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This paper presents a novel approach to the correction of robot steady state motion error. This approach acquires the motion error information from robot internal encoders and feeds the acquired information to an iterative learning controller (ILC) to compute a compensation variable. It then adds the compensation variable to the original position reference command of the robot to correct the steady state motion error. The proposed approach does not require any external measurement device and any changes to robot’s internal controller, therefore it can be easily implemented and embedded into a robot’s user program. The proposed approach has a nice mathematical property that guarantees its convergence. Simulation and test facility experiments have shown that the proposed approach is effective and can significantly and consistently reduce SMPE (servo motion positional error) to within ±0.05 mm, which is an 82% reduction of SMPE.

This paper proposes a unique coordinated ride-through capability enhancement scheme for Type IV wind generators to counter the impact of symmetrical and asymmetrical voltage swells. A novel protection hardware configuration is utilized to restrict the dc-link overvoltage and undervoltage in the event of voltage swells at the Point of Common Coupling (PCC), which would otherwise damage the converter. Moreover, a reactive power flow management algorithm is implemented to support the grid voltage during the transient event. A supervisory controller is used to control the insertion of the protection hardware and also to regulate the reactive power flow between the generator and grid. It is observed that there is substantial improvement in ride-through performance. A 10-MW Wound Rotor Synchrnous Generator (WRSG) wind farm in MATLAB/Simscape Power Systems is utilized to validate the effectiveness of the scheme. The 10 MW wind farm consists of 5 × 2-MW wind generators.

This paper presents a novel coordinated performance augmentation scheme for Doubly-Fed Induction Generators (DFIG) to improve their response to symmetrical and asymmetrical voltage sags. The augmentation scheme consists of a protection system and a reactive power management strategy. The protection system limits the over current in the Rotor Side Converter (RSC) and keeps the dc-link capacitor voltage within an acceptable range; whereas, the reactive power management supports the grid voltage stability by either injecting or absorbing reactive power depending on the PCC (Point of Common Coupling) voltage. A grid-connected 9-MW DFIG wind farm has been used for simulation in MATLAB/Simscape Power Systems. Simulation results show that the performance of DFIGs improves significantly under the proposed scheme.

This paper provides a novel integrated protection and power management scheme for Doubly-Fed Induction Generators (DFIG) to enhance their performance under voltage sags and swells. Both symmetrical and asymmetrical voltage sags and swells are considered. The protection system limits the overcurrent in the Rotor Side Converter (RSC) and keeps the dc-link voltage within an acceptable range; while, the reactive power management supports the grid by either injecting or absorbing reactive power to reduce the magnitude of voltage sags and swells. It has been found that the performance of DFIGs improves considerably under the proposed scheme. A grid-connected 9-MW DFIG wind farm has been used for simulation in MATLAB/SimPowerSystems.

A novel pitch control design method is proposed for the doubly fed induction generator (DFIG) wind turbine (WT) using linear quadratic regulator (LQR). A seven-order model represents the DFIG WT which is linearized by truncated Taylor series expansion. A systematic approach is adopted to determine the weighting matrices in LQR design for the optimal solution. Simulations have been carried out to compare the performance of the proposed LQR pitch control method against a PI pitch control for small and large disturbances. It is shown that the proposed control method enhances low-voltage ride-through capability and improves system damping under large disturbances.

Oversampled filter banks (FBs) with lattice structure allow fast implementation and guarantee the linear phase and perfect reconstruction property. For such FBs, the synthesis FB is not unique. This nonuniqueness provides extra design freedom for optimal reduction of subband noise required in many applications. However, the existing design methods of synthesis FB for optimal reduction of subband noise cannot guarantee the linear phase and lattice structure property. This paper studies the design of oversampled synthesis FBs with guaranteed lattice structure for optimal reduction of subband noise. Based on a state space parameterization of all synthesis FBs with lattice structure, the explicit formulae are derived to find the optimal solution for noise reduction. Numerical examples are presented to demonstrate the effectiveness of the new design methods obtained.

This paper studies the optimal noise reduction problem for oversampled filter banks (FBs) with perfect reconstruction (PR) constraint. Both the optimal design and worst case design are considered, where the former caters for the noise with known power spectral density (PSD) and the latter for the noise with unknown PSD. State-space based explicit formulae involving only algebraic Riccati equation and matrix manipulations are provided for the general (IIR or FIR) oversampled PR FBs, and the relations between different cases are analyzed and revealed. Extensive numerical examples are provided to illustrate the proposed design methods and to show their effectiveness.

This paper analyzes the performance of discrete linear time varying (LTV) control of discrete linear periodically time varying (LPTV) plants for l2 disturbance rejection. It extends the results of [11-13] for linear periodic controllers to general LTV control of LPTV plants. It is shown that LPTV control provides strictly better control performance than linear strictly time varying control for LPTV plants. The analysis is carried out in frequency domain. This approach provides not only new results on disturbance rejection of LTV control but also some new insight into properties of general LTV systems.

A causal realization of an inverse system can be unstable, and an anti-causal realization is used to deal with this problem to provide a numerically stable procedure to realize the inverse system and compute its input signal. In this paper, we consider the anti-causal realization of the inverse of discrete-time linear periodic systems obtained by an outer-inner factorization approach. It presents an analysis and understanding of the inverse system error caused by different parts of the system components. The analysis shows that the inverse system error due to the mismatching of the system initial state in the anti-causal inverse system is inevitable in practical computations.

Many authors have identified the need to improve the definitions of non-active power under non-sinusoidal conditions. It has also been stated the need for a generalised power theory to provide a simultaneous common base for measurement, compensation, power quality and identification of sources of distortion. A solution is to decompose, as accurately as possible, the total instantaneous power into active and non-active components based on the power system properties. To enable this, the load model must closely represent the actual. This paper presents a new instantaneous power theory that achieves this for the single-phase system. This theory is based on both voltage and current harmonic components. With good knowledge of the time profile of active/non-active power components, an accurate time-domain measurement of the non-active power is achieved. This non-active component can be utilised to achieve optimal compensation, as well as gauge power quality. The theory is evaluated for linear and non-linear loads in the presence of harmonics using case studies. The case studies use single-phase resistive and inductive loads with diodes to create non-linear load as necessary. Evaluations of the results demonstrate good performance of the proposed theory.

This paper proves the validity of a basic feasibility property which makes it possible to extend, to the case of set-point tracking in ANCBI systems under joint positional and incremental input saturations, the approach in [Mosca, E. (2005). Predictive switching supervisory control of persistently disturbed input-saturated plants. Automatica, 41, 55-67] restricted to positional input saturation and the pure regulation problem. An example on the use of the proposed technique is considered.

This paper extends of the horizon-switching predictive control approach, so far restricted to positional input saturation and the pure regulation problem, to the case of set-point tracking. It is proved a basic feasibility property which makes it possible to extend this approach so as to achieve offset-free asymptotic tracking under joint positional and incremental input saturations and constant disturbances. It is also addressed the same problem in the presence of time-varying disturbances. In such a case it is proved that, whenever the system is subject only to incremental input saturations, the goal is achieved with the property of bounded-noise bounded-state l ∞ - stability.

This paper studies the frames corresponding to oversampled filter banks (FBs). For this class of FB frames, we present a state-space parameterization of perfect reconstruction FB frames and explicit and numerically efficient formulas to compute the tightest frame bounds, to obtain the dual FB frame, and to construct a tight (paraunitary) FB frame from a given untight (nonparaunitary) FB frame. The derivation uses well-developed techniques from modern control theory, which results in the unified formulas for generic infinite-impulse-response (IIR) and finite-impulse-response (FIR) FBs. These formulas involve only algebraic manipulations of real matrices and can be computed efficiently, reliably, and exactly without the approximation required in the existing methods for generic FBs. The results provide a unified framework for frame-theory-based analysis and systematic design of oversampled filter banks

This paper extends the existing results on the robust H"2 and H"~ filtering problems with respect to polytopic uncertainty. A new structure of slack variables is introduced to provide extra free dimensions in the solution space for the H"2 and H"~ optimization. This directly leads to performance improvement and reduction of conservativeness in the filtering solution. The method is applicable to both discrete and continuous time systems. Performance of the proposed solutions in comparison with that of the existing methods is illustrated by several examples.

Based on linear matrix inequality (LMI) technique, a new design method is proposed for the reduced-order filters of continuous and discrete time linear systems. The method is derived from decomposing the key matrix in LMIs which determines the order of designed filters. Different from the existing methods, the proposed method first minimizes the upper bound of the key matrix and then eliminates its near-zero eigenvalues, which results in a simpler, more direct and reliable design procedure. The proposed method can be used to design H"2 and H"~ reduced-order filters and multirate filter banks. Its effectiveness is illustrated by several examples.

This paper extends the results of Zhang et.al. (1997) for linear periodically time-varying control to general linear time-varying (LTV) control. It is shown that linear time-invariant (LTI) control provides strictly better control performance than linear strictly time-varying control if l2 disturbance rejection of LTI plants is considered. The analysis is carried out in the frequency domain. This approach provides not only new results on disturbance rejection of LTV control but also some new insight into the properties of general LTV systems.

Investigates robustness of linear periodically time varying (LPTV) control of discrete linear time invariant (LTI) plants subject to LTI unstructured perturbations. The note first derives a necessary and sufficient condition for robust stability of an LPTV system subject to LTI perturbations, which is less conservative than the well known small gain condition. It then presents a quantitative analysis on the robustness of LPTV control under LTI unstructured perturbations in comparison with that of LTI control. It is shown that under the normal value of the controller period suggested in the previous literature, the stability margin is deteriorated by LPTV control if LTI unstructured perturbations are considered. Hence LTI control is superior to LPTV control in this respect.

In this paper, the performance of discrete time periodically time-varying controllers for rejection of lp specific and uniform disturbances is analyzed. For control of linear time-invariant plants, this paper distinguishes linear time-invariant controllers from linear non-time-invariant periodic controllers in the performance analysis. For a given linear non-time-invariant periodic controller, a linear time-invariant controller is constructed and necessary and sufficient conditions are presented under which the linear time-invariant controller gives strictly better lp control than the non-time-invariant periodic controller.

Analyzes performance of periodically time-varying sampled data controllers for L/sub p/ deterministic and uniform disturbance rejection. For a given linear periodic sampled data controller controlling a linear time-invariant continuous-time plant, it is shown that a linear time-invariant controller can be found to give better L/sub p/ sampled data control than the time-varying controller. The performance analysis is in time domain using convexity properties of the L/sub p/ signal space.

This paper uses a frequency domain approach to the analysis of H 2 performance of continuous time periodically time varying controllers. For control of linear time invariant plants, it is shown that the time varying dynamics of the periodic controller deteriorates the closed-loop system H 2 performance and a linear time invariant controller can be found to provide strictly better H 2 control of the system.

This paper presents analysis of the H 2 and H ∞ performance of discrete linear periodically time-varying controllers for control of linear time-invariant plants. Using a frequency-domain lifting approach, the analysis distinguishes periodically time-varying control from time-invariant control to show that the multiple transfer channels of the system time-varying dynamics amplify the overall system gain. Such a result can provide deeper insights into the system time-varying mechanism and clarify how the time-varying dynamics acts and degrades the system performance. Quantitatively, the paper presents necessary and sufficient conditions under which a linear time-invariant controller can be found to provide strictly better control than periodically time-varying controllers.

This paper uses a frequency domain approach to the performance analysis of periodically time varying controllers. It is shown that for control of linear time invariant plants, the time varying dynamics of the controller degrade the closed loop system H 2 and H ∞ performance. Provided the time varying dynamics of the controller actively control the system, a time invariant controller can be found which can provide strictly better H 2 and H ∞ performance than that of the periodically time varying controller.

Shift variance bounds of critically sampled multirate filter banks are usually defined by using eigensystem analysis of the commutator operator. Computational methods are provided for two-channel FIR filter banks by Aach and Fuhr (2009). This paper investigates shift variance bounds in oversampled multi-channel filter banks and derives some general results which include some of Aach and Fuhr (2009) as special cases. Using polyphase representation, numerical methods are provided to compute the shift variance bounds for arbitrary filter banks. Examples are given to demonstrate the effectiveness of the obtained results.

In this paper, we study the system error of an inverse LPTV system, which is the difference between the reconstructed input sequence and the actual input sequence. The inverse LPTV system is computed by outer-inner factorization approach, and is realized mixed causal-anticausally. It is shown that the system error is exponential stable and can be modeled. By appending a number of zeros before and after the actual input sequence, a number of redundant system errors are introduced. The actual system error can be reduced by discarding the redundant errors.

A stabilizing 2-DOF predictive control law embodying integral action is used to adaptively control an unknown linear plant of given order. A syndrome detects if the estimated plant yields a singular control law. After singularity detection the inputs are perturbed. Though the above perturbation can be always chosen vanishingly small, it is shown that the self-excitation turns off forever after a finite time, and the controller self-tunes so as to make the closed-loop system exponentially stable and offset-free.

Models of anticausal systems have provided useful means for the analysis and understanding of system performance and properties and found applications in circuits, signal processing and dynamical systems. In this paper, structure and properties of linear time varying (LTV) mixed causal and anticausal systems are studied and state space realizations of cascaded LTV mixed causal and anticausal systems are presented. The conditions for the cascaded system realizations are related to time-varying Sylvester equations in terms of state-space matrices of the systems.

This paper presents a frame analysis of Zero Forcing (ZF) precoding problem. It shows that from a frame point of view, the filter bank (FB) channel is a synthesis frame and its canonical dual analysis frame is the optimal ZF precoder under total power constraint. Based on this analysis, a new precoder design is presented. The new design removes the minimum phase assumption of polyphase FB channel in the existing methods and gives rise to optimal noncausal (stable) precoder. It provides a general framework for optimal zero-forcing precoding under total power constraint. The numerical results show that the new design outperforms existing causal stable design.

This paper investigates signal predictive quantization subject to channel loss. It uses the analysis and design tools of H ∞ optimal filtering of discrete-time Markov jump linear system to obtain an optimal predictor for a signal predictive quantization system with channel loss. A linear matrix inequality (LMI) based design method is derived to design the predictor that minimizes the variance of the reconstruction error and removes the unrealistic assumption on quantizer model in the present literature. Simulation results are presented to show the advantages of the obtained design method.

The paper deals with I/O versions of receding horizon controllers based on the minimization of multistep quadratic costs with the constraint that the terminal state goes to zero. The resulting control law yields stable closed-loop systems under sharp conditions. Simulation results are presented to both verify the theoretical analysis and relate the new control law with GPC

This paper investigates optimal signal predictive quantization in the presence of source model uncertainties. It uses polytopic system model to represent the uncertainties in source signal and uses the recent results on robust filtering [8] to obtain a robust H ∞ optimal design of signal predictor. Results of computational study is presented to demonstrate the advantages of the obtained design.

This paper is concerned with signal predictive quantization with channel loss. It uses the analysis and design tools of H 2 optimal filtering of discrete-time Markov jump linear system to obtain an optimal predictor for a signal predictive quantization system with channel loss. An LMI based design method is derived to design the predictor that minimizes the variance of the reconstruction error subject to the channel loss. Simulation results are presented to show the advantages of the obtained design method.

In this short paper, the H ∞ filter design for uncertain singular systems is considered. We study to design normal filters and singular filters for the same singular systems. Via using linear matrix inequalities (LMIs), the sufficient conditions are established for the existences of two kinds of filter forms such that two uncertain error systems are admissible and their transfer functions from the disturbance to the filtering error output satisfy a prescribed H ∞ -norm bound constraint. By solving LMIs, explicit parameterization expressions of all desired normal filters and singular filters are obtained. Furthermore, all results involve no decomposition the original singular system matrices. It makes that the procedure of filter design is simple and direct. Simultaneously, we still optimize and compare with their H ∞ performances for uncertain error systems under two kinds of filter cases. Finally, a numerical example is given to illustrate the effectiveness of the proposed design method and compare with their H ∞ performances.

This paper investigates robust fault isolation and estimation of networked systems, where the plant output is transmitted to the estimator through a network channel with limited communication capacity including signal transmission delay, data packet dropout and measurement quantization. A sufficient condition in terms of affine matrix inequality is developed which guarantees the estimation error below a prescribed bound in the presence of polytopic model uncertainties, time-varying signal delay, networked induced data dropout and quantization. Based on this result, an algorithm for robust fault estimation design is developed by the congruence transformation which transforms the nonlinear matrix inequality to a computable linear matrix inequality (LMI). A numerical example demonstrates that the proposed approach is less constraint restrictive than the existing approaches in literature.

A causal realization of an inverse system can be unstable and an anti-casual realization is to deal with this problem to provide a numerically stable procedure to inverse the system and compute its input signal. In this paper, we consider the anti-causal realization of the inverse of discrete time linear periodic systems obtained by an outer-inner factorization approach. It is shown that the outer-inner factorization can result in a stable anti-causal realization. An expression of the inversion error is derived, showing such an error is inevitable due to the anti-causal reversal operation.

This paper presents a simple method to improve the frame-bounds-ratio of perfect reconstruction (PR) oversampled filter banks (FBs) by adjusting the gain of each subband filter. For a given analysis PRFB, a finite convex optimization algorithm is presented to redesign the subband gains such that the frame-bounds-ratio of the FB is minimized. The algorithm also provides an effective way to compute the frame bounds. Examples show the effectiveness of the presented method.

This paper is concerned with signal predictive subband quantization in oversampled filter banks. It uses the analysis tools of robust filtering and control to obtain a worst case power spectral analysis of the prediction error system. The analysis removes the unrealistic assumptions on the quantization noises in the present literature and leads to the definition of Hinfin optimal signal predictor. Based on this analysis, an LMI optimization based method is obtained to design the Hinfin optimal signal predictor with guaranteed inverse stability. Simulation results are presented to show the advantages of the Hinfin optimal signal predictor over the conventional signal predictor.

This paper is concerned with the design of signal predictor in oversampled signal predictive subband coding. Spectral analysis of the prediction error system is used to derive an H2 optimization formulation of the design problem, and an LMI based method is obtained to design the H2 optimal signal predictor that minimizes the variance of quantizer input signals. Simulation examples are presented to demonstrate the obtained design method.

This paper is concerned with reduced-order H/sub 2/ and H/sub /spl infin// multirate filter bank design. Parameter-dependent Lyapunov function (PDLF) based linear matrix inequality (LMI) conditions are presented for the design of reduced-order synthesis filters. By the introduction of two new slack variables in PDLF, the constraint on the Lyapunov matrix is converted to the constraint on the new slack variables. This renders a less conservative design method for reduced-order multirate filter bank. The effectiveness of the proposed method is illustrated by an example.

In this paper, a state space approach for computing the inverse of a general single-input single-output linear periodically time-varying filter is proposed. The inverse of the filter is derived by first constructing the inverse of an LPTV filter. The result is then extended to obtain the inverse of the IIR filter. Compared with existing approaches using other techniques, the proposed approach is quite straightforward, hence, can reduce the computational complexity.

In this paper, we present an explicit and numerically efficient formulae to construct a tight (paraunitary) FB frame from a given un-tight (non-paraunitary) FB frame. The derivation uses the well developed techniques from modern control theory, which results in the unified formulae for generic IIR and FIR FBs. These formulae involve only algebraic matrix manipulations and can be computed efficiently and reliably without the approximation required in the existing literature.

This paper studies the noise reduction design problem for oversampled filter banks (FBs) with perfect reconstruction (PR) constraint. Both the optimal design and worst case design are considered, where the former method caters for the noise with known power spectral density (PSD) and the latter one for the noise with unknown PSD. Explicit formulae involving only algebraic Riccati equation and matrix manipulations are provided for the general (IIR or FIR) oversampled PR FBs.

In this paper, we propose a state space approach to the decomposition of linear periodic time-varying (LPTV) systems. It decomposes an LPTV system into two subsystems: the stable LPTV subsystem and the unstable LPTV subsystem. An anti-causal realization for the unstable LPTV subsystem is further developed for providing stable numerical computation of the unstable system output.

The deficiencies of present power measurement definitions and techniques in the presence of harmonics is a known problem. As a solution to this problem, a new three phase power theory, which decomposes the instantaneous power into active and non-active instantaneous power, is proposed. With good knowledge of the active/non-active power components an accurate measurement especially of the non-active component is achieved. Also this non-active component can be utilised to achieve better compensation. The theory is evaluated for linear and nonlinear loads in the presence of harmonics with a case study. Results of case study and analysis of the results demonstrate good performance of the proposed theory.

The values of non-active (reactive) and total (apparent) power for three-phase systems change with choice of reference conductor. Presently, the neutral in a four-wire system and virtual neutral in three wire systems is the commonly used reference in definitions. In this paper, it is shown that this is not necessarily the optimal choice of reference. Thus, there is a need to define an optimal reference that has practical value. As a solution to this problem, a new approach to determine the optimal reference is proposed. The approach is simple but effective. It allows extension of single-phase power definitions to 3-phase systems to produce unique values without the need to address balanced and unbalanced cases separately. The resulting definitions can be used to provide optimal non-active power compensation. The performance of this approach is illustrated with a case study. The case study uses three-phase three and four wire systems with different resistive, inductive and capacitive load combinations. The results of case study demonstrate good performance of the new approach.

A multivariable version of an I/O (input/output) receding horizon control law is presented, and its guaranteed stabilizing property is analyzed. The scheme that is considered makes easier the design of the controller and makes possible the reduction of computational burden in the adaptive application of predictive control. >

This paper analyzes robustness of multirate control systems with fast control sampling rate and slow output measurement rate in the frequency domain. It is shown that the multirate control is characterized by manipulating the system frequency response in high frequency subbands and folding the high frequency subband response to the base frequency band. This amplifies the system loop gain in high frequency subbands leading to deterioration of system robustness stability under the uniform plant model perturbation.

Extends the analysis results of linear periodically time varying controllers to general linear time varying (LTV) controllers. It is shown that linear time invariant (LTI) control provides strictly better control performance than linear strictly time varying control if l/sub 2/ disturbance rejection of LTI plants is considered. The analysis is carried out in the frequency domain. This approach provides not only new results on disturbance rejection of LTV control but also some insight into the properties of general LTV systems.

A method to insure the required excitation degree in closed loop via self-excitation is proposed for plants subject to bounded disturbances. A lower bound on the dither intensity which guarantees the required excitation degree is derived. Combining the proposed self-excitation method with a constant trace normalized RLS with a dead-zone and paradigmatic predictive control law-the stabilizing I/O receding horizon control, a globally convergent robust adaptive control algorithm is obtained for generic controllable plants. Advantages and limitations of the method are discussed. >