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We explore the incremental flatness based control of single input under-actuated nonlinear Hamiltonian systems exhibiting a controllable tangent linearization model around a given equilibrium point. General properties of controllable linearized Hamiltonian systems are presented, which significantly ease the stabilizing, or output reference trajectory tracking, feedback controller design for the nonlinear system. Controllability of the tangent linear system is equivalent to its flatness. A flat filter controller and a set of nested controllers are presented which are based on incremental position measurements alone. There will be no need for explicit estimations of the conjugate momenta through observers. The proposed controller is constituted by a set of nested, second order linear Flat Filter compensation networks acting on the second order pure integration models, naturally present in the input-to-flat output system structure. For pure integration perturbed systems, Flat Filters have been shown to be equivalent, in general, to reduced order extended state observer based Active Disturbance Rejection controllers. A challenging stabilization problem for an unstable, nonlinear, two spring–mass system carrying an inverted pendulum is considered. Computer simulations illustrate the effectiveness of the proposed controller design in the presence of flat output measurement noise. • Underactuated nonlinear Hamiltonian systems may exhibit a controllable tangent linearization. • Flat output of linearized underactuated Hamiltonian systems is function of incremental positions. • Flat Filters are equivalent to Reduced Order Extended State Observers-based ADRC. • For the flatness-based control only the odd order time derivatives need be estimated. [ABSTRACT FROM AUTHOR]

This article summarizes the comprehensive design of an adaptive control that solves the trajectory tracking of a four-rotor unmanned aerial vehicle supplied by an own-designed grasping device. The controller design uses the regular proportional–derivative (PD) structure which is common to solve regulation, as well as tracking problems for robotic systems. The PD structure needs the estimation of the time-derivative to be exerted on-line. The super-twisting algorithm served to operate as a decentralized estimator of the derivatives for the tracking errors. The controller gains were adjusted by the differential laws aimed to track attainable reference trajectories. The adaptive strategy adjusts the controller gains enforcing the convergence of both the estimation and the tracking errors. A numerical example showed the observer/controller performance. A comparison with a classic non-adaptive PD controller confirms the effectiveness on the tracking task by the proposed design. In addition, a set of virtual numerical evaluations using the parameters of a real quadcopter system confirmed the performance benefits of the adaptive controller based on the PD structure aided with the estimation of the velocity obtained by the observer. • This study presents the design of an adaptive controller to solve a trajectory tracking problem. • The tracking applies for a modified unmanned aerial vehicle supplied by a grasping device. • The super twisting algorithm operated as a decentralized differentiator for the tracking errors. • The controller gains were adjusted by a differential law aimed to track attainable reference trajectories. • The adaptive gain strategy adjusts the controller gains enforcing the convergence of the tracking errors. [ABSTRACT FROM AUTHOR]

This study addressed the problem of robust control of a biped robot based on disturbance estimation. Active disturbance rejection control was the paradigm used for controlling the biped robot by direct active estimation. A robust controller was developed to implement disturbance cancelation based on a linear extended state observer of high gain class. A robust high-gain scheme was proposed for developing a state estimator of the biped robot despite poor knowledge of the plant and the presence of uncertainties. The estimated states provided by the state estimator were used to implement a feedback controller that was effective in actively rejecting the perturbations as well as forcing the trajectory tracking error to within a small vicinity of the origin. The theoretical convergence of the tracking error was proven using the Lyapunov theory. The controller was implemented by numerical simulations that showed the convergence of the tracking error. A comparison with a high-order sliding-mode-observer-based controller confirmed the superior performance of the controller using the robust observer introduced in this study. Finally, the proposed controller was implemented on an actual biped robot using an embedded hardware-in-the-loop strategy. [ABSTRACT FROM AUTHOR]

A discrete time, on-line approach is proposed for the simultaneous identification of the frequency, the amplitude and the phase parameters in continuous noisy sinusoidal signals. The proposed technique takes the exact discretization of a continuous sinusoidal signal and generates exact computation formulas for the frequency, bias, amplitude and phase parameters, calculated in terms of quotients involving functions of the output and of some of its delayed values. The formula yields exact parameter calculations in the noiseless case, and it can be synthesized by means of time-varying filters whose outputs are obtained on-line. When the treated signal is affected by additive noises, a least squares-based “invariant filtering” is proposed, resulting in an enhancement of the signal to noise ratio of the factors conforming the basic algorithm. The scheme is proven and analysed by means of a laboratory experiment, a noise analysis and a comparison against other existing methods, where the proposed method shows accurate results with fast convergence rates. [ABSTRACT FROM AUTHOR]

Abstract: An input–output based feedback controller is proposed for the sliding mode control of a large class of switched systems. The method avoids state measurements, or the use of observers, and it extends the sliding mode control design methodology to input–output descriptions of the plant. The approach regards the average Generalized Proportional Integral (GPI) output feedback controller as a guide for defining the switched implementation of the average sliding mode features via a Sigma–Delta modulation strategy. The considerations are circumscribed to the class of differentially flat systems. Experimental results are presented for a trajectory tracking problem on a DC-to-DC switched power supply of the “buck” type with unknown loads subject to abrupt variations. [Copyright &y& Elsevier]

This paper describes the design and implementation of a robust adaptive bilateral observer based control to solve the trajectory tracking problem for a class of master–slave robotic systems. The output-based bilateral control uses an adaptive observer to estimate the force and the unmeasurable velocity state considering only the master–slave system order as well as the position measurements. The stability of the observer and controller is simultaneously proved via the second method of Lyapunov. A set of experimental tests proved the performance of the presented algorithm for a manipulation task in a bilateral teleoperated system based on two delta robots. • The bilateral teleoperation for robotic systems is solved using adaptive disturbance estimation. • The disturbance adaptive estimation is based on a Least Squares Algorithm. • The disturbance is expressed by a time varying combination of the state vector. • The second method of Lyapunov is used to show the ultimate bound of the estimation/tracking error. • Experimental tests on two parallel robots show the effectiveness of the suggested controller. [ABSTRACT FROM AUTHOR]