25,324 research outputs found
Enhanced Continuous Higher Order Sliding Mode Control with Adaptation
This is the author accepted manuscript. The final version is availabel from Elsevier via the DOI in this recordThis paper proposes a new Continuous Adaptive HOSM control algorithm. The key
advantage of the adaption scheme is that it does not require knowledge of the bounds on
the matched uncertainty, and the gains themselves are not conservatively overestimated
by the adaption scheme – which helps mitigate the problem of chattering. Compared
with earlier work, two variable parameters are allowed to adapt and this facilitates
much better self-tuning capabilities and improved closed-loop performance
Adaptive Discrete Second Order Sliding Mode Control with Application to Nonlinear Automotive Systems
Sliding mode control (SMC) is a robust and computationally efficient
model-based controller design technique for highly nonlinear systems, in the
presence of model and external uncertainties. However, the implementation of
the conventional continuous-time SMC on digital computers is limited, due to
the imprecisions caused by data sampling and quantization, and the chattering
phenomena, which results in high frequency oscillations. One effective solution
to minimize the effects of data sampling and quantization imprecisions is the
use of higher order sliding modes. To this end, in this paper, a new
formulation of an adaptive second order discrete sliding mode control (DSMC) is
presented for a general class of multi-input multi-output (MIMO) uncertain
nonlinear systems. Based on a Lyapunov stability argument and by invoking the
new Invariance Principle, not only the asymptotic stability of the controller
is guaranteed, but also the adaptation law is derived to remove the
uncertainties within the nonlinear plant dynamics. The proposed adaptive
tracking controller is designed and tested in real-time for a highly nonlinear
control problem in spark ignition combustion engine during transient operating
conditions. The simulation and real-time processor-in-the-loop (PIL) test
results show that the second order single-input single-output (SISO) DSMC can
improve the tracking performances up to 90%, compared to a first order SISO
DSMC under sampling and quantization imprecisions, in the presence of modeling
uncertainties. Moreover, it is observed that by converting the engine SISO
controllers to a MIMO structure, the overall controller performance can be
enhanced by 25%, compared to the SISO second order DSMC, because of the
dynamics coupling consideration within the MIMO DSMC formulation.Comment: 12 pages, 7 figures, 1 tabl
Adaptive sliding mode observers in uncertain chaotic cryptosystems with a relaxed matching condition
We study the performance of adaptive sliding mode observers in chaotic synchronization and communication in the presence of uncertainties. The proposed robust adaptive observer-based synchronization is used for cryptography based on chaotic masking modulation (CM). Uncertainties are intentionally injected into the chaotic dynamical system to achieve higher security and we use robust sliding mode observer design methods for the uncertain nonlinear dynamics. In addition, a relaxed matching condition is introduced to realize the robust observer design. Finally, a Lorenz system is employed as an illustrative example to demonstrate the effectiveness and feasibility of the proposed cryptosyste
Yaw Rate and Sideslip Angle Control Through Single Input Single Output Direct Yaw Moment Control
Electric vehicles with independently controlled drivetrains allow torque vectoring, which enhances active safety and handling qualities. This article proposes an approach for the concurrent control of yaw rate and sideslip angle based on a single-input single-output (SISO) yaw rate controller. With the SISO formulation, the reference yaw rate is first defined according to the vehicle handling requirements and is then corrected based on the actual sideslip angle. The sideslip angle contribution guarantees a prompt corrective action in critical situations such as incipient vehicle oversteer during limit cornering in low tire-road friction conditions. A design methodology in the frequency domain is discussed, including stability analysis based on the theory of switched linear systems. The performance of the control structure is assessed via: 1) phase-plane plots obtained with a nonlinear vehicle model; 2) simulations with an experimentally validated model, including multiple feedback control structures; and 3) experimental tests on an electric vehicle demonstrator along step steer maneuvers with purposely induced and controlled vehicle drift. Results show that the SISO controller allows constraining the sideslip angle within the predetermined thresholds and yields tire-road friction adaptation with all the considered feedback controllers
Function based control for bilateral systems in tele-micromanipulation
Design of a motion control system should take into
account (a) unconstrained motion performed without interaction
with environment or any other system, and (b) constrained
motion with system in contact with environment or other systems.
Control in both cases can be formulated in terms of maintaining
desired system configuration what makes essentially the same
structure for common tasks: trajectory tracking, interaction force
control, compliance control etc. The same design approach can be
used to formulate control in bilateral systems aimed to maintain
desired functional relations between human and environment
through master and slave motion systems. Implementation of
the methodology is currently being pursued with a custom built
Tele-micromanipulation setup and preliminary results concerning
force/position tracking and transparency between master and
slave are clearly demonstrated
Sliding modes in constrained systems control
Abstract—In this paper, a sliding-mode-based design framework
for fully actuated mechanical multibody system is discussed.
The framework is based on the possibility to represent complex
motion as a collection of tasks and to find effective mapping of
the system coordinates that allows decoupling task and constraint
control so one is able to enforce concurrently, or in certain time
succession, the task and the constraints. The approach seems naturally
encompassing the control of motion systems in interaction,
and it allows application to bilateral control, multilateral control,
etc. Such an approach leads to a more natural interpretation of
the system tasks, simpler controller design, and easier establishment
of the systems hierarchy. It allows a unified mathematical
treatment of task control in the presence of constraints required
to be satisfied by the system coordinates. In order to show the
applicability of the proposed techniques, simulation and experimental
results for high-precision systems in microsystem assembly
tasks and bilateral control systems are presented
Integral sliding modes generation via DRL-assisted Lyapunov-based control for robot manipulators
This paper proposes an enhanced version of the integral sliding mode (ISM) control, where a deep neural network (DNN) is first trained as a deep reinforcement learning (DRL) agent. Then, such a DNN is fine-tuned relying on a Lyapunov-based weight adaptation law, with the aim of compensating the lack of knowledge of the full dynamics in the case of robot manipulators. Specifically, a DRL agent is trained off-line on a reward depending on the sliding variable to estimate the unknown drift term of the robot dynamics. Such an estimate is then exploited to initialize and perform the fine tuning of the online adaptation mechanism based on the DNN. The proposal is theoretically analysed and assessed in simulation relying on the planar configuration of a Franka Emika Panda robot manipulator
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