Randomized optimization is a recently established tool for control design with modulated robustness. While for uncertain convex programs there exist randomized approaches with efficient sampling, this is not the case ...
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ISBN:
(纸本)9781479932757
Randomized optimization is a recently established tool for control design with modulated robustness. While for uncertain convex programs there exist randomized approaches with efficient sampling, this is not the case for non-convex problems. Approaches based on statistical learning theory are applicable for a certain class of non-convex problems, but they usually are conservative in terms of performance and are computationally demanding. In this paper, we present a novel scenario approach for a wide class of random non-convex programs. We provide a sample complexity similar to the one for uncertain convex programs, but valid for all feasible solutions inside a set of a-priori chosen complexity. Our scenario approach applies to many non-convex control-design problems, for instance control synthesis based on uncertain bilinear matrix inequalities.
In this article, an Active Disturbance Rejection control (ADRC) scheme, using a Generalized PI disturbance observer based control is applied to the stabilization problem of the Inertia wheel pendulum. The control sche...
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ISBN:
(纸本)9781479917730
In this article, an Active Disturbance Rejection control (ADRC) scheme, using a Generalized PI disturbance observer based control is applied to the stabilization problem of the Inertia wheel pendulum. The control scheme assumes a limited knowledge of the underactuated system and relies on a simplified model regarded as a perturbed chain of two integrators with a stable zero dynamics. The control scheme is experimentally tested, showing good performance. A comparison study with respect to a linear control scheme is also carried out.
It is well known that the process of tuning a fuzzy logic controller is almost always a very complex task, which is time consuming, very laborious and often requires expert knowledge of the controlled system. Mapping ...
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It is well known that the process of tuning a fuzzy logic controller is almost always a very complex task, which is time consuming, very laborious and often requires expert knowledge of the controlled system. Mapping of fuzzy logic controller's parameters (rule base and membership functions of input(s) and output(s)) into a performance measure in a closed analytical form is near impossible to get, and thus the use of any classical optimization method is automatically ruled out. Knowing this, genetic algorithms with a fitness function in a form of cumulative response error represent a good choice of the optimization method. This approach enables the use of offline optimization of membership functions' parameters (which are being coded into chromosomes). Sugeno-Takagi fuzzy logic controllers with a proportional and a derivative component, and also with a fixed rule base are used in this approach. Experimental results of both simulations and validations on real systems are given in this paper and they show the good performance of this approach.
The practical effectiveness of modular robotic systems depends heavily on the connection mechanisms used to join their separate entities, particularly for those systems capable of self-reconfiguration. This work prese...
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ISBN:
(纸本)9781479969357
The practical effectiveness of modular robotic systems depends heavily on the connection mechanisms used to join their separate entities, particularly for those systems capable of self-reconfiguration. This work presents HiGen, a high-speed genderless mechanical connection mechanism for the docking of robotic modules. HiGen connectors can join with one another in a manner that allows either side to disconnect in the event of failure. During connection electrical contacts are mated, supporting the concurrent use of local and global communication protocols, as well as power sharing techniques. Rapid actuation of the mechanism allows connections to be made and broken at a speed that is, to our knowledge, an order of magnitude faster than existing mechanical genderless approaches that feature single-sided disconnect, benefiting the reconfiguration time of modular robots. The HiGen connector is intended for future work in modular robotics, but could also see use in other areas of robotics for tool and payload attachment.
In this paper, an alternating direction method of multipliers (ADMM) based realtime model predictive control (MPC) algorithm is presented. With the use of indicator function and by introducing extra consensus constrai...
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Recently the control methods based on disturbance rejection have largely renewed our understanding of automaticcontrol, especially the role of feedforward control. With the renewed understanding, this work presents a...
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Recently the control methods based on disturbance rejection have largely renewed our understanding of automaticcontrol, especially the role of feedforward control. With the renewed understanding, this work presents a feedforward and feedback approach for control of general dynamic systems under a state tracking framework. This is realized by introducing a fictitious system model and employing a proper state and disturbance estimator. The resultant control scheme embodies a close cooperation between feedforward and feedback controls: Feedforward control rejects the general disturbance and embeds a reference state trajectory, whilst feedback control cancels the fictitious dynamics and enforces desired tracking error dynamics. A notable advantage of the approach is that control designs of linear and nonlinear systems can follow a common routine and the closed-loop stability is guaranteed under standard conditions.
Lecture flipping is a relatively new concept (Mazur, 2012) in higher education. This paper serves as a test case of lecture flipping used in the context of some classical control courses. Specifically the paper discus...
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Lecture flipping is a relatively new concept (Mazur, 2012) in higher education. This paper serves as a test case of lecture flipping used in the context of some classical control courses. Specifically the paper discusses the resource implications, and availability including how resources can be accessed by the wider community. Also, the paper includes gives detailed staff reflections on the efficacy of the approach and some preliminary student evaluation.
Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity...
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ISBN:
(纸本)9781510821415
Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.
In this paper, we address the wellposedness and online resolution of algebraic loop arising from the feedback interconnection of a linear time invariant system and a static nonlinearity whose input-output characterist...
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This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representations of nonlinear (NL) systems which are originally defined by control affine state-space representations. The conver...
This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representations of nonlinear (NL) systems which are originally defined by control affine state-space representations. The conversion approach results in LPV state-space representations in the observable canonical form. Based on the relative degree concept of NL systems, the states of a given NL representation are transformed to new coordinates that provide its normal form. In the SISO case, all nonlinearities of the original system are embedded in one NL function which is factorized to construct the LPV form. An algorithms is proposed for this purpose. The resulting transformation yields an LPV model where the scheduling parameter depends on the derivatives of the inputs and outputs of the system. In addition, if the states of the NL model can be measured or estimated, then the procedure can be modified to provide LPV models scheduled by these states. Examples are included for illustration.
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