Explore the vast range of titles available.

This paper studies operator and fractional order nonlinear robust control for a spiral counter-flow heat exchanger with uncertainties and disturbances. First, preliminary concepts are presented concerning fractional order derivative and calculus, fractional order operator theory. Then, the problem statement about nonlinear fractional order derivative equation with uncertainties is described. Third, the design of an operator fractional order controller and fractional order PID controller and determination of several related parameters is described. Simulations were performed to verify tracking and anti-disturbance performance by comparison to different control cases; verification is described and concluding remarks provided.

Considering sensor faults for a thermoelectric cooler actuated by Peltier devices, this work proposes an operator-based robust nonlinear fault tolerant controller (FTC) integrated with early fault detection using a support vector machine (SVM). Firstly, a physical model is formulated based on the law of heat transfer, and the estimated model is derived based on Volterra identification. Then, an operator-based robust nonlinear control system is employed to compensate for uncertainties and to eliminate the effects of coupling. Furthermore, FTC integrated with SVM-based early fault detection is designed to improve the safety performance in the case of sensor faults. The simulation results indicate that SVM-based fault detection can shorten the detection time in comparison to the conventional method without the SVM classier. The experiment results are utilized to verify the tracking performance of the proposed FTC method in the case study.

This paper presents a methodology to solve the problem of robustification of Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) scheme for the case of under-actuated systems with inertia matrix dependent of the unactuated coordinates. Specifically, we analyze the robustness of the IDA-PBC strategy with respect to constant external disturbances. This algorithm requires adding an integral action with a particular change of coordinates in an outer-loop to the IDA-PBC strategy to reject constant external disturbances. The asymptotic stability of the proposed controller despite constant external disturbances is proved using the closed-loop Hamiltonian as a Lyapunov candidate function and LaSalle’s invariance principle. Finally, as a proof of concept, we have applied the proposed robust IDA-PBC strategy to an Unmanned Aerial vehicle that transports a payload suspended by a cable, which is a class of underactuated system with inertia matrix dependent of the unactuated coordinate. Satisfactory results in numerical experiments demonstrate the applicability of the method.

High precision motion control of permanent magnet linear motors (PMLMs) is limited by undesired nonlinear dynamics, parameter variations, and unstructured uncertainties. To tackle these problems, this paper presents a neural-network-based adaptive robust precision motion control scheme for PMLMs. The presented controller contains a robust feedback controller and an adaptive compensator. The robust controller is designed based on the robust integral of the sign of the error method, and the adaptive compensator consists of a neural network component and a parametric component. Moreover, a composite learning law is designed for the parameter adaption in the compensator to further enhance the control performance. Rigorous stability analysis is provided by using the Lyapunov theory, and asymptotic tracking is theoretically achieved. The effectiveness of the proposed method is verified by comparative simulations and experiments on a PMLM-driven motion stage.

This paper proposes a nonlinear robust H∞ excitation controller based on an improved slime mould optimization algorithm (ISMA) to enhance the stability and anti-disturbance performance of synchronous generators (SGs) in power systems. First, a nonlinear dynamic model of the excitation system (ES) is established based on the electromechanical coupling mechanism of SGs, and it is transformed into an equivalent linear state-space form through feedback linearization. Subsequently, a controller design framework with linear matrix inequality (LMI) constraints satisfying H∞ performance indicators is constructed, and ISMA is utilized to optimize the key design parameters, thereby balancing dynamic response and control robustness. Simulation results demonstrate that, compared with traditional excitation control strategies, the proposed method exhibits superior comprehensive performance in terms of transient response speed, steady-state regulation accuracy, and robust performance under parameter perturbations and disturbance conditions. The research results can provide a technical reference for achieving safe and stable operation of SGs in power grids.

Deep space missions are recently gaining increasing interest from space agencies and industry, their maximum exponent being the establishment of a permanent station in cis-lunar orbit within this decade. To that end, autonomous rendezvous and docking in multi-body dynamical environments have been defined as crucial technologies to expand and maintain human space activities beyond near Earth orbit. Based on analytical and numerical formulations of the relative dynamics in the Circular Restricted Three Body Problem (CR3BP), a family of optimal, linear and nonlinear, continuous and impulsive, guidance and control techniques are developed for the design of end-to-end rendezvous trajectories between co-orbiting spacecraft in this multi-body dynamical environment. To this end, several modern control techniques are effectively designed and adapted to this problem, with particular emphasis on the design of low cost rendezvous manoeuvres. Finally, the designed hybrid rendezvous strategies, combining both discrete and continuous control techniques, are effectively tested and validated under several start-to-end deep space testbench mission scenarios, where their performance is compared and quantitatively assessed with a set of performance indices.

This paper is concerned with the synthesis of reduced-order robust nonlinear controllers for more efficient robust mitigating of friction-induced vibration (FIV) issued from the mode-coupling mechanism. A novel scheme is proposed and developed. It consists of the centre manifold approach which is first proposed for reducing the dimension of the system model to control. Then, the obtained reduced model is exploited to synthesize a sliding-mode-based reduced-order controller which is then applied on the full-order original model for suppressing or at least mitigating the mode-coupling-based FIV. The main objective of the proposed study is to analyse performances of the proposed reduced-order controller in terms of its capacities to efficiently mitigate mode-coupling-based vibrations while ensuring suitable robustness levels with respect to the centre manifold-based reduced model inaccuracy and the friction coefficient uncertainty.

This paper addresses the problem of trajectory tracking control of an underactuated surface vessel moving in a two-dimensional space in the presence of unknown disturbances. In a preliminary stage, a couple of nonlinear observers is derived to obtain an estimate of the perturbations, which are assumed to originate from unmodeled time-varying dynamics and/or exogenous disturbances. Secondly, we resort to the Lyapunov-based backstepping technique to design two stabilizing control laws, governing the thrust force and torque actuations, that are proved to render the overall control system error globally uniformly bounded. Each control law yields an actuator signal which is implicitly bounded with respect to the position error, and the resulting estimation and tracking errors can be made arbitrarily small by tweaking the control parameters. A set of realistic simulations results is presented to validate our strategy. Experimental trials using an autonomous surface vehicle are also showcased to further demonstrate the efficacy and robustness of the proposed controller.

This paper presents a novel robust decentralized control of electrically driven robot manipulators by adaptive fuzzy estimation and compensation of uncertainty. The proposed control employs voltage control strategy, which is simpler and more efficient than the conventional strategy, the so-called torque control strategy, due to being free from manipulator dynamics. It is verified that the proposed adaptive fuzzy system can model the uncertainty as a nonlinear function of the joint position error and its time derivative. The adaptive fuzzy system has an advantage that does not employ all system states to estimate the uncertainty. The stability analysis, performance evaluation, and simulation results are presented to verify the effectiveness of the method. A comparison between the proposed Nonlinear Adaptive Fuzzy Control (NAFC) and a Robust Nonlinear Control (RNC) is presented. Both control approaches are robust with a very good tracking performance. The NAFC is superior to the RNC in the face of smooth uncertainty. In contrast, the RNC is superior to the NAFC in the face of sudden changes in uncertainty. The case study is an articulated manipulator driven by permanent magnet dc motors.