Adaptive Output Control Research Articles

Design and Verification of Adaptive Adjustable Output Control on Micro Spray Gun

The general spray gun is used for industrial large-area spraying, and there is less demand for different pressures and the accuracy of spraying pressure, so mechanical pressure regulators are mostly used. However, as the demand for artistic innovation continues to grow, it promotes the advent of the micro spray gun. The micro spray gun is currently commonly known as an airbrush. The micro spray gun is mainly used for fine drawing, so it must provide different pressures with high precision pressures, but the existing mechanical regulators cannot meet this requirement. For these unmet requirements, this study proposed a solution for PID (proportional-integral-derivative) control micro spray gun system. The results showed that the PID control could effectively provide various stable output pressures of the micro spray gun. The pressure-varying range of 30 kPa could rapidly return to the target value in 10 s (the usual spraying time). The proposed solution then presents better spraying effects.

Use of microelectromechanical measuring systems to stabilize the spatial position of the platform

With the growth of sea freight, as well as cargo operations at sea, in particular the transfer of cargo in difficult climatic conditions, there is a need for automated systems. Such systems can compensate for the disturbing effects of the rolling of ships and allow the safe transfer of cargo on the high seas. One such system is an automated cargo receiving platform located on the receiving vessel. To assess the feasibility of its construction and efficiency of work, a physical model of an automatic stabilized platform has been developed using micromechanical measuring systems that ensure its stabilization in the horizontal plane. In the course of building the model, its functional and kinematic diagram was developed. The problem of processing the received «raw» data from microelectromechanical sensors: a gyroscope and an accelerometer has been solved. Control algorithms are constructed using a PID controller in the program code, as well as a complementary filter for combining accelerometer and gyroscope readings. The work of the model is to keep the platform in a horizontal plane; regardless of the movement of the base (the vessel on which it is installed). The created model showed high efficiency, fast response, positioning accuracy. The stabilization system developed on the basis of the simulated one is capable of working in difficult conditions, ensuring safety when loading on the open sea. Based on the developed model of the automatic stabilized platform, the adaptive output control algorithms were tested.

Adaptive output control of a mobile manipulator hanging from a quadcopter unmanned vehicle

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.

Prescribed performance adaptive neural output control for a class of switched nonstrict‐feedback nonlinear time‐delay systems: State‐dependent switching law approach

SummaryThis paper investigates the tracking problem for a class of uncertain switched nonlinear delayed systems with nonstrict‐feedback form. To address this problem, by introducing a new common Lyapunov function (CLF), an adaptive neural network dynamic surface control is proposed. The state‐dependent switching rule is designed to orchestrate which subsystem is active at each time instance. In order to compensate unknown delay terms, an appropriate Lyapunov‐Krasovskii functional is considered in the constructing of the CLF. In addition, a novel switched neural network–based observer is constructed to estimate system states through the output signal. To maintain the tracking error performance within a predefined bound, a prescribed performance bound approach is employed. It is proved that by the proposed output‐feedback control, all the signals of the closed‐loop system are bounded under the switching law. Moreover, the transient and steady‐state tracking performance is guaranteed by the prescribed performance bound. Finally, the effectiveness of the proposed method is illustrated by two numerical and practical examples.

Output Adaptive Switching Controller Design with DREM-Based Multi-Harmonic Disturbance Cancellation

A new DREM-based (Dynamic Regressor Extension and Mixing) modification for output adaptive controller with input multi-harmonic disturbance cancellation is proposed in this paper. This approach provides monotonic convergence of the disturbance internal model parameters’ estimates to its true values. We also introduce a novel algorithm for the DREM-based estimator gains tuning in order to improve convergence under poor excitation. Parallel kinematics Ball-and-Plate robotic system is considered as a test-bed, while the non-prehensile ball stabilization in a predefined coordinates under bounded disturbances is a task to be solved.

Algorithm of adaptive output control of linear system with improved parametric convergence

Algorithm of adaptive output control of linear system with improved parametric convergence

Fradkov Theorem-Based Control of MIMO Nonlinear Lurie Systems

Consideration was given to the problem of adaptive output control of the class of MIMO (Multiple Input Multiple Output) systems that are functionally and parametrically uncertain. An approach to the design of the control law ensuring stabilization of the MIMO nonlinear Lurie system, that is, a system consisting of the linear part (strictly minimum-phase unit) and nonlinear static feedback unit, was proposed on the basis of the Fradkov theorem on feedback passification of linear systems.

Adaptive Boundary Control for a Flexible Manipulator With State Constraints Using a Barrier Lyapunov Function

In this paper, the problem of state constraints control is investigated for a class of output constrained flexible manipulator system with varying payload. The dynamic behavior of the flexible manipulator is represented by partial differential equations. To prevent states of the flexible manipulator system from violating the constraints, a barrier Lyapunov function which grows to infinity whenever its arguments approach to some limits is employed. Then, based on the barrier Lyapunov function, boundary control laws are given. To solve the problem of varying payload, an adaptive boundary controller is developed. Furthermore, based on the theory of barrier Lyapunov function and the adaptive algorithm, state constraints and output control under vibration condition can be achieved. The stability of the closed-loop system is carried out by the Lyapunov stability theory. Numerical simulations are given to illustrate the performance of the closed-loop system.

Алгоритмы адаптивного и робастного управления по выходу роботизированным макетом надводного судна

Алгоритмы адаптивного и робастного управления по выходу роботизированным макетом надводного судна

Output Adaptive Controller for a Class of MIMO Systems with Input Delay and Multisinusoidal Disturbance

We present a new output control approach for a class of MIMO systems with the input delay and unknown multisinusoidal disturbance affected the inputs and the outputs. We combine the well-known predictor feedback approach with the state observer and adaptive scheme for feed-forward disturbance rejection based on disturbance observer. Compared to the existing approaches, our adaptive scheme is applicable to plants that are unstable, non-minimum phase, and have an arbitrary relative degree and delay.

Adaptive fuzzy output feedback control of nonlinear uncertain systems with unknown backlash-like hysteresis based on modular design

In this paper, an adaptive fuzzy output feedback control approach is presented for a class of single-input single-output uncertain nonlinear systems with unknown backlash-like hysteresis and unmeasured states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a state filter observer is designed to estimate unmeasured states. Combining the backstepping recursive design with modular design techniques, a new adaptive fuzzy output control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. A simulation is included to illustrate the effectiveness of the proposed approach. The important feature of the proposed control approach is that it can solve the states immeasurable problem of nonlinear systems with unknown backlash-like hysteresis and the problem of unknown virtual control coefficients.

Dynamic Positioning System for Nonlinear MIMO Plants and Surface Robotic Vessel

In this paper the new control approach for a class of nonlinear MIMO systems with unknowns is proposed. The mathematical model is divided on two parts: static MIMO transformation and a few SISO channels that allows to design the control law in two steps. At the first step we design the virtual controls for each SISO channel and then after the inverse MIMO transformation we propose the control law for considered system. In the paper the recent advantages in the development of adaptive output control approach using high-gain principle named by the authors as “consecutive compensator” is applied for SISO channels. We present the robotic research setup designed for analysis of control algorithms oriented to complex technical objects. This setup is a model of real plant with similar constraints for developers: parametric uncertainty, delay, disturbances, and bounded control.

An iterative algorithm of adaptive output control with complete compensation for unknown sinusoidal disturbance

The problem is considered for the output control of a linear, parametrically indeterminate object subjected to the effect of an external unknown, sinusoidal disturbing influence. The solution of this problem is found in the class of iterative adaptive algorithms involving the channels of stabilization and identification of the frequency of a disturbing influence.

Adaptive fuzzy modular backstepping output feedback control of uncertain nonlinear systems in the presence of input saturation

In this paper, we present a new scheme to design adaptive fuzzy output-feedback controller for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a state filter is designed to estimate unmeasured states. Combining the backstepping recursive design with modular design techniques, a new adaptive fuzzy output control scheme is synthesized. Unlike some existing control schemes for systems with input saturation, the developed controller dose not require assumptions on the states available and nonlinear systems satisfying the matching condition. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. A simulation is included to illustrate the effectiveness of the proposed approach.

Adaptive Output-Feedback Fuzzy Tracking Control for a Class of Nonlinear Systems

This paper is concerned with the problem of adaptive fuzzy tracking control via output feedback for a class of uncertain single-input single-output (SISO) strict-feedback nonlinear systems. The dynamic feedback strategy begins with an input-driven filter. By utilizing fuzzy logic systems to approximate unknown and desired control input signals directly instead of the unknown nonlinear functions, an output-feedback fuzzy tracking controller is designed via a backstepping approach. It is shown that the proposed fuzzy adaptive output controller can guarantee that all the signals remain bounded and that the tracking error converges to a small neighborhood of the origin. Simulations results are presented to demonstrate the effectiveness of the proposed methods.

Modeling and control of nonlinear systems using novel fuzzy wavelet networks: The output adaptive control approach

This paper proposes an observer based self-structuring robust adaptive fuzzy wave-net (FWN) controller for a class of nonlinear uncertain multi-input multi-output systems. The control signal is comprised of two parts. The first part arises from an adaptive fuzzy wave-net based controller that approximates the system structural uncertainties. The second part comes from a robust H ∞ based controller that is used to attenuate the effect of function approximation error and disturbance. Moreover, a new self structuring algorithm is proposed to determine the location of basis functions. Simulation results are provided for a two DOF robot to show the effectiveness of the proposed method.

Neural Network Control of Resistive Wall Modes in Tokamaks

A neural network (NN) implementation of an adaptive optimal stochastic output feedback control is developed to stabilize the resistive wall mode (RWM), a critically important instability in fusion machines like tokamaks. The design of an adaptive optimal stochastic output feedback control was discussed and reported earlier by Sun, Sen, and Longman. The system dynamics is experimentally determined via the extended least square method with an exponential forgetting factor and covariance resetting. The optimal output feedback controller is redesigned periodically online based on the system identification. The output measurements and past control inputs are used to construct new control inputs. These are achieved by an architecture of NNs consisting of a pool of sequentially linked Hopfield networks and implemented in hardware with digital NN processors made by the Accurate Automation Corporation. The simulations have shown that the NN adaptive output controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of the inverse of the nonlinear growth rate, which is the time scale of the development of the possibly dangerous levels of fluctuations. This stabilization is similar to that of the simulation with a C++ implementation. It is expected that significant gains can be achieved for the systems of a higher order, which are to be found in future fusion devices.

Output feedback strict passivity of discrete-time nonlinear systems and adaptive control system design with a PFC

In this paper, a passivity-based adaptive output feedback control for discrete-time nonlinear systems is considered. Output Feedback Strictly Passive (OFSP) conditions in order to design a stable adaptive output control system will be established. Further, a design scheme of a parallel feedforward compensator (PFC), which is introduced in order to realize an OFSP controlled system, will be provided and an adaptive output feedback control system design scheme with a PFC will be proposed.

Non-linear filter-based adaptive output feedback control for spacecraft formation flying

This paper presents a non-linear filter-based adaptive output control for spacecraft formation flying missions. The study is motivated by the fact that only accurate position measurements are available for some systems, and velocities have to be estimated from those measurements. The proposed adaptive output controller guarantees asymptotic stability of the position and velocity tracking motion, even in the presence of uncertainties and external perturbations. The effectiveness of the proposed controller is verified by numerical simulations.

Adaptive output control with compensation of biased harmonic disturbance

Methods for compensation of biased harmonic disturbances using measurements of the output variable of the plant are developed. An algorithm of adaptive control, which outperforms known analogues in simplicity of implementation and in a number of characteristics is proposed.