Global Stabilization of Uncertain SISO Dynamical Systems Using a Multiple Delayed Partial State Feedback Sliding Mode Control

Abstract: In SISO (single input and single output) system, refers to have only one input and one output. Here only one antenna is used at receiver and transmitter side. SISO are relatively simple to design and implement. They are of low cost and used in wide range of applications. However, SISO systems are poor in performance and deliver low data rate. So we’ll prefer MIMO (multiple input and multiple output) over SISO as it gives better spectral efficiency, improved reliability and good coverage. In MIMO we use multiple antennas at transmitter and receiver side which is known as Spatial Multiplexing(SM) which enhances the data rate. In the paper the performance of spatial combining MIMO system is analysed. Matlab used for simulation.

Using a special determination of the state variables it is noted, that with the faster modes of the conventional reduced order Luenberger observer, a smaller sensitivity to the change of the plant parameters is related. Especially, for the plants with single input and single output (SISO) and no zeros, it is shown that the sufficiently fast observer has a negligible sensitivity to all of the plant parameters. For the SISO plants with some zeros, the number of the plant parameters with respect to which the observer is almost insensitive decreases, if the number of zeros increases. The considerations are extended to the plants with multiple inputs and single output (MISO) and to the MIMO plants. These observations are confirmed by the enclosed results of simulations.

SummaryIn this paper, we develop a new model reference control architecture to effectively suppress system uncertainties and achieve a guaranteed transient and steady‐state system performance. Unlike traditional robust control frameworks, only a parameterization of the system uncertainty given by unknown weights with known conservative bounds is needed to stabilize uncertain dynamical systems with predictable system performance. In addition, the proposed architecture's performance is not dependent on the level of conservatism of the bounds of system uncertainty. Following the same train of thought as adaptive controllers that modify a given reference system to improve system performance, the proposed method is inspired by a recently developed command governor theory that minimizes the effect of system uncertainty by augmenting the input signal of the uncertain dynamical and reference systems. Specifically, a dynamical system, called a command governor, is designed such that its output is used to modify the input of both the controlled uncertain dynamical and reference systems. It is theoretically shown that if the command governor design parameter is judiciously selected, then the controlled system approximates the given original, unmodified reference system. The proposed approach is advantageous over model reference adaptive control approaches because linearity of the uncertain dynamical system is preserved through linear control laws, and hence, the closed‐loop performance is predictable for different command spectrums. Additionally, it is shown that the architecture can be modified for robustness improvements with respect to high frequency content due to, for example, measurement noise. Modifications can also be made in order to accommodate actuator dynamics and retain closed‐loop stability and predictable performance. The main contribution of this paper is the rigorous analysis of the stability and performance of a system utilizing the command governor framework. A numerical example is provided to illustrate the effectiveness of the proposed architecture. Copyright © 2015 John Wiley & Sons, Ltd.

In this paper, we consider the problem of designing sliding mode control for a class of uncertain systems with mismatched uncertainties and disturbances simultaneously. Firstly, a sufficient condition is derived to guarantee the global exponential stability of the reduced-order system for all allowable uncertainties and disturbances. Secondly, a state feedback sliding mode control is constructed such that the prescribed system can be driven to the switching surface in finite time, stay on it thereafter and exponentially converge to zero.

The synthesis of mechanisms has an important effect in the product development. A mechanism has two basic kinds of functions, i.e. to transform motion and to transform force. However, current methods always focus on either motion synthesis or force synthesis. The paper proposed a dynamic programming-based synthesis of multi-input or multi-output mechanisms with the simultaneous consideration of motion and force transmission. A general function model is proposed with a result of function matrix of mechanisms. After the solving process of single input and single output (SISO) system using dynamic programming algorithm is proposed, the single input and multiple outputs (SIMO) system, and the multiple inputs and single output system (MISO) are also discussed in detail, together with design evaluation. The synthesis of mechanisms for jacking up system in offshore platform is taken as an example, which demonstrates that the methodology is helpful to produce valuable mechanisms.

As the evolution of the 3G standards, multiple input and multiple output (MIMO) has been adopted to enhance the performance of 3G systems for the potential of beamforming, spatial multiplexing or spatial diversity. So far, no MIMO scheme has been adopted for time division-synchronous code division multiple access (TD-SCDMA). In this paper, 2times8 MIMO eigen beamforming is proposed to improve the performance of TD-SCDMA. As size limited, the antennas at the UE or Node B are correlated, only one eigen mode of the spatial correlation matrix is found to be useful, and only the beamforming gain and spatial diversity gain can be obtained efficiently. The simulation results of high speed uplink packet access (HSUPA) in the fixed reference channel show that, compared to single input and multiple output (SIMO) 1times8, 3 dB performance gain can be obtained by MIMO 2times8 eigen beamforming; while compared to that of single input and single output (SISO), the performance gain is 8-3 dB

Design, implementation, and testing of a single axis levitation system for the suspension of a platform

This study is devoted to design of the fault estimation adaptive observer. Initial observer is modified with correction filter in order to improve robustness against external disturbance with known spectral structure. Computation of correctors parameters is based on special spectral algorithm of SISO (Single Input and Single Output) H2 optimisation in frequency domain. Novel algorithm is proposed for practical implementation. Its effectiveness is demonstrated with example of successive additive fault estimation during marine ship yaw motion process.

During the past three decades, evolutionary computing techniques have grown manifold in tackling all sorts of optimization problems. Genetic algorithm (GA) is one of the most popular EAs because it is easy to implement and is conducive for noisy environment. Similarly, amongst several swarm intelligence techniques, bacterial foraging optimization (BFO) is the recent popular algorithm being used for many practical applications. Depending on the complexity of the problem concerned, there is need for hybridized techniques which help in balancing exploration and exploitation capability over the search space. Many hybridized techniques have been developed recently to tackle such problems. This paper proposes a hybridization of GA and BFO to solve a real-life unconstrained electrical engineering problem. This unconstrained optimization problem is a model order reduction (MOR) problem of linear time invariant continuous single input and single output (SISO) system.

This study proposes a stripe artifact removal method based on robust principal component analysis (RPCA) for millimeter wave (MW) automotive radar images. With the development of MW radar detection technology, there is a demand for installing obstacle detectors on vehicular for safety. From this background, the authors developed squint-mode synthetic aperture radar (SAR) with MW (MW-SAR) as a high-resolution imaging technique. For synthesizing radar images, a back-projection algorithm (BPA) is adopted because of its real-time processing nature with high accuracy. However, SAR images obtained with Single Input and Single Output (SISO) systems are prone to be contaminated by a stripe-shaped artifact and can affect to the obstacle detection performance. Thus, to reduce the structured noise, this paper proposes successive RPCA on the assumption that the stripe artifacts and obstacle reflection are low-rank and sparse, respectively. As a solver, the alternating direction method of multipliers (ADMM) is adopted. The main contribution of this work is to initialize the ADMM state by taking account of the similarity of low-rank components between adjacent segments. Through simulations with experimental data, the significance of the proposed method is verified.

In this paper an attempt has made for stable suspension of a cylindrical rod under two electromagnets controlling different degrees of freedom movement. The two actuators are controlled independently through two identical controllers and the stable levitation of the rod is achieved through single input and single output (SISO) control of each air-gap corner. The focus is on to design and development of controller unit for two actuators. The proposed single switch based power circuit simplifies the overall hardware and it can be extended to any number of magnet-coil. A cascade lead-lag compensation control scheme utilizing inner current loop and outer position loop has been designed and implemented for stabilization of such highly unstable and strongly non-linear system. The prototype has been successfully tested and stable levitation was demonstrated at the desired operating gap.

Developing a virtual physical system for vortex-induced vibration studies of a bluff body

Fuzzy sliding mode controller design for uncertain time-delayed systems with nonlinear input

In this paper, a nonlinear robust output feedback control is proposed for a class of autonomous underwater vehicles. In specific, we consider the nonlinear mathematical model of a heavy-weight torpedo and design a sliding mode controller to achieve robust stabilization of the closed-loop system in the presence of environmental disturbances and parametric uncertainties. Lyapunovs method is used to present the closed-loop stability analysis of the system. Then, the state feedback sliding mode control law is extended to an output feedback control design using a fourth order observer. It is highlighted that the performance of the state feedback control is recovered arbitrarily fast by the proposed output feedback controller in the presence of parametric uncertainties and environmental disturbances. Finally, the performance of the proposed control design is shown using simulation.

Two state feedback sliding mode control schemes are developed for position control for brushless DC motor drives. The first controller design achieves the desired swiftness of response. In addition to swiftness, the second controller drastically reduces system’s chattering by adding the guaranteed cost constraint. The proposed controller consists of two parts, linear and non-linear. Linear matrix inequalities (LMIs) optimisation is used to design the linear part that achieves the desired dynamic performance: it is robust against system uncertainties, and is based on a new sufficient condition for the existence problem; the non-linear part is created to guarantee that the sliding surface is attained. System uncertainty due to changes in drive’s load inertia is represented with norm- bounded structure. The main advantages of this technique are that: the LMI algorithm includes an optimal part to preclude high control efforts, and the control burden is heavily placed on the linear part to improve the chattering problem of the conventional sliding mode control.