Several Single-input Single-output Research Articles

Comparing Different Resonant Control Approaches for Torque Ripple Minimisation in Electric Machines

Electric machines are highly efficient and highly controllable actuators, but they do still suffer from a number of imperfections. One of them is torque ripple, which introduces high frequency harmonics into the motion. One (cost- and performance-neutral) countermeasure is to apply control that counters the torque ripple. This paper compares several single-input single-output (SISO) control approaches for feedback control of torque ripple of a Permanent Magnet Synchronous Machine (PMSM). The baseline is PI (proportional-integral) control, which does not suppress torque ripple, and the most popular control approach is proportional-integral resonant (PIR) control. Both are compared to an advanced PIR controller (PIRA), frequency modulation, a mixed sensitivity design, and an iterative learning controller (ILC). The analysis demonstrates that PIR control, mixed sensitivity state feedback, and the modulating controller achieve identical behaviour. The choice between these three options is therefore dependent on preferences for the design methodology, or on implementation factors. The PIRA and the ILC on the other hand show more sophisticated behaviour that may be advantageous for certain applications, at the expense of higher complexity.

A Low-Complexity Modulation Classification Algorithm for MIMO–OSTBC System

In this paper, a low-complexity modulation classification algorithm is proposed for the multiple-input multiple-output orthogonal space---time block code (MIMO---OSTBC) system. First, MIMO---OSTBC system is decoupled into several single-input single- output (SISO) systems by utilizing the orthogonal property of OSTBC. Then, these SISO systems are grouped into several two-input two- output systems. Finally, a maximum likelihood- based approach is used to classify the modulation. Both the cases of perfect and unknown channel state information (CSI) are considered. Simulations show that the proposed algorithm exhibits significantly lower complexity than conventional algorithm in both cases. Meanwhile, it provides better performance than conventional algorithm in the case of unknown CSI.

Identification of MISO Systems Using Periodic Inputs and Its Application to Dual-Stage Hard Disk Drives

In this paper, we address identification of a class of multi-input single-output (MISO) linear time-invariant (LTI) discrete-time systems, where the MISO system is composed of several single-input single-output (SISO) LTI systems and only the sum of the output of each SISO system can be measured. By exciting one SISO system and employing periodic inputs to the remaining SISO systems, we decompose the MISO system into the excited SISO system where its input and output can be calculated from the measured data. As such, the original parameters for each SISO system can be estimated using the well-established identification techniques. The proposed method using periodic inputs is also extended to identification beyond the Nyquist frequency. Both simulation and experimental results on identification of actuators in the dual-stage hard disk drive are carried out to demonstrate the efficacy of the proposed approach.

Fuzzy neural network-based robust adaptive control for dynamic positioning of underwater vehicles with input dead-zone

This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural Network (DRFNN) with feedback loops is employed to approximate the unknown portion of the controller, which can greatly reduce the number of neural network inputs. A fuzzy logic dead-zone compensator is designed to cope with the unknown dead-zone characteristics of actuators. The upper bounds of the approximation errors and disturbances of the network, which are often used in existing works, are not necessary in this paper due to the presentation of a special robust compensator. Stability analysis is conducted according to the Lyapunov theorem, and the tracking error is proved to converge to zero. Simulation results indicate that the proposed controller demonstrates good performance.

Energy Efficient MIMO Relay Transmissions via Joint Power Allocations

The energy efficient joint source-relay power allocation problem is studied for the multi-input multi-output (MIMO) amplify-and-forward two-hop relaying system, in which the objective of the optimization is the number of the bits per second per hertz per Joule with the guarantee of the minimum spectral efficiency (SE). By assuming perfect channel state information at the transmitter, the MIMO channel is divided into several single-input single-output (SISO) subchannels via singular value decomposition (SVD). The problem is first established as an optimization subject to the minimum SE constraint, in which it is observed that both of the cost function and the constraint are not convex. By employing the high signal-to-noise ratio (SNR) approximation, the problem becomes suddenly a pseudo-convex optimization problem. Yet, the difficulty comes from solving the final Lagrangian equation, which is tackled by our proposed relaxation method according to the Jensen inequality. Finally, the analytical expression is derived for the energy efficient power allocations of the multiple antennas at the source and at the relay. Simulations demonstrate the effectiveness of the proposed method.

Feedback Approach for Reproduction of Field Measurements on a Hydraulic Four Poster

The study of vibrations in agriculture is performed to assess the efficiency of machinery, lifetime of components, drivers’ comfort, damage of crop during harvest and transport. An important source of vibrations is the soil. Owing to the stochastic character and visco-elastic behaviour of the soil, it is very difficult to create repeatable testing conditions. Experiments on vibration test rigs, also called shakers, in combination with time waveform replication (TWR) can solve this problem. The objective of TWR is to determine the inputs to the shakers in order to obtain the same sensor readings as during the field experiments. The classical TWR method consists of an iterative procedure that can be time consuming. This paper presents a feedback approach, thereby reducing the number of iterations. As in general, several sensor signals need to be reproduced, a multiple-input multiple-output (MIMO) controller needs to be designed, which is often a time consuming and difficult process. A methodology based on static decoupling is introduced such that the MIMO controller design reduces to the synthesis of several single-input, single-output (SISO) controllers. Experiments on a tractor indicate that with the present procedure, compared to the classical TWR procedure, the number of iterations can be reduced and a better accuracy can be achieved.