Gradient-based algorithms: they use derivative information to iterate in the direction of steepest descent for the objective function. Only local designs are compared in each iteration, which makes the implementation of CRN efficient and allows for application of stochastic approximation, which can significantly improve the computational efficiency of stochastic search methods (Kushner and Yin 2003). The latter approximation is performed by establishing through proper recursive formulas an equivalent averaging across the iterations of the optimization algorithm, instead of getting higher accuracy estimates for the objective function at each iteration (that is, averaging over one single iteration). In simple examples, the performance measure h(φ,θ) (or even the limit state function ( , ) g φ θ in ROP) are such that the gradient of the objective function with respect to φ can be obtained through a single stochastic simulation analysis (Spall 2003; Royset and Polak 2004). In many structuraldesign problems, though, the models used are generally complex and it is difficult, or impractical, to develop an analytical relationship between the design variables and the objective function. Finite difference numerical differentiation is often the only possibility for obtaining information about the gradient vector but this involves a computational cost which increases linearly with the dimension of the design parameters. Simultaneous-perturbation stochastic approximation (SPSA) (Spall 1992; Spall 2003) is an efficient alternative search method. It is based on the observation that one properly chosen simultaneous random perturbation in all components of φ provides as much information for optimization purposes in the long run as a full set of one at a time changes of each component. Thus, it uses only two evaluations of the objective function, in a direction randomly chosen at each iteration, to form an approximation to the gradient vector.
Model updating using measured system response, with or without measured excitation, has a wide range of applications in response prediction, reliability and risk assessment, and control of dynamic systems and structural health monitoring (e.g., Vanik et al. 2001; Beck et al. 2001; Papadimitriou et al. 2001; Beck and Au 2002; Katafygiotis et al. 2003; Lam et al. 2004; Yuen and Lam 2006; Ching et al. 2006). There always exist modeling errors and uncertainties associated with the process of constructing a mathematical model of a system and its future excitation, whether it is based on physics or on a black-box ‘nonparametric’ model. Being able to quantify the uncertainties accurately and appropriately is essential for a robust prediction of future response and reliability of structures (Beck and Katafygiotis 1991, 1998; Papadimitriou et al. 2001; Beck and Au 2002; Cheung and Beck 2007a, 2008a, 2008b). Here in this thesis, a fully probabilistic Bayesian model updating approach is adopted, which provides a robust and rigorous framework due to its ability to characterize modeling uncertainties associated with the system and to its exclusive foundation on the probability axioms.
Sliding mode control (SMC) has various attractive features such as fast response, good transient performance, order reduction and, particularly, robust with matched uncertainties, and is well known to be an effective way to handle many challenging problems of robust stabilization. Over the past decades, SMC has been one of the most popular control methods among the control community and has found wide applications to automotive systems, observers design, chemical processes, electrical motor control, aero-engineering and so on (see, e.g., Choi (2007), Gouaisbaut, Dambrine, and Richard (2002), Hu, Ge, and Su (2004), Hu, Ma, and Xie (2008), Jafarov (2005), Li and Decarlo (2003), Utkin (1992), Utkin, Guldner, and Shi (1999), Edwards, Akoachere, and Spurgeon (2001), Oucheriah (2003) and the references therein). Generally speaking, SMC uses a discontinuous control law (relays) to force and restrict the state trajectories to a predefined sliding surface on which the system has some desired properties such as stability, disturbance rejection capability and tracking (see Gouaisbaut et al. (2002), Li and Decarlo (2003) and Utkin (1992)).
LPV system [8-13] has been built by several linear systems and a specific weighting function to represent uncertain systems or nonlinear systems. According to the structure of LPV system, a general description for uncertain systems can be proposed to represent complex uncertainties. In [12-13], a Gain-Schedule (GS) control scheme has been applied to deal with the stabilization problem of LPV system. Because the structure of GS controller is similar to LPV system, the robustness of the described system can be increased. It means that the GS scheme is vary suitable control scheme for systems described by numerous sub-systems. Therefore, many robust stability criteria [10-13] have been proposed for LPV systems via applying the GS design scheme. Furthermore, many practical robustcontrolapplications [9, 13] have been achieved via LPV system and
Since magnetic levitation system is a voltage-controlled third-order nonlinear system, it is wise that design a nonlinear controller to transform it into a linear model. Thus, a feedback linearization technique [10, 13] is used to transform the nonlinear model into a linear model. However, the robustness of the system is not guaranteed due to there are some uncertainties or disturbances occur in the system and these uncertainties is needed to develop a linear model. In spite of that, this technique also required perfect model to cancel the exact nonlinear terms. Therefore, it needs a lot of work to study and design. Then, a sliding-mode control [12, 15] is proposed to make sure the robustness of the system in this project instead of using adaptive controller . This is because the adaptive controller does not give a good transient response although sliding-mode control needs a lot of control effort. Apart from that, H ∞ method  is used with sliding mode control to solve
In literature, the adaptive control approaches has been widely developed in aerospace ap- plications on the base of a large panel of methods. The authors developed in  a method based on the self-learning to accomplish a precise mission of the spacecrafts. The developed adaptive controllers through these methods used the principles of characteristics frequency stabilization and the reference model. In , an attitude adaptive control of satellites in el- liptic orbits is proposed. The paper presents a novel non certainty-equivalent adaptive controlsystem for the satellites pitch control. The adaptive law is based on the attractive manifold design using filtered signals for the synthesis. The developed work in  is devoted to the adaptive control of a flexible spacecraft in noisy environment. A new control law for a large angle rotational maneuver of the spacecraft is derived. The controlsystem includes a state predictor to generate the estimates of the unknown parameters to be used in the feedback law. The controller is synthesized using only the pitch angle and its first derivative. A new design of a simple adaptive system for the rotational maneuver and the vibration suppression of an orbiting spacecraft with flexible appendages is proposed in . The control output variable is chosen as the linear combination of the pitch angle and rate. A simple adaptive control law is derived for the pitch angle control and the elastic mode stabilization. The adaptation rule requires only four adjustable parameters and the structure of the controlsystem does not de- pend on the order of the truncated spacecraft model. The authors in  described a hybrid control scheme for a flexible spacecraft. To obtain good static and dynamic characteristics, the hybrid control scheme is put forward with a variable structure and an intelligent adaptive control method.
Deployment of multimodal visual sensors in a manufacturing factory may have some special challenges that video surveillance does not. Although the surveillance images are transferred through LAN/WAN for a large amount of nodes, the loss of one or two data packets or even one or two image frames will not cause any serious problems to its observer since human beings possess rather fantastic reasoning ability than computers. However, things are quite different for industrial processes. The loss of even one packet may cause the failure of the whole system, let alone the whole image frame. For example, if thermal image, which conveys the temperature signal, is used as a temperature feedback for a thermal management system, the measurement may become inaccurate when there are packet losses in the thermal image. Malfunction may be caused by the inaccuracy. Furthermore, a factory is usually noisier than the street in terms of the working environment for a camera. There may be thousands of machines running at the same time in a factory which may have electromagnetic interference with the camera, and hence further corrupts the performance of the vision guided controlsystem.
ABSTRACT: One of the most important issues in controlsystemdesign is to ensure the stability of the plant. PID controller used in industrial solutions still represents the most common controller in industry. However PID can only guess stability area and indicates stability zone by trial and error together with the experience of the designer. Decrement of system performance index leads to easier and better controlsystem stability. Integral time absolute error (ITAE) is one of the most criterion used to reduce system error and give the best PID gain values for a desired system response requirements. This paper discusses the steps used to obtain a proper PID gain parameters values using ITAE method.
ginal nonlinear system, described by Equations (1)-(4), will be simulated with each of three controllers in closed- loop form. In simulations, the inertia moments of satel- lites have 30 percent of uncertainty as shown in Figure 10. The simulation of the closed-loop system has done in two cases. In one case, the closed-loop system response is obtained to zero reference input and with T d equal to disturbance pulse, which is shown in Figure 11. In the other case, the closed-loop system response to a refer- ence sinus input with the amplitude of 15 degree in roll channel, 10 degree in pitch channel and 5 degree in yaw channel and 20 Hz frequency in the presence of space physical disturbances and measurement noise, is obtained to examine the performance of system in tracking. The RMS amount of attitude sensors’ noise of and their error are considered equal to 0.01 ˚.
topic and hence our work is a useful improvement. Our controller is mode-dependent and this may be unrealistic in some real-world situations where the system mode is inaccessible. So the problem of mode-independent control for hybrid systems has attracted a lot of attention and some excellent results have appeared (see e.g. [38, 39]). However, there are also some practical systems which are mode available or part available. In this case, the mode-independent results may be conservative due to the full negligence of mode information. In fact, some papers designed both mode-independent controllers and mode-dependent controllers, corresponding to the cases of mode inaccessible and mode accessible or part accessible, respectively (see e.g. ).
In the context of coalitional TU games, robustness and dynamics naturally arise in all the situations where the coalitions values are uncertain and time-varying, see e.g., . Robustness has to do with modeling coalitions’ values as unknown entities and this is in spirit with some literature on stochastic coalitional games , . However, we deviate from the latter works since the probability function generating the random coalitions values is unknown, and this is more in line with the concept of Unknown But Bounded (UBB) variables formalized in . It is worth to mention that this formulation shares some common elements with the recent literature on interval valued games , where the authors use intervals to describe coalitions values quite similar to what is done in this paper. The interval nature of coalitions’ values arises generally due to the optimistic and pessimistic expectations of the coalitions  when cooperation is achieved from a strategic form game. We also note some differences in that we focus here more on the time-varying nature of the coalitions’ values. In doing so, we also link the approach to the set invariance theory  and stochastic stability theory  which provides us some nice tools for stability analysis (see, e.g., the use of a Lyapunov function in the proof of Theorem 4.1).
We present three interesting applications of stochasticcontrol in finance. The first is a real option model that considers the optimal entry into and subsequent operation of a biofuel production facility. We derive the associated Hamilton Jacobi Bellman (HJB) equation for the entry and operating decisions along with the econometric analysis of the stochastic price inputs. We follow with a Monte Carlo analysis of the risk profile for the facility. The second application expands on the analysis of the biofuel facility to account for the associated regulatory and taxation uncertainty experienced by players in the renewables and energy industries. A federal biofuel production subsidy per gallon has been available to producers for many years but the subsidy price level has changed repeatedly. We model this uncertain price as a jump process. We present and solve the HJB equations for the associated multidimensional jump diffusion problem which also addresses the model uncertainty pervasive in real option problems such as these. The novel real option framework we present has many applications for industry practitioners and policy makers dealing with country risk or regulatory uncertainty—which is a very real problem in our current global environment. Our final application (which, although apparently different from the first two applications, uses the same tools) addresses the problem of producing reliable bid-ask spreads for derivatives in illiquid markets. We focus on the hedging of over the counter (OTC) equity derivatives where the underlying assets realistically have transaction costs and possible illiquidity which standard finance models such as Black- Scholes neglect. We present a model for hedging under market impact (such as bid-ask spreads, order book depth, liquidity) using temporary and permanent equity price impact functions and derive the associated HJB equations for the problem. This model transitions from continuous to impulse trading (control) with the introduction of fixed trading costs. We then price and hedge via the economically sound framework of utility indifference pricing. The problem of hedging under liquidity impact is an on-going concern of market makers following the Global Financial Crisis.
really a difficult task and also the optimum value change with the changing system operating conditions. Thus the gains of PI controller are optimized for improving damping performance significantly. Further H- infinite controller has been proposed that gives better stability to the system under abnormal conditions. This controller also provides large operating zone within which the system can operate without loss of generality.
With the rapid development of deep learning, the accuracy of object detection is dramatically increased. Image annotation becomes more important in Content-based Image Retrieval. In addition, different kinds of image hashing are developed. The image can be represented by a series of numbers, also known as hash. The hash can be used to obtain the similarity for image retrieval. The traditional visual feature vectors, such as shape descriptor, can also be used in image retrieval. This kind of information can be stored in a system as indexing for fast retrieval. Similar to relational database system, indexing plays an important role to speed up data retrieval. Therefore, database system needs to apply indexing in order to achieve fast retrieval. Storing multimedia, such as image or PDF, is different from relational database system. This article advocates a robust approach that there is no limitation to apply some of algorithms for indexing. The proposed architecture can be extended to add any algorithm in order to achieve fast retrieval. In addition, the systemdesign is considered to be used in internet environment. It can be easily integrated with the internet-based systems.
To better illustrate the benefits of having an algorithm to compute the entire stochasticstochastic growth path, consider the two solution methods adopted in Moro (2012) and Moro (2015). The working tool in both works is a two-sector growth model with non- homothetic preferences and exogenous stochastic TFP in the two sectors. However, the two papers resort to different solution methods to analyze the business-cycle effects of structural transformation. Moro (2012) performs standard RBC analysis around two steady states differing in the level of TFP but not in the stochastic process for TFP shocks in the two sectors. Due to non-homothetic preferences, a larger TFP level endogenously creates a larger share of services in steady-state. In turn, the different size of the share of services affects the response of endogenous variables to shocks. Thus, in this case the Euler equation is made stationary by removing the growth component of TFP. This amounts to imposing no future structural change in the expectation term. Moro (2015), instead, focuses on both growth and volatility together so that, to find a solution, it simplifies the model by dropping capital accumulation and assuming an exogenous growth rate for TFP in the two sectors. In this model TFP is given by a deterministic growth component and a stochastic cyclical component, and the growth path becomes a sequence of static equilibria. In this case there is no forward looking component in the household problem (i.e. no expectation term and no Euler equation) and the effect on investment on the cyclical properties of the economy is excluded. The method presented here allows to avoid such simplifications and to study the volatility properties of the multi-sector model along the entire growth path.
For grid connected operation, the controller is intended to supply a constant current output. The main aspect to consider in grid connected operation is synchronised with the grid voltage. For unity power factor operation, it is vital that the grid current reference signal is in phase with the grid voltage .This grid synchronization be able to be carried out by using a PLL. Fig.1 shows the control topology used.
This paper investigates the problem of robust H ∞ control for a class of switched stochastic systems with time delays under asynchronous switching, where the asynchronous switching means that the switching of the controllers has a lag to the switching of system modes. The parameter uncertainties are allowed to be norm bounded. Firstly, by using the average dwell time approach, the stability criterion and H ∞ performance analysis for the underlying systems are developed. Then, based on the obtained results, suﬃcient conditions for the existence of admissible
In this paper we have introduced a robustdesign process for a scalar model reference adaptive control (MRAC) algorithm. Different types of MRAC control rules have been reviewed and analysed in the frequency domain by using Bode plot analysis. Then a design process for MRAC has been developed for systems with plant settling times in the range 0.01-100 seconds which is relevant to a wide range of mechanical systems. By using this design method a robust adaptive window is obtained meaning
The MBMS video streaming delivery system is shown in Figure 6. In this case the source RTP packets are transmit- ted almost unmodified to the receiver. However, in addition a copy of the source RTP packet is forwarded to the FEC en- coder and placed in a so-called source block, a virtual two- dimensional array of width T bytes, referred to as encod- ing symbol length. Further RTP packets are filled into the source block until the second dimension of the source block, the height K determining the information length of the FEC code to be used, is reached. Each RTP packet starts at the beginning of a new row in the source block. The flexible sig- naling specified in  allows the adaptation of T for each session, as well as that of the height K for each source block to be encoded. After processing all original RTP packets to be protected within one source block, the FEC encoder gen- erates N - K repair symbols by applying a code over each byte column-wise. These repair symbols can be transmitted indi- vidually or as blocks of P symbols within a single RTP packet. Suﬃcient side information is added in payload headers of both, source and repair RTP packet, such that the receiver can insert correctly received source and repair RTP pack- ets in its encoding block. If su ﬃ cient data for this specific source block is received, the decoder can recover all pack- ets inserted in the encoding block, in particular the original source RTP packets. These RTP packets are forwarded to the RTP decapsulation process which itself hands the recovered application layer packets to the media decoder. Codes having been considered in the MBMS framework are Reed-Solomon codes , possibly extended to multiple dimensions as well as Raptor codes  which have some unique properties in