This paper presents a simple but effective tuning strategy for robust static output feedback (SOF) controllers with minimal quadratic cost in the context of multiple parametric uncertainties. Finding this type of cont...
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This paper presents a simple but effective tuning strategy for robust static output feedback (SOF) controllers with minimal quadratic cost in the context of multiple parametric uncertainties. Finding this type of controller is known to be computationally intractable using conventional techniques. This is mainly due to the non-convexity of the resulting control problem, which has a fixed structure. To solve this kind of control problem easily and directly, without using any complicated mathematical manipulations, we utilize Kharitonov's theorem and an evolutionary algorithm (EA) for the resolution of the underlying constrained optimization problem. Using Kharitonov's theorem, a family of bounded, robustly stable static output feedback controllers can be defined and EA is used to select the controller that ensures a minimal quadratic cost within this family. The resulting tuning strategy is applicable to both stable and unstable systems, without any limitations on the order of the process to be controlled. A numerical study was conducted to demonstrate the validity of the proposed tuning procedure. (C) 2010 Elsevier Inc. All rights reserved.
This paper presents a simple but effective tuning strategy for robust PID controllers satisfying multiple H-infinity performance criteria. Finding such a controller is known to be computationally intractable via the c...
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This paper presents a simple but effective tuning strategy for robust PID controllers satisfying multiple H-infinity performance criteria. Finding such a controller is known to be computationally intractable via the conventional techniques. This is mainly due to the non-convexity of the resulting control problem which is of the fixed order/structure type. To solve this kind of control problem easily and directly, without using any complicated mathematical manipulations and without using too many "user defined" parameters, we utilize the heuristic Kalman algorithm (HKA) for the resolution of the underlying constrained non-convexoptimization problem. The resulting tuning strategy is applicable both to stable and unstable systems, without any limitation concerning the order of the process to be controlled. Various numerical studies are conducted to demonstrate the validity of the proposed tuning procedure. Comparisons with previously published works are also given. (C) 2009 Elsevier Ltd. All rights reserved.
This paper introduces a new control scheme which incorporates the concept of shaping filter together with the use of the v-gap metric and the robust design of a structured controller. The main motivation in doing this...
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This paper introduces a new control scheme which incorporates the concept of shaping filter together with the use of the v-gap metric and the robust design of a structured controller. The main motivation in doing this is related to the development of efficient control laws for small size actuators. Designing a structured controller is known to be computationally intractable via the traditional Ho. method. This is mainly due to the non-convexity of the resulting control problem which is of fixed order or structure type. To solve this kind of control problem easily and directly, without using any complicated mathematical manipulations and without using too many "user defined" parameters, we utilize the heuristic Kalman algorithm (HKA) for the resolution of the underlying constrained non-convexoptimization problem. The experimental results validate the proposed technique and demonstrate its convenience for the development of fast and precise positioning systems. (C) 2014 ISA. Published by Elsevier Ltd. All rights reserved.
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