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In this paper, we propose a straightforward method to select the parameters of the PI controllers in Field Oriented Control (FOC) scheme for Permanent Magnet Synchronous Motor (PMSM) based on geometric model reduction and structured H∞-synthesis. The main contribution of this paper is that, by recognizing the essential linear system structure of PMSM model and using mature robust control method, the...
In this paper, an interal observer for both state and unknown input estimation is proposed for a Linear Time Invariant (LTI) system. It generalizes previous work done on the subject. Such an observer is constructed under some specific conditions. Among those conditions, a rank condition is needed to ensure the independence between the state estimation and the unknown input. In this paper, former proposed...
This paper deals with a design problem of variable gain robust model following/tracking control for a class of uncertain linear systems. The new proposed variable gain robust control system is composed of fixed gain controllers and variable ones. In this paper, LMI-based sufficient conditions for the existence of the proposed variable gain robust controller are given. Finally, a simple numerical example...
A simple but versatile approach to robust control design for linear systems with system and exogenous disturbances is proposed. The proposed approach is based on the technique of linear matrix inequalities and the concept of invariant ellipsoids. The approach is easily implemented computationally, its efficacy is demonstrated on the benchmark example of the F-16 aircraft model.
In this paper, we propose a control model based on NCS theory to solve the vehicle-following problem, which presents both issues: the difficulty in the identification process and a lossy network. To deal with network losses, we use a mode dependent Markov jump linear filter coupled with a statefeedback controller. To handle parameter uncertainty, a polytopic representation of the car model is presented...
In this paper, we propose a predictor-based sliding mode control algorithm for LTI systems with input-delay and disturbance. It is shown that our proposed algorithm can completely reject the constant disturbance from the state channel. It is also shown that with our proposed algorithm, an enhanced disturbance rejection can be achieved for a large class of other time-varying disturbances. Simulations...
In this study we introduce a Linear Parameter Varying (LPV) based controller design possibility for LPV systems with state and input uncertainties. Through the LPV framework the developed method can be used for the nonlinear system belongs to the given LPV system. The controller design approach effectively exploits the combination of the classical state feedback and matrix similarity theorems in order...
Using graph-theoretic tools, distributed control algorithms have been widely designed to manage a cooperative task among a group of individual agents. However, when agents are physically interconnected, these algorithms do not guarantee stability of the closed-loop multiagent system. In this paper, we consider a class of interconnected linear multiagent systems with state- and input-coupled modeling...
For the state estimation of safety-critical systems, interval observers are an emerging alternative to classical state estimation methods due to their provision of guaranteed information on unmeasurable quantities. One possible application of interval observers are induction machines used as a traction drive whose common models belong to the class of linear parameter-varying (LPV) systems. To overcome...
This paper presents a controller design methodology for linear dynamic systems with interval parameters. In order to overcome the conservatism of classical Interval Analysis methods applied to this class of uncertain systems, the paper proposes a solution for the problem of multi-incidences of model parameters when the controller design is based on interval Diophantine equations. The paper includes...
This paper considers the problem of dynamic output feedback H∞ controller design for linear systems with input and output imprecision. In the controlled systems, the measurement and control signal transmissions from the plant to the controller and the controller to the plant, respectively, are assumed to be imprecise, and norm-bounded uncertainties are utilized to model the phenomenon of the imprecise...
The problem of the state tracking over a finite-time interval is concerned in this paper. Based on the average dwell-time method, both matched and unmatched cases are considered in the system. To make the state tracking error is finite-time bounded and the considered system achieves a weighted H∞ performance for the exogenous disturbance, the switching law is designed by the states error. Sufficient...
This paper investigates robust adaptive control of uncertain switched linear systems considering disturbances. Two modifications of the adaptive law of switched linear systems [1] based on parameter projection and a leakage approach are developed to guarantee the stability of the closed-loop switched linear system: a projection law that requires knowledge of the bounds of the parameter estimates;...
An adaptive model predictive control (MPC) is proposed in this paper to stabilize linear constrained systems with parametric uncertainties. The proposed control is designed by combining linear MPC and an adaptive updating law for uncertain parameters. It is proved that, by using the proposed adaptive MPC, states of the linear system can be stabilized, and the estimated parameters are bounded. The...
In this paper, an off-policy reinforcement learning method is developed for the robust stabilizing controller design of discrete-time uncertain linear systems. The proposed robust control design consists of two steps. First, the robust control problem is transformed to an optimal control problem. Second, the off-policy RL method is used to design the optimal control policy which guarantees the robust...
This paper presents a complete method for automatic and robust control configuration selection for linear systems which relies upon acquired process data under Gaussian noise excitation. The selection of the configuration is based on the estimation of the Interaction Measure named Participation Matrix. This estimation is derived with uncertainty bounds, which allows to determine online whether the...
The problem of rejecting unknown sinusoidal disturbances in the output of an unknown LTI system which is also corrupted by wide-band noise has received a lot of interest in the recent years. Most of the successful efforts proposed up to now assume that the model of the LTI system is stable and is known exactly. This paper shows how an overparameterized classical robust model-reference adaptive control...
This paper formulates the problem of allocating the closed loop poles of discrete-time systems in specific regions of the complex plane through state-feedback as a semi-definite optimization program. In order to handle the non-convex sets that arise from the minimum damping factor specification, a new inner approximation is proposed. Linear matrix inequalities (LMI) regions are used to define restrictions...
This paper improves a stabilization condition of one-step receding horizon control for discrete-time linear systems with model uncertainties. By using matrix inversion lemma, the improved stabilization condition is derived in terms of a matrix inequality associated with the terminal-time weighting matrix of the cost. A numerical example verifies that the proposed condition guarantees the larger maximum...
Exact linearization is often applied to nonlinear processes. This method requires not only the knowledge of the model structure but also the accurate parameter values. If the real parameter values of the controlled process are different from the nominal values used for the exact linearization, the resulting system may not be linear or may have different gains and time constants as expected. A simple...
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