Discrete Control Scheme Research Articles

Dynamic Coverage Control in a Time-Varying Environment Using Bayesian Prediction

This paper investigates the dynamic coverage control problem for a group of agents with unknown density function. A cost function, depending on a certain metric and the density function, is defined to describe the performance of coverage network. Since the optimal deployment of agents is closely depending on the density function, we employ the Bayesian prediction approaches to estimate the density function. Moreover, a novel coverage-control-customized algorithm is proposed to acquire the Bayesian parameters. The merits of this Bayesian-based spatial estimation algorithm are the consideration of measurement noise and the capability of dealing time-varying density function. However, the estimated density function from Bayesian framework follows normal distribution, which leads the cost function to a stochastic process. To deal with this type of cost function, a discrete control scheme is proposed to steer the agents approaching to a near-optimal deployment. The mean-square stability of the proposed coverage system is further analyzed. Finally, numerical simulations are provided to verify the effectiveness of the proposed approaches.

Frequency and time domain characteristics of digital control of electric vehicle in-wheel drives

Abstract In-wheel electric drives are promising as actuators in active safety systems of electric and hybrid vehicles. This new function requires dedicated control algorithms, making it essential to deliver models that reflect better the wheel-torque control dynamics of electric drives. The timing of digital control events, whose importance is stressed in current research, still lacks an analytical description allowing for modeling its influence on control system dynamics. In this paper, authors investigate and compare approaches to the analog and discrete analytical modeling of torque control loop in digitally controlled electric drive. Five different analytical models of stator current torque component control are compared to judge their accuracy in representing drive control dynamics related to the timing of digital control events. The Bode characteristics and stepresponse characteristics of the analytical models are then compared with those of a reference model for three commonly used cases of motor discrete control schemes. Finally, the applicability of the presented models is discussed.

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control

A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

Influence sampling of trailing variables of dynamical systems

AbstractFor dealing with dynamical instability in predictions, numerical models should be provided with accurate initial values on the attractor of the dynamical system they generate. A discrete control scheme is presented to this end for trailing variables of an evolutive system of ordinary differential equations. The Influence Sampling (IS) scheme adapts sample values of the trailing variables to input values of the determining variables in the attractor. The optimal IS scheme has affordable cost for large systems. In discrete data assimilation runs conducted with the Lorenz 1963 equations and a nonautonomous perturbation of the Lorenz equations whose dynamics shows on-off intermittency the optimal IS was compared to the straightforward insertion method and the Ensemble Kalman Filter (EnKF). With these unstable systems the optimal IS increases by one order of magnitude the maximum spacing between insertion times that the insertion method can handle and performs comparably to the EnKF when the EnKF converges. While the EnKF converges for sample sizes greater than or equal to 10, the optimal IS scheme does so fromsample size 1. This occurs because the optimal IS scheme stabilizes the individual paths of the Lorenz 1963 equations within data assimilation processes.

Energy-saving control strategies for a ferromagnetic shape memory alloy based actuator

Two different strategies are presented for the control of a positioning actuator based on a ferromagnetic shape memory alloy (FSMA). The actuator consists of two orthogonal pairs of coils that generate a pulsed magnetic field when a bank of capacitors is discharged through one of the coil pairs. The FSMA element is located between the coils and expands when a field perpendicular to the crystal's long axis is applied, and contracts in response to a parallel one. In each case, the deformation of the element remains until a driving force in the opposite direction is applied, therefore operating in a “set-and-forget” mode. The current experimental set-up is capable of achieving submicrometer resolutions. Two discrete control strategies are proposed and compared based on their ability to achieve a position with a given precision and transient behaviour. Taking into account that the energy consumption of the actuator is directly related to the number of control actions, two control strategies aimed to minimize such consumption by reducing the number of actions are presented and their experimental performance described. The first of the proposed strategies has two control modules, one for each pair of coils, while the second approach is based on an event-based PI control algorithm.

Optimized Discrete Control Law for Quadrotor Stabilization: Experimental Results

This paper deals with the real-time stabilization of a Quadrotor mini helicopter applying a discrete optimal control. A discrete control strategy is better adapted to be executed in a micro-controller, therefore better results are expected with respect to continuous case. Furthermore, the optimal control law allows to helicopter to save energy and then increase its time of flight. The discrete optimal control law is synthesized considering an infinite horizon together with an exact linearization of the nonlinear dynamics of flying vehicle. At the end of this procedure the optimal control law obtained through an exact linearization is simple and easier to tune compared to the optimal strategy where the exact linearization is not performed. Taking into account the obtained experimental results, the proposed control technique produces an appropriate stabilization of the mini UAV.

Discrete Sliding Mode control of small UAS in tight formation flight under information constraints

This paper is concerned with a new control strategy based on discrete sliding mode control of small Unmanned Aerial Systems (UAS) in tight formation flight under information constraints. A discrete robust control strategy based on the sliding mode approach and a leader-follower scheme is proposed to achieve the desired flight performances while assuming realistic information constraints. A predictive reaching law is compared to a linear reaching law. This predictive discrete sliding mode control (PDSMC) strategy allows taking into account hard actuator constraints by solving an optimization problem at each time step.Also, this paper presents a meaningful study and comparison of the two discrete sliding mode control designs and time sampling continuous sliding mode control (TSCSMC). Here, the comparison focuses on the effect of discrete sampling on the control error analytically and in simulation. Effects on mesh stability are evaluated in simulation. Simulation results of a flight scenario with two different sampling frequencies demonstrate the efficiency of the proposed control strategy and show clearly the effect of the sampling time on the formation flight performance of the UAS obtained by the considered control strategies.

Nonlinear optimal suppression of vortex shedding from a circular cylinder

This study is focused on two- and three-dimensional incompressible flow past a circular cylinder for Reynolds number $\mathit{Re}\leqslant 1000$. To gain insight into the mechanisms underlying the suppression of unsteadiness for this flow we determine the nonlinear optimal open-loop control driven by surface-normal wall transpiration. The spanwise-constant wall transpiration is allowed to oscillate in time, although steady forcing is determined to be most effective. At low levels of control cost, defined as the square integration of the control, the sensitivity of unsteadiness with respect to wall transpiration is a good approximation of the optimal control. The distribution of this sensitivity suggests that the optimal control at small magnitude is achieved by applying suction upstream of the upper and lower separation points and blowing at the trailing edge. At high levels of wall transpiration, the assumptions underlying the linearized sensitivity calculation become invalid since the base flow is eventually altered by the size of the control forcing. The large-magnitude optimal control is observed to spread downstream of the separation point and draw the shear layer separation towards the rear of the cylinder through suction, while blowing along the centreline eliminates the recirculation bubble in the wake. We further demonstrate that it is possible to completely suppress vortex shedding in two- and three-dimensional flow past a circular cylinder up to $\mathit{Re}=1000$, accompanied by 70 % drag reduction when a nonlinear optimal control of moderate magnitude (with root-mean-square value 8 % of the free-stream velocity) is applied. This is confirmed through linearized stability analysis about the steady-state solution when the nonlinear optimal wall transpiration is applied. While continuously distributed wall transpiration is not physically realizable, the study highlights localized regions where discrete control strategies could be further developed. It also highlights the appropriate range of application of linear and nonlinear optimal control to this type of flow problem.

Effects of wave excitation force prediction deviations on the discrete control performance of an oscillating wave energy converter

Oscillating-body converters are widely used in offshore engineering, to capture wave energies. In such a case, discrete control including both latching and declutching controls is adopted to improve the power capture performance of oscillating wave energy converters (WECs). A reliable prediction of wave excitation forces on the WEC is essential for the discrete control strategy. In this study, a time domain model is developed to calculate the hydrodynamic responses of a hemispherical oscillating WEC with discrete control in regular waves. A state space model is used to deal with the convolution term in the time domain equation, taking into account the memory effects of wave surface. Based on the developed numerical model, the effects of prediction deviations, such as the amplitude and phase of wave excitation force, have been studied. It is observed that the amplitude prediction deviation exhibits very few effects on the control performance. However, the phase prediction deviation performances significantly influence on the control performance. In some conditions, the phase prediction deviation will reduce the efficiency of the discrete control.

Servomechanism for periodic reference input: Discrete wavelet transform-based repetitive controller

The presented work explored the possibility of developing a discrete wavelet transform-based repetitive control (DWTRC) strategy along with a proportional controller for a liquid level system (LLS) to track a periodic reference signal. The modified DWTRC with a P control system is a type of servo mechanism, effective for periodic reference input. The entire effort derives from two distinct parts. First, the tracking performance and stability measure of the system with inclusion of a repetitive controller (RC) in presence of P controller that has been studied and compared with conventional P and PI controllers in both time and frequency domains, subjected to periodic command to establish the usefulness of the former. The most obvious disadvantage of the RC with P control is the requirement of large memory for the presence of RC, and the memory requirement linearly increases with both repetition time and sampling frequency. Second, to overcome this difficulty, deployment of the discrete wavelet transform (DWT) in the RC loop is done to reduce the problem of memory requirement, and ensures efficient and high-speed computation due to the filtering and data reduction property of DWT. Finally, the effectiveness of DWTRC is validated through saving memory and optimizing the tracking error with variation of the wavelet order and its decomposition level.

Modelling of transient cornering and suspension dynamics, and investigation into the control strategies for an ideal driver in a lap time simulator

Lap time simulation is one of the most powerful tools for evaluating design proposals in motorsport engineering. In particular, transient simulations play an important role as the ultimate and more accurate approach than other static or quasi-steady-state methodologies. In this paper, first, the method to transform the differential equations of a system into a formally linear continuous and then discrete state-space representation, particularised for a seven-degree-of-freedom suspension and a transient cornering model, is proposed. The use of time-variant coefficients in the matrices of the model will allow the non-linear and time-variant characteristics of these systems to be described. Second, in the case of the transient cornering model, this representation is translated into a transfer function in order to apply a discrete control strategy such as a finite-time strategy or a predictive strategy for an adaptive ideal driver. It was found that the calculation methodology described above can be successfully applied with a more than acceptable degree of accuracy according to comparison with the results using other mechanical or numerical software (ADAMS or Simulink). It was also observed that the use of the curvature of the track as a reference in the control closed loop is sufficiently accurate to force the car to follow the target path closely. Furthermore, both predictive control and finite-time control (including integration) provide excellent results with a smooth response of the steering input. Many lap time simulators are language specific; however, the methodology proposed in this paper will run in most programming languages.

Smart Relaying for Selection Combining Based Decode-and-Forward Cooperative Networks

This letter proposes three smart relaying strategies, including power allocation, continuous power control, and discrete power control strategies, to mitigate the error propagation problem for single-relay decode-and-forward cooperative networks using selection combining at the destination. By fully exploiting the channel state information at the relay, these relaying strategies can optimize transmit power so as to minimize the bit error rate of the system, as well as allowing the source and relay nodes to use different modulation levels to improve spectral efficiency. Simulation results demonstrate that the proposed smart relaying strategies can effectively mitigate erroneous relaying and achieve diversity orders close to two.

Validity of Approach to Maximize the ASR of the Order Superiorly Two in Discrete Nonlinear Systems

This paper is, in fact, a proposal of a polynomial approach to the nonlinear systems control by using the concept of linearization by state feedback. In this context, a discretization method is presented. We developed a discrete control scheme based on an approximate feedback linearization method and the reversing trajectory method. The proposed control strategy sits on the methods of widening the stability domains of operating points. Such domains are expanded through the use of the non Lyapunov stability synthesis methods. Additionally, the developed technique is employed for the control of the class of systems with an order higher than two; more precisely, the example of a synchronous generator featured in a strongly nonlinear model.

Robust controller design for discrete unstable non-minimum-phase delayed stochastic processes

Control of unstable non-minimum-phase delayed stochastic processes is a challenging problem. In this work based on the Diophantine equation and using pole-placement technique, a discrete control scheme for such processes has been proposed. Robust stability of the suggested control structure has been shown. Advantages of the proposed scheme over the existing algorithms have been shown through computer simulations. It has been shown that performance of the proposed scheme for handling model mismatch and colored noise is superior to the previous work proposed in the literature.

Hybrid control for high‐penetration distribution grid based on operational mode conversion

For the purpose of developing smart control with a great degree of flexibility to enhance the stability, security and self-healing capability of a high-penetration distribution grid, in this study smart control called a hierarchical hybrid control is proposed based on operational mode conversions of distributed energy resources. Corresponding to the hybrid dynamic behaviours of the system, the hierarchical hybrid control consists of discrete control strategies at the upper level, local continuous controllers at the lower level and their interactions. The upper level discrete control strategies are mainly responsible for switching operational modes so as to enhance security and self-healing capability during significant disturbances. The lower level continuous control aims to regulate dynamic stability of each controlled unit in order to obtain satisfactory performance. The effectiveness of the proposed hybrid control is demonstrated through simulation examples.

Energy Efficient Spectrum Sharing Strategy Selection for Cognitive MIMO Interference Channels

In this paper, we propose a promising discrete game-theoretic framework for distributed energy efficient discrete spectrum sharing strategy selection (i.e., joint discrete power control and multimode precoding strategy selection) with limited feedback for cognitive MIMO interference channels. Given the competitive nature, the secondary users are assumed to be selfish and noncooperative, each of whom attempts to maximize its individual energy efficiency under a minimum data rate constraint and an interference power constraint. A mechanism for shutting down links is proposed to reduce interference and save energy. A payoff function is designed to guarantee the feasibility of the pure strategy Nash equilibrium with no need to know the infeasible strategy profiles (a spectrum sharing strategy profile is said to be feasible if the stated constraints are satisfied; otherwise, the spectrum sharing strategy profile is said to be infeasible, i.e., they may not satisfy the interference power constraint and minimum data rate constraint) in advance. We then investigate the existence and the feasibility of the pure strategy Nash equilibrium, and further devise a pricing-based distributed algorithm for spectrum strategy selection. The proposed algorithm is proved to converge to a feasible pure strategy Nash equilibrium under specific conditions. Moreover, by studying the relationship between our proposed game and the social optimum, we find that the pricing mechanism can result in Pareto improvement and lead to better convergence for the proposed distributed algorithm. Numerical results show that our designed algorithm significantly outperforms the random selection algorithm and the pricing mechanism has a dramatic effect in improving the system performance.

Discrete Composite Control of Piezoelectric Actuators for High-Speed and Precision Scanning

The scanning accuracy of piezoelectric mechanisms over broadband frequencies is limited due to inherent dynamic hysteresis. This phenomenon has been a key bottleneck to the use of piezoelectric mechanisms in fast and precision scanning applications. This paper presents a systematic model identification and composite control strategy without hysteresis measurement for such applications. First, least squares estimation using harmonic signals is applied to achieve the Preisach density function. Next, the hysteresis output is estimated, such that the non-hysteretic dynamics can be identified. The discrete composite control strategy is proposed with a feedforward-feedback structure. The feedforward controller is the primary component designed for the performance. The secondary proportional-integral (PI) feedback controller is employed to suppress disturbances for robustness. Finally, the identification and composite control strategy is implemented with a dSPACE 1104 board for a real piezoelectric actuator setup. The experimental results indicate that adequate scanning performance can be sustained at a rate higher than the first resonant frequency.

Discrete Current Control Strategy of Permanent Magnet Synchronous Motors

A control strategy of permanent magnet synchronous motors (PMSMs), which is different from the traditional vector control (VC) and direct torque control (DTC), is proposed. Firstly, the circular rotating magnetic field is analyzed on the simplified model and discredited into stepping magnetic field. The stepping magnetomotive force will drive the rotor to run as the stepping motor. Secondly, the stator current orientation is used to build the control model instead of rotor flux orientation. Then, the discrete current control strategy is set and adopted in positioning control. Three methods of the strategy are simulated in computer and tested on the experiment platform of PMSM. The control precision is also verified through the experiment.

Hierarchical hybrid control for improving comprehensive performance in smart power system

For the purpose of improving comprehensive performance including stability, security and economic benefit of power system, in this study a two-level hierarchical hybrid control is proposed in a real-time manner. First, a novel hybrid model is founded to clearly explain the hybrid dynamical behaviors of the power systems. On the basis of the model, a hybrid control scheme is designed in an interaction manner between the discrete control strategies at the upper level and the continuous dynamical controls at the lower level. The upper level discrete control strategies are responsible for converting operating modes to guarantee the security during significant disturbances and the economic benefit of overall system. After locating operating modes, the lower level local continuous controllers are responsible for regulating dynamic behavior of each controlled unit to obtain the satisfactory stability performance. The effectiveness of the proposed hybrid control is demonstrated through simulation examples.

Transient control for micro-grid with multiple distributed generations based on hybrid system theory

With the rapid increase in the rate of distributed generation (DG) penetration depth, the issues of improving micro-grid transient become more significant. This paper investigates a two-level hierarchical hybrid control consists of continuous local controller for each DG unit at the first level coordinated by discrete supervisory control strategies at the secondary level for transients performance enhancement of micro-grid with various DG units following pre-planned or accidental events. The discrete supervisory control strategies are established based on information fusion technique by using wide-area measurements (WAMs) in order to switch each DG subsystem into apposite operational mode following large disturbances. The continuous local controller for each DG unit is designed based on multiple Lyapunov stability theory integrating linear matrix inequality (LMI) techniques in order to regulate the set point of each DG subsystem to reach the best performance and acceptable operation indexes. The effectiveness of the proposed hybrid control is demonstrated through simulation examples.