTRACT FROM AUTHOR]

This paper investigates a passivity-based hierarchical SM control (PBHSMC) approach to solve the trajectory tracking issue of a special class of UMSs using unmeasured states and in presence of both unmatched and matched perturbations. First, a passivity-based SM observer (PBSMO) is designed for quick estimation of states in the UMS. Then, we develop a nonlinear two-layer switching surface using feedback passivation. The passivation-based approach ensures global asymptotical convergence of tracking error on the switching surface with the discontinuous term. Moreover, we develop an SMC law that can satisfy reaching mode and sliding mode conditions. Finally, to illustrate the performance of theoretical results, the developed control scheme is assessed by numerical simulation of two case studies including flexible-joint manipulator (FJM) and underactuated surface vessel (USV) systems. The simulation results indicate the superiority of the PBSMO-based PBHSMC scheme over the conventional SMO-based HSMC in suppressing unwanted oscillations of link, low tracking error and overshoot, short settling time, smooth and small control efforts, and also more accurate estimation of state variables with less chattering. [ABSTRACT FROM AUTHOR]

Summary: This paper reports an immersion and invariance (I&I)–based robust nonlinear controller for atomic force microscope (AFM) applications. The AFM dynamics is prone to chaos, which, in practice, leads to performance degradation and inaccurate measurements. Therefore, we design a nonlinear tracking controller that stabilizes the AFM dynamics around a desired periodic orbit. To this end, in the tracking error state space, we define a target invariant manifold, on which the system dynamics fulfills the control objective. First, considering a nominal case with full state measurement and no modeling uncertainty, we design an I&I controller to render the target manifold exponentially attractive. Next, we consider an uncertain AFM dynamics, in which only the displacement of the probe cantilever is measured. In the framework of the I&I method, we recast the robust output feedback control problem as the immersion of the output feedback closed‐loop system into the nominal full state one. For this purpose, we define another target invariant manifold that recovers the performance of the nominal control system. Moreover, to handle large uncertainty/disturbances, we incorporate the method of active disturbance rejection into the I&I output feedback control. Through Lyapunov‐based analysis of the closed‐loop stability and robustness, we show the semiglobal practical stability and convergence of the tracking error dynamics. Finally, we present a set of detailed, comparative software simulations to assess the effectiveness of the control method. [ABSTRACT FROM AUTHOR]

SUMMARY: This paper reports an extended state observer (ESO)-based robust dynamic surface control (DSC) method for triaxial MEMS gyroscope applications. An ESO with non-linear gain function is designed to estimate both velocity and disturbance vectors of the gyroscope dynamics via measured position signals. Using the sector-bounded property of the non-linear gain function, the design of an $\mathcal{L}_2$ -robust ESO is phrased as a convex optimization problem in terms of linear matrix inequalities (LMIs). Next, by using the estimated velocity and disturbance, a certainty equivalence tracking controller is designed based on DSC. To achieve an improved robustness and to remove static steady-state tracking errors, new non-linear integral error surfaces are incorporated into the DSC. Based on the energy-to-peak ($\mathcal{L}_2$ - $\mathcal{L}_\infty$) performance criterion, a finite number of LMIs are derived to obtain the DSC gains. In order to prevent amplification of the measurement noise in the DSC error dynamics, a multi-objective convex optimization problem, which guarantees a prescribed $\mathcal{L}_2$ - $\mathcal{L}_\infty$ performance bound, is considered. Finally, the efficacy of the proposed control method is illustrated by detailed software simulations. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a nonlinear disturbance rejection–based controller for the robust output regulation of a triaxial microelectromechanical system (MEMS) vibratory gyroscope. In a MEMS gyroscope, parameter variations, mechanical couplings, suspension system nonlinearities, thermal noise, and centripetal/Coriolis forces are the main uncertainty sources. In the dynamical equations of the gyroscope, these uncertainties appear as a matched total disturbance, which does not coincide with the required structure of a standard output regulation problem. More specifically, the total disturbance is not guaranteed to belong to the solution space of a fixed dynamical system. Therefore, we propose a control system that comprises a nominal output regulator equipped with a disturbance rejection loop. On the basis of a suitable reference dynamics of the gyroscope, the control system is developed as the stabilization of a zero‐error invariant manifold in the tracking error space. In the disturbance rejection loop, a nonlinear extended state observer (ESO) is designed to estimate the total disturbance. The convergence of the ESO is analyzed in a Lyapunov‐Lurie framework by linear matrix inequalities (LMIs). In the nominal output regulation loop, the stabilization problem of the desired manifold is tackled by introducing a suitable distance coordinate. Next, to achieve guaranteed attenuation of the ESO estimation errors, an energy‐to‐peak design is pursued. On the basis of the center manifold theory, the stability of the overall closed‐loop system is guaranteed. The efficacy of the proposed control method is assessed through software simulations. [ABSTRACT FROM AUTHOR]

Biomedical applications of swimming microrobots comprising of drug delivery, microsurgery and disease monitoring make the research more interesting in MEMS technology. In this paper, inspired by the flagellar motion of microorganisms like bacteria and also considering the recent attempts in one/two-dimensional modelling of swimming microrobots, a three degrees-of-freedom swimming microrobot is developed. In the proposed design, the body of the swimming microrobot is driven by multiple prokaryotic flagella which produce a propulsion force through rotating in the fluid media. The presented swimming microrobot has the capability of doing three-dimensional manoeuvres and moving along three-dimensional reference paths. In this paper, following dynamical modelling of the microrobot motion, a suitable controller is designed for path tracking purposes. Based on the resistive-force theory, the generated propulsion force by the flagella is modelled. The feedback linearization method is applied for perfect tracking control of the swimming microrobot on the desired motion trajectories. It is seen that, by the use of three flagella, the microrobot is able to perform three-dimensional manoeuvres. From the simulation results, the tracking performance of the designed control system is perfectly guaranteed which enables the microrobot to perform the desired three-dimensional manoeuvres and follow the desired trajectory. [ABSTRACT FROM AUTHOR]