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A neural network (NN)-based compensation control is proposed for the trajectory tracking of robotic manipulators with unknown dynamics. This compensation controller includes a PD feedback controller, a nonlinear feedback controller and a neural network compensator with input modification. The PD controller and the nonlinear feedback controller are used to ensure the stability of the robot system,...
This paper describes nonlinear control of a two degree of freedom mechanical system which models a bird perched on a branch or cable. The primary contribution is the implementation, in a controlled laboratory experiment, of the recently developed C\ adaptive control approach. This technique, which allows fast adaptation with guaranteed stability margins, has been proposed for use in a variety of more...
In the head positioning systems of hard disk drives (HDDs), multirate control is very effective since the sampling frequency is restricted by the mechanism. In the short- span seeking-mode, the mechanical vibration is getting crucial obstruction to achieve high-speed data access. In this paper, a high-order vibration suppression perfect tracking control (PTC) method is proposed based on multirate...
This paper presents a control scheme for angular position control of a rotary load using shape memory alloy (SMA) actuators in an antagonistic configuration. Hysteresis and significant nonlinearities in the stress-strain-temperature characteristics hinder effective utilization of SMA actuator. By considering the nonlinear behavior and thermal characteristics of SMA, a force control scheme based on...
A near input-output (IO) linearizing position tracking controller is a nonlinear controller based on a nonlinear model of an electrohydraulic actuator. It uses feedback of piston friction force. In this paper, a friction model is identified from offline experiments and is subsequently approximated with differentiable functions. The effects of altering the friction estimate and even of ignoring it...
It is difficult to identify the unstable processes with time delay, especially with large time delay. In this paper, a new relay feedback identification method for open-loop unstable processes with time delay is proposed. The exact expressions for the periods and amplitudes of limit cycles under the biased relay feedback are derived for unstable processes which can be modeled by first-order plus dead-time...
This paper presents the various stages for the construction of a two wheeled riding simulator. Despite its simplicity, the particularity of this simulator comes from the possibility to reproduce most of the movements and the inertial effects allowing to perceive sensations close to reality cases. This simulator has been developed for two purposes: ldr as a training tool for new riders with different...
This paper deals with the control system design of an electrohydraulic fully flexible valve actuator (EHVA) with a mechanical feedback for a camless engine. A model of the actuator was obtained using a frequency response identification method in a closed loop configuration from which a fifth-order linear model was subsequently derived. The problem was formulated using quantitative feedback theory...
The problem of model-based stabilization of a nonlinear system based on its approximate discrete-time model is addressed under the assumption that both the feedforward and the feedback paths are subject to network induced constraints. These constraints include irregularity of the transfer intervals, time-varying communication delays, and possibility of packet losses. A communication protocol that...
We analyse the control output feedback sensitivity function which results from imposing the minimal signal-to-noise ratio requirement needed for stabilisability. The signal to noise ratio constraint used here includes the effect of a band limited, additive coloured Gaussian noise communication link and a (non) minimum phase unstable continuous (discrete) linear time invariant (LTI) plant with time...
We consider a control system in which sensor data is transmitted from the plant to a receiver over a communication channel, and the receiver uses the data to estimate the state of the plant. Using a feedback policy to choose when to transmit data, the goal is to schedule transmissions to balance a trade-off between communication rate and estimation error. Computing an optimal policy for this problem...
The topic of cost-cumulant control is currently receiving substantial research from the theoretical community oriented toward stochastic control theory. For instance, the present paper extends the application of cost-cumulant controller design to control of a wide class of linear-quadratic tracking systems where output measurements of a tracker follow as closely as possible a desired trajectory via...
We propose an adaptive output-feedback control design technique for a class of feedforward systems with input-to-state stable (ISS) appended dynamics. The system contains uncertain functions involving all states with the assumed bounds on uncertain functions allowed to contain crossproducts of unknown parameters and unmeasured states. The ISS appended dynamics are coupled with all the system states...
This paper presents an extension of the L1 adaptive controller to output feedback for systems with time-varying unknown parameters and time-varying bounded disturbances. The adaptive controller ensures uniformly bounded transient and asymptotic tracking for system's both signals, input and output, simultaneously. The performance bounds can be systematically improved by increasing the adaptation rate...
This paper extends the author's previous work on spatial-based repetitive control. We propose another repetitive control design for rotational motion systems required to operate at various speeds, and subject to structured parameter uncertainty and spatially periodic disturbances. To synthesize a repetitive controller in spatial domain, a linear time-invariant system is reformulated with respect to...
Reinforcement learning refers to a class of learning tasks and algorithms in which the learning system learns an associative mapping by maximizing a scalar evaluation function by interacting with environment. Fuzzy actor critic learning (FACL) is a reinforcement learning method based on dynamic programming principle. A priori knowledge of the process either in the form of models or experts is required...
This paper proposes a new analytical method for multivariable control design for a class of stable linear multi-input-multi-output (MIMO) processes. By using the unity feedback structure, a multivariable controller with full matrix form is derived based on internal model control (IMC) theory. The proposed design approach provides a single adjustable parameter for each control loop. Two analytical...
Many multi-agent coordinated behaviors can be achieved using decentralized estimation-and-control, where each agent uses limited communication with neighbors in a network to estimate global properties of the performance of the group. This global information is used in each agent's local motion controller, creating a feedback connection between the estimators and controllers. To ensure the stability...
We study a preloaded two-bar linkage that exhibits hysteresis due to the presence of multiple attracting equilibria. The dynamics at the unstable equilibrium, through which a snap-through buckle occurs, are not linearizable due to a singularity that is solution-dependent. We stabilize the unstable equilibrium using two distinct nonlinear controllers. The feedback linearization controller requires...
This tutorial paper presents backstepping boundary control designs for fluid systems. It starts with an introduction of an output-feedback controller for the problem of vortex shedding around a cylindrical bluff body in the flow. It is then followed by a presentation of stabilization of the thermal convection loop. Finally, the paper concludes with a control design for the turbulent channel flow.
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