Neural network-based adaptive sliding mode control for underactuated dual overhead cranes suffering from matched and unmatched disturbances

To improve transportation capacity,dual overhead crane systems(DOCSs)are playing an increasingly important role in the transportation of large/heavy cargos and containers.Unfortunately,when trying to deal with the control problem,current methods fail to fully consider such factors as external disturbances,input dead zones,parameter uncertainties,and other unmodeled dynamics that DOCSs usually suffer from.As a result,dramatic degradation is caused in the control performance,which badly hinders the practical applications of DOCSs.Motivated by this fact,this paper designs a neural network-based adaptive sliding mode control(SMC)method for DOCS to solve the aforementioned issues,which achieves satisfactory control performance for both actuated and underactuated state variables,even in the presence of matched and mismatched disturbances.The asymptotic stability of the desired equilibrium point is proved with rigorous Lyapunov-based analysis.Finally,extensive hardware experimental results are collected to verify the efficiency and robustness of the proposed method.

Finite-time convergence of an nth nonlinear system with unmatched disturbance and its application in integrated guidance and control system

The finite-time convergence problem of an nth nonlinear system with unmatched disturbance is primarily studied in this paper. During the recursive procedure, a new finite-timecontroller is designed and proven by adding a sign function and a power integrator. Meanwhile, a C1 positive definite and proper Lyapunov function, which satisfies the finite-timeLyapunov stability law, is designed. Finally, the designed finite-time controller is appliedto some examples and an application of integrated guidance and control system to testand verify its advantage and practicability.

An adaptive sliding mode controller design to cope with unmatched uncertainties and disturbance in a MEMS voltage reference source

Tunable micro-electro-mechanical systems(MEMS)capacitors as the fundamental parts are embedded in MEMS AC voltage reference sources(VRS).Being concerned with the accuracy of the output voltage in the reference sources,it gets important to address uncertainties in the physical parameters of the MEMS capacitor.The uncertainties have the great inevitable potentiality of bringing about output voltage perturbation.The output deterioration is more remarkable when the uncertainties are accompanied by disturbance and noise.Manufacturers have been making great attempts to make the MEMS adjustable capacitor with desired rigorous physical characteristics.They have also tried to mitigate physical parameter veracity.However,ambiguity in the values of the parameters inescapably occurs in fabrication procedures since the micro-machining process might itself suffer from uncertainties.Employing a proportional integral(PI)adaptive sliding mode controller(ASMC),both terms of matched and unmatched uncertainties as well as the disturbance,are addressed in this work for the MEMS AC VRS so that a strict voltage is stabilized while the system is simultaneously subjected into uncertainties and exogenous disturbance.Cross-talk,some inertial forces,and electrostatic coercions may appear as matched and unmatched disturbances.Alteration in stiffness and damping coefficients might also take place as matched uncertainties due to variations in the fabrication process or even working environment.The simulation results in the paper are persuasive and the controller design has shown a satisfactory tracking performance.