Zhiqiang Tan

Dissipative control of linear discrete-time systems with dissipative uncertainty

This paper focuses on the dissipative control of uncertain linear discrete-time systems. The uncertainty under consideration is characterized by a dissipative system, which contains commonly used uncertainty structures, such as normbounded and positive real uncertainties, as special cases. We consider the design of a feedback controller which can achieve asymptotic stability and strict quadratic dissipativeness for all admissible uncertainties. Both the linear static state feedback and the dynamic output feedback controllers are considered. It is shown that the robust dissipative control problem can be solved in terms of a scaled quadratic dissipative control problem without uncertainty. Linear matrix inequality (LMI) based methods for designing robust controllers are derived. The result of this paper unifies existing results on discrete-time H and positive real control and it provides a more flexible and less conservative control design as it al ows for a bet er trade-off between phase and gain performances.

Envelope-constrained H∞ filter design : An LMI optimization approach

In this correspondence, we solve the envelope-constrained H/sub /spl infin// filter design problem by minimizing the H/sub /spl infin// norm of the filtering error transfer function subject to the constraint that the filter output is contained in a prescribed envelope. The filter design is transformed into a standard linear matrix inequality (LMI) optimization problem.

Envelope-constrained IIR filter design: An LMIH∞ optimization approach

In this paper, we consider envelope-constrained (EC) infinite impulse response (IIR) filtering problems. The aim is to design an IIR filter such that theH∞ norm of the filtering error transfer function is minimized subject to the constraint that the estimation error with a given input to the linear dynamic system is contained or bounded in a prescribed envelope. The filter design problem is formulated as a standard optimization problem in linear matrix inequalities (LMIs).

H2 optimal envelope-constrained FIR filter design: An LMI approach

Abstract This paper is concerned with an H 2 optimal envelope-constrained (EC) finite impulse response (FIR) filtering problem. The aim is to design an FIR filter such that the H 2 norm of the combined filter and fixed noise shaping filter is minimized subject to the constraint that for a given input to the filter, its noiseless output is contained or bounded in a prescribed envelope. The filter design problem is formulated as a standard optimization with linear matrix inequality (LMI) constraints. Futhermore, by relaxing the H 2 optimal norm constraint, we propose a robust ECFIR filter design algorithm based on the LMI approach.

H optimal envelope-constrained FIR filter design with uncertain input

This paper is concerned with the design of H∞ optimal envelope-constrained FIR filter with uncertain input (ECUI). The aim is to design an FIR filter such that norm-bounded additive enhancement is minimized while satisfying the constraint that the filter output, in response to a set of input signals, lies within a pulse shape envelope. The filter design is formulated as a standard optimization problem with linear matrix inequality (LMI) constraints.

Envelope-constrained H/sub /spl infin// filter design: An LMI optimization approach

In this correspondence, we solve the envelope-constrained H/sub /spl infin// filter design problem by minimizing the H/sub /spl infin// norm of the filtering error transfer function subject to the constraint that the filter output is contained in a prescribed envelope. The filter design is transformed into a standard linear matrix inequality (LMI) optimization problem.

H/sub /spl infin// optimal envelope-constrained FIR filter design: an LMI approach

In this paper, we consider the envelope-constrained (EC) finite impulse response (FIR) filtering problems. The aim is to design an FIR filter such that the H/sub /spl infin// norm of the filter is minimized subject to the constraint that for a given input to the filter, its noiseless output is contained or bounded in a prescribed envelope. The filter design problem is formulated as a standard optimization one with linear matrix inequality (LMI) constraints. Furthermore, by relaxing the H/sub /spl infin// optimal norm constraint, we propose a robust ECFIR filter design algorithm based on the LMI approach.

Envelope-constrained H2 FIR filter design

In this paper, we consider an envelope-constrained (EC)H2 optimal finite impulse response (FIR) filtering problem. Our aim is to design a filter such that theH2 norm of the filtering error transfer function is minimized subject to the constraint that the filter output with a given input to the signal system is contained or bounded by a prescribed envelope. The filter design problem is formulated as a standard optimization problem with linear matrix inequality (LMI) constraints. Furthermore, by relaxing theH2 norm constraint, we propose a robust ECFIR filter design algorithm based on the LMI approach.

Dissipation design for uncertain discrete-time systems

Considers dissipative analysis and synthesis problems for a class of signal processing systems with uncertainties satisfying some summed quadratic constraints. For dissipative analysis, we are concerned with deriving conditions such that a given system is of a desired dissipative property. As for the latter problem, we focus on compensation design for each of the subsystems to achieve certain dissipative property such that their interconnections will be stable. Our solution to the above two problems are in terms of the feasibility of one or more linear matrix inequalities which can be solved efficiently.

Envelope-constrained H i filter design: An LMIoptimization approach

In this correspondence, we solve the envelope-constrained H/sub /spl infin// filter design problem by minimizing the H/sub /spl infin// norm of the filtering error transfer function subject to the constraint that the filter output is contained in a prescribed envelope. The filter design is transformed into a standard linear matrix inequality (LMI) optimization problem.