Sliding-mode neuro-controller for uncertain systems

In this paper, a method that allows for the merger of the good features of sliding-mode control and neural network (NN) design is presented. Design is performed by applying an NN to minimize the cost function that is selected to depend on the distance from the sliding-mode manifold, thus providing that the NN controller enforces sliding-mode motion in a closed-loop system. It has been proven that the selected cost function has no local minima in controller parameter space, so under certain conditions, selection of the NN weights guarantees that the global minimum is reached, and then the sliding-mode conditions are satisfied; thus, closed-loop motion is robust against parameter changes and disturbances. For controller design, the system states and the nominal value of the control input matrix are used. The design for both multiple-input-multiple-output and single-input-single-output systems is discussed. Due to the structure of the (M)ADALINE network used in control calculation, the proposed algorithm can also be interpreted as a sliding-mode-based control parameter adaptation scheme. The controller performance is verified by experimental results

Neuro-sliding mode controllers for systems with uncertainties

A Neuro - Sliding Mode Controller was designed for systems that have uncertainties like unknown external disturbances and unknown system parameters. First, the controller was designed for single input single output (SISO) systems and then it was generalized for a certain class of multi input multi output systems. Stability proof was given using Lyapunov Stability Criteria and finally, the theory was supported by simulation and experimental results. The Neuro - Sliding Mode Controller proposed in this thesis consists of a one layered neural network whose activation functions are linear. The main working principle of the controller is minimizing a cost function which is determined from the requirements of the Lyapunov Stability Criteria and Sliding Mode Control Theory. The major contribution of this work is that, different from the similar works in the field, the stability of the overall control system was shown by analyzing the properties of the cost function introduced to the neural network for minimization. Two different experimental setups were used for SISO and MEVIO cases respectively. For the SISO case, the position of an electrical motor that actuates a linear servo - drive was controlled. For the MEVIO case, a system consisting of two piezoelectric actuators connected to each other via a load cell, which was used for force measurement, was used. In this system, the position of one actuator and the internal force created were controlled simultaneously. Both experiments were successful and supported the theory

Adaptive nonlinear hierarchical control of a quad tilt-wing UAV

Position control of a quad tilt-wing UAV via a nonlinear hierarchical adaptive control approach is presented. The hierarchy consists of two levels. In the upper level, a model reference adaptive controller creates virtual control commands so as to make the UAV follow a given desired trajectory. The virtual control inputs are then converted to desired attitude angle references which are fed to the lower level attitude controller. Lower level controller is a nonlinear adaptive controller. The overall controller is developed for the full nonlinear dynamics of the tilt-wing UAV and thus no linearization is required. In addition, since the approach is adaptive, uncertainties in the UAV dynamics can be handled. Performance of the controller is presented via simulation results

Trajectory control of a quadrotor using a control allocation approach

A quadrotor is an underactuated unmanned aerial vehicle with four inputs to control the dynamics. Trajectory control of a quadrotor is a challenging task and usually tackled in a hierarchical framework where desired/reference attitude angles are analytically determined from the desired command signals, i.e. virtual controls, that control the positional dynamics of the quadrotor and the desired yaw angle is set to some constant value. Although this method is relatively straightforward, it may produce large and nonsmooth reference angles which must be saturated and low-pass filtered. In this work, we show that the determination of desired attitude angles from virtual controls can be viewed as a control allocation problem and it can be solved numerically using nonlinear optimization where certain magnitude and rate constraints can be imposed on the desired attitude angles and the yaw angle need not be constant. Simulation results for both analytical and numerical methods have been presented and compared. Results for constrained optimization show that the flight performance is quite satisfactory

Uric acid and high sensitive C-reactive protein are associated with subclinical thoracic aortic atherosclerosis

AbstractBackground and purposeThe detection of atherosclerotic lesions in the aorta by transesophageal echocardiography (TEE) is a marker of diffuse atherosclerotic disease. Hyperuricemia is a well-recognized risk factor for cardiovascular diseases. However, no data are available concerning the relationship between serum uric acid (UA) and subclinical thoracic aortic atherosclerosis. We aimed to investigate the association between thoracic aortic atherosclerosis and serum UA level.MethodsWe studied 181 patients (mean age 46.3±8 years) who underwent TEE for various indications. Four different grades were determined according to intima–media thickness (IMT) of thoracic aorta. UA and other biochemical markers were measured with an automated chemistry analyzer.ResultsTEE evaluation characterized thoracic aortic intimal morphology as Grade 1 in 69 patients, Grade 2 in 52 patients, Grade 3 in 31 patients, and Grade 4 in 29 patients. The highest UA level was observed in patients with Grade 4 IMT when compared with Grade 1 and 2 IMT groups (p<0.001 and p=0.014, respectively). UA levels in patients with Grade 3 and Grade 2 IMT were also higher than patients with Grade 1 IMT group (p<0.001, for all). In multiple linear regression analysis, IMT was independently associated with UA level (β=0.350, p<0.001), age (β=0.219, p=0.001), total cholesterol (β=−0.212, p=0.031), low-density lipoprotein cholesterol (β=0.350, p=0.001), and high sensitivity C-reactive protein (hsCRP) levels (β=0.148, p=0.014).ConclusionUric acid and hsCRP levels are independently and positively associated with subclinical thoracic atherosclerosis

Neuro sliding mode controller for MIMO systems

In this paper, the previously proposed neuro-sliding mode controller for SISO systems by the authors is modified for MIMO case. The structure benefits from the power of sliding mode control and nonlinear function approximation ability of the neural networks. The controller is a two layer feed-forward neural network and weight updates are done using backpropagation algorithm. The error function that is introduced to the neural network is such that the states of the system are restricted to belong to a certain manifold in state space. Different from the works done until now, in this work the aim is not calculating the equivalent control but instead finding the control input by just minimizing a certain error function. Simulation results demonstrate the performance of the controller

Neuro sliding mode control of timing Belt Servo System

In this paper, the employment of neural networks with sliding mode control in the control of a linear drive with flexible transmission element is described. Linear drives with flexible transmission elements are cheaper and also more efficient than the ones with rigid transmissions like power screw systems. Hence, these devices play an important role in the industry. A neuro-sliding mode controller cascaded with a discrete sliding mode controller is used to control the system. Neuro-sliding mode controller is used in the outer loop and produces reference for the discrete sliding mode controller which serves as a force controller, in the inner loop. The control signal of the neuro-controller is obtained by minimizing an error function which is derived from Lyapunov stability analysis. The controller performance is tested with different loading conditions and different friction torques and the results are presented

Nonlinear hierarchical control of a quad tilt-wing UAV: an adaptive control approach

In this paper, a nonlinear hierarchical adaptive control framework is proposed for the control of a quad tilt-wing unmanned aerial vehicle (UAV). An outer loop model reference adaptive controller with robustifying terms creates required forces to be able to move the UAV on a reference trajectory, and an inner loop nonlinear adaptive controller realizes the required attitude angles to achieve these forces. A rigorous stability analysis is provided showing the boundedness of all the signals in this cascaded controller structure. The development and the stability analysis of the controller do not use any linearizations and use the full nonlinear UAV dynamics. The controller is implemented on a high-fidelity nonlinear tilt-wing quadrotor model in the presence of uncertainties, wind disturbances, and measurement noise as well as actuator and structural failures. In this work, in addition to earlier modeling studies, the effect of wing-angle variations, actuator failures, and structural failures and their effect on the center of gravity of the UAV are rigorously and systematically investigated and reflected in the model. Simulation results showing the performance of the proposed controller and a comparison with the fixed controller used in earlier studies are presented in the paper

Is routine ureteral stenting really necessary after retrograde intrarenal surgery?

WOS: 000440260100015PubMed: 25847901Objectives: To investigate the situations in which ureteral double-J stent should be used after retrograde intrarenal surgery (RIRS). Patients and Methods: Patients with no ureteral double-J stent after RIRS constituted Group 1, and those with double-J stent after RIRS constituted Group 2. Patients' age and gender, renal stone characteristics (location and dimension), stone-free status, VAS score 8 hours after surgery, post-procedural renal colic attacks, length of hospitalization, requirement for re-hospitalization, time to rehospitalization and secondary procedure requirements were analyzed. Results: RIRS was performed on 162 renal units. Double-J stent was used in 121 (74.6%) of these after RIRS, but not in the other 41 (25.4%). At radiological monitoring at the first month postoperatively after RIRS, complete stone-free status was determined in 122 (75.3%) renal units, while residual stone was present in 40 (24.6%). No significant differences were observed between the groups in terms of duration of fluoroscopy (p = 0.142), operation (p = 0.108) or hospitalization times (p = 0.798). VAS values determined routinely on the evening of surgery were significantly higher in Group 1 than in Group 2 (p = 0.025). Twenty-eight (17.2%) presentations were made to the emergency clinic due to renal colic within 1 month after surgery. Double-J catheter was present in 24 (85.7%) of these patients. Conclusions: Routine double-J stent insertion after RIRS is not essential since it increases costs, morbidity and operation time