• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.4
• /
• pp.255-261
• /
• 2000

This paper presents the results of the robust H(sub)$\infty$ FIR filtering for a class of nonlinear continuous time-varying systems subject to real norm-bounded parameter uncertainty and know Lipschitz nonlinearity under sampled measurements. We address the problem of designing filters, using sampled measurements, which guarantee a prescribed H(sub)$\infty$ performance in continuous time-varying context, irrespective of the parameter uncertainty and unknown initial states. The infinite horizon causal H(sub)$\infty$FIR filter are investigated using the finite moving horizon in terms of two Riccati equations with finite discrete jumps.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.27 no.2
• /
• pp.102-113
• /
• 2004

This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of vehicle is determined. A distribution system is consisted of a distribution center and many retailers. The model is assumed that the time horizon is discrete and finite, and the demand of retailers is dynamic and deterministic. Products are transported from distribution center to retailers according to transportation planning. Cost factors are the transportation cost and the inventory cost, which transportation cost is proportional to transportation distance of vehicle when products are transported from distribution center to retailers, and inventory cost is proportional to inventory amounts of retailers. Transportation time to retailers is represented as a genetic string. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. A mathematical model is developed. Genetic algorithm procedure is suggested, and a illustrative example is shown to explain the procedure.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.12
• /
• pp.1183-1187
• /
• 2011

In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.83.4-83
• /
• 2002

$\bullet$ We present a state-feedback RHC for discrete-time TS fuzzy systems with input constriants. $\bullet$ The controller employ the current and one-step past information on the fuzzy weighting functions. $\bullet$ It is obtained from the finite horizon optimization problem with the invariant ellipsoid constraint $\bullet$ Under parameterized LMI conditions on the terminal weighting matrix $\bullet$ The closed-loop system stability is guaranteed. $\bullet$ The parameterized linear matrix inequalities are relaxed to a finite number of solvable LMIs.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.567-573
• /
• 1998

본 논문에서는 입력과 상태변수에 hard constraint가 있는 이산시간 시스템에 대한 새로운 이동구간 제어기를 제안한다. 제안된 이동구간제어기가 terminal ellipsoid constraint를 이용하여 지수 안정성(exponential stability)을 보장함을 보인다. Feasibility를 증가시키기 위하여 시스템을 안정 모드와 불안정 모드로 바꾸는 방법, constraint를 완화하는 방법을 제안한다. Constraint를 완화할 때 constraint를 만족시키지 못하는 부분의 성능을 개선시키는 방법을 제안하고 예제를 통해서 몇 가지 제안한 방법들을 비교한다.

• 전기의세계
• /
• v.49 no.9
• /
• pp.17-24
• /
• 2000

This paper presents sufficient conditions7 for monotonicity of the saddle point value for receding-horizon H$\infty$ control(RHHC). The resulting monotonicity is used to prove the stability of the closed-loop. Under these sufficient conditions the well-known terminal equality condition is handled as a special case and the condition on the state weighting matrix is weakened so as to include even the zero matrix. The whole procedure is much simpler than the previous results and thus is expected to be easily extended for constrained delayed and/or nonlinear systems with the RHHC.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.3
• /
• pp.159-163
• /
• 2001

An input constrained receding horizon predictive control algorithm for uncertain systems with nonzero set points is proposed. for constant nonzero set points, models with uncertainty can be converted into an augmented incremental system through the use of integrators and the problem is transformed into a zero-state regulation problem for the incremental system. But the original constraints on inputs are converted into constraints on the sum of control inputs at each time instants, which have not been dealt in earlier constrained robust receding horizon control problems. Recursive state bounding technique and worst case minimizing strategy developed in earlier works are applied to the augmented incremental system to yield an offset error free controller. The resulting algorithm is formulated so that it can be solved using LP.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.4
• /
• pp.289-292
• /
• 2001

This paper concerns with a receding horizon estimator (RHE) for discrete-time linear systems subject to constraints on the estimate. In solving the optimization for every horizons, the past all measurement data outside the horizon is discarded and thus the arrival cost is not considered. The RHE in the current work is a finite impulse response (FIR) structure which has some good inherent properties. The proposed RHE can be represented in the simple matrix form for the unconstrained case. Various numerical examples demonstrate how including constraints in the RHE can improve estimation performance. Especially, in the application to the unknown input estimation, it will be shown how the FIR structure in the RHE can improve the estimation speed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.49-55
• /
• 1992

In this paper, we developed a Receding Horizon Predictive Control for Stochastic state space models(RHPCS). RHPCS was designed to minimize a quadratic cost function. RHPCS consists of Receding Horizon Tracking Control(RHTC) and a state observer. It was shown that RHPCS is equivalent to Generalized Predictive Control(GPC) when the underlying state space model is equivalent to the I/O model used in the design of GPC. The equivalence between GPC and RHPCS was shown through. the comparison of the transfer functions of the two controllers. RHPCS provides a time-invarient optimal control law for systems for which GPC can not be used. The stability properties of RHPCS was derived. From the GPC's equivalence to RHPCS, the stability properties of GPC were shown to be the same as those for RHTC.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.502-502
• /
• 2000

An input constrained receding horizon predictive control algorithm for uncertain systems with nonzero set points is proposed. For constant nonzero set points, models with uncertainty can be converted into an augmented incremental system through the use of integrators and the problem is transformed into a zero-state regulation problem for the incremental system. But the original constraints on inputs are converted into constraints on the sum of control inputs at each time Instants, which have not been dealt in earlier constrained robust receding horizon control problems. Recursive state bounding technique and worst case minimizing strategy developed in earlier works are applied to the augmented incremental system to yield an of set error free controller. The resulting algorithm is formulated so that it can be solved using LP.