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In underwater vehicles controlled by thrusters and fins, effect of the AUV depth control could be seriously affected because of dead zone nonlinearity in steering gear transmission system. This paper takes a certain AUV as an example. In this paper, a nonlinear pid controller is desired in considering of the actuator being saturated; response speed of the actuator is improved through tracking differentiator;...
This paper studies the system identification, modeling and precision motion control of coreless linear motor drive stage which offers several advantages over its rotary counterparts in many applications requiring linear motion by eliminating mechanical transmission mechanisms. System identification is first carried out to capture the system dynamics characteristics. And with a precision motion control...
Two memoryless adaptive observers are proposed for systems with unknown time-delays and nonlinearities, in which time-delays are not used in the observer. Using high order neural networks (HONN), the precise system model, the Lipschitz, linear-in-parameter or norm-bounded assumptions of nonlinear functions are not needed. A robust term based on the matching condition is introduced in the first observer,...
Theoretically, if the inverse transfer function of the plant is known, feedforward control can achieve zero error between the reference and the output. The main aim of this paper is to design a simple feedforward model and to compensate for the errors brought about by a change in the cogging torque and current measurement inaccuracies. The reference position, speed and acceleration have been designed...
The tracking control problem of muscular vessel systems with dynamic uncertainties and unknown parameters is studied. The unknown system parameters are adaptively identified, and the exogenous disturbance is attenuated by Nussbaum-type functions based on the backstepping methods. The derived adaptive robust controller guarantees that the closed-loop system is globally and uniformly bounded, and the...
This paper presents one implementation of an ILC (iterative learning control) algorithm in motion-focused production control systems. The implementation is an enhancement, but not a replacement of PID tuning. It is able to improve the system performance in terms of following error without re-tuning PID parameters when the operation conditions, such as mechanical device, load, and motion profile, change...
In this paper we report some results of a research project aimed at deriving high-performance, adaptive control algorithms for electronic expansion valves (EEVs) to be used in finned-coiled, dry-expansion evaporators for refrigeration systems. The approach we use in the design is that of virtual prototyping, with the aim of developing a software environment that can be used for controller design,...
This paper develops an adaptive controller for (wireless) networked control systems by combining delay estimation and a jitter margin based PID controller tuning. A control system with wireless measurement is assumed, where the network induces delay jitter. Two delay jitter estimation algorithms are developed, with a method for selecting only valid delay estimates. The delay jitter adaptive PID controller...
A method is presented for the robust control of a disassembly system that undergoes process plan variations due to heterogeneity of demands and product conditions. Two colored timed Petri net (CTPN) models is proposed and extended for the hierarchical modeling of both the system architecture and disassembly plans corresponding to the products to be processed. To address the high levels of uncertainty...
This paper presents an adaptive fuzzy controller for the robust backstepping control of a class of uncertain nonlinear systems in pure-feedback form. The proposed approach incorporates the Nussbaum gain function (NGF) and the dynamic surface control (DSC) into the existing adaptive fuzzy control scheme. The major features of the proposed method are that: 1) the two problems, control directions and...
Numerous physical processes are modeled by partial differential equations and are often instrumented with boundary actuators and sensors. A major new effort has been underway in recent years to develop constructive designs of boundary control laws for unstable PDE systems. This development draws upon the ideas of "backstepping" synthesis for nonlinear ODEs from the 1990s and is an infinite-dimensional,...
We consider the adaptive control problem for a class of SISO unknown nonlinear systems in the presence of additive input disturbances, with guaranteed prescribed performance. By prescribed performance we mean that the tracking error should converge to an arbitrarily predefined small residual set, with convergence rate no less than a prespecified value, exhibiting a maximum overshoot less than a sufficiently...
Robust output-feedback simplified adaptive control model following with uncertainties and disturbances is considered. Sufficient conditions for closed-loop stability, model following performance and prescribed Hinfin disturbance attenuation level are introduced, under an almost-strictly-positive-realness requirement on the plant. A numerical example, taken from the field of flight control, demonstrates...
This paper presents a direct adaptive fuzzy control scheme for a class of uncertain single-input single-output nonlinear systems subject to input amplitude and rate saturation constraints. The fuzzy controller is designed to mimic an ideal controller which is assumed guarantying the control objective. The free parameters of the fuzzy controller are adjusted by an adaptive law which prevents the presence...
This paper compares two different methods applied to adaptive control of a real multivariable laboratory system of three interconnected tanks. In first case, a controller based on polynomial methods was used. The second method is based on model predictive control (MPC) approach. Both methods are based on a same model of the controlled process. Both controllers were realized as self - tuning controllers...
This paper recapitulates the adaptive (time- varying) control strategy funnel-control (FC) and introduces its direct derivative error reference control (ERC) with specially designed Funnel boundaries and auxiliary reference. Both controller designs are comparatively applied to a nonlinear two-mass flexible servo system for speed control. ERC (as derivative of FC) is based on the high-gain controllability...
This paper presents a new approach for on-line identification of an exact affine model for single-input, single- output (SISO) processes with nonlinear and time-varying behaviors. For this purpose, a modified growing and pruning algorithm for radial basis function (MGAP-RBF) neural network is used for affine modeling of the SISO nonlinear and time-varying processes. The extended Kalman filter (EKF)...
An adaptive (time-varying) MIMO/SISO control strategy - funnel-control - for position control of nonlinear, coupled (rigid) robotic systems is presented and its applicability in robotics introductory shown. The concept is based on the high-gain controllability of minimum-phase systems with relative degree one and known high-frequency gain. The approach allows prescribed transient behavior without...
The paper presents an adaptive system identification and control application using a digital signal processor (DSP) from Texas Instruments (TI). The system to be modelled is an automotive alternator. Experimental application illustrates the effectiveness and the simplicity of the proposed method. The application runs on a TMS320F2812 DSP. Once the desired functionality has been captured and simulated,...
This paper deals with intelligent controller design using artificial neural networks (ANN) in the role of feedback controllers. Neural controllers are built up and trained as inverse neural process models. Their performance and robustness are, gradually, improved and augmented by introducing, first, an adaptive simple integrator and, then, a controller with fuzzy integrator part. The proposed ANN...
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