Adaptive dynamic programming (ADP) is a sub-field of approximate dynamic programming that deals with the adaptive control of continuous nonlinear dynamic systems. Its origins stem from dynamic programming in optimal control, but it is extended into a form where approximations are used to reduce the curse of dimensionality and reduce the need for model knowledge. ADP is also considered to be one of the main reinforcement learning (RL) approaches since it uses information obtained from interaction with the environment to improve its policy. RL in general and ADP in particular are well suited for application to autonomous aerospace systems, since they allow adaptive control in case of uncertainties or faults in the system, even if the fault is of a type that is not anticipated during the control design. This chapter first gives a brief historical overview of ADP applications to flight control tasks. After that, four recent advances of ADP for flight control are presented.

Nowadays, due to the advancement of design and manufacturing technology, there are many consumer products with high reliability. Similarly, the competition in the business sector influences the product development time to become shorter and that makes it difficult for manufacturers to evaluate the reliability of current products before new products are released to the market. This phenomenon is manifested in the lighting industry, especially for the high power white light-emitting diodes (LEDs) as these products have a long lifetime and high reliability. Currently, the standard to predict the lifetime of LEDs is based on a deterministic nonlinear least squares method which has low prediction accuracy. To overcome this, degradation models are being used to study the reliability of such products, considering the uncertainties and the quality characteristics whose degradation over a period of time can be related to the product lifetime. A stochastic approach based on gamma distributed degradation (GDD) is proposed in this study to estimate the long-term lumen degradation lifetime of phosphor-converted white LEDs. An accelerated thermal degradation test was designed to gather luminous flux degradation data which was analyzed based on maximum likelihood estimation (MLE) and the method of moments (MM) to estimate the parameters for the GDD model. The MLE method has shown superiority over MM in terms of the estimation of the model parameters due to its iterative algorithm being likely to find the optimal estimation. The lifetime prediction results show that the accuracy of the proposed method is much better than the TM-21 nonlinear least squares (NLS) approach which makes it promising for future industrial applications.

In this paper, a physics of failure-based prediction method is combined with statistical models to consider the impact of current crowding and current droop effects on the reliability of LED arrays. Electronic-thermal models of LEDs are utilized to obtain the operation conditions under the influences of current crowding and current droop. A Markov chain-based model is used to calculate the probability distribution of each failure mode, including the lumen decay and catastrophic failure. Two types of LEDs were selected for a numerical study. The proposed prediction method provides the realistic reliability prediction results. It is found that the properties of LEDs have a great impact on their hazard rates of LED arrays. The equivalent resistance, third-order non-radiative coefficient, and radiative coefficient of LEDs are critical to the reliability of an LED array.

This work studies the effect of randomness of LED's lumen depreciation on reliability of the entire LED lamp. An integrated LED light bulb is selected as carrier of the proposed method. A PoF based lumen depreciation model and electronic-thermal simulations are introduced for reliability prediction. The normal distribution is used to describe the statistical distribution of LEDs. The probabilities of the driver's catastrophic failures and lumen can then be obtained by Monte Carlo simulations by considering the increase of lamp's temperature. The effect of the lumen depreciation to the entire lamp is studied with two scenarios: constant light mode and constant current mode.

In this paper, an integrated LED lamp with an electrolytic capacitor-free driver is considered to study the coupling effects of both LED and driver's degradations on lamp's lifetime. An electrolytic capacitor-less buck-boost driver is used. The physics of failure (PoF) based electronic thermal simulation is carried out to simulate the lamp's lifetime in three different scenarios: Scenario 1 considers LED degradation only, Scenario 2 considers the driver degradation only, and Scenario 3 considers both degradations from LED and driver simultaneously. When these two degradations are both considered, the lamp's lifetime is reduced by about 22% compared to the initial target of 25,000 h. The results of Scenario 1 and 3 are close to each other. Scenario 2 gives erroneous results in terms of luminous flux as the LED's degradation over time is not taken into consideration. This implies that LED's degradation must be taken into considerations when LED and driver's lifetimes are comparable.

This paper studies the interaction of catastrophic failure of the driver and LED luminous flux decay for an integrated LED lamp with an electrolytic capacitor-free LED driver. Electronic thermal simulations are utilized to obtain the lamp's dynamic history of temperature and current for two distinct operation modes: constant current mode (CCM) and constant light output (CLO) mode, respectively. Driver's mean time to failure (MTTF) and the LED's lifetime in terms of luminous flux are calculated. Under CLO mode, the LED's current increases exponentially to maintain the constant light output. As a result, the junction temperatures of LEDs, MOSFETs, and power diodes in driver rise significantly, leading to a much shorter MTTF and faster luminous flux depreciation. However, under the CCM, the junction temperatures of LEDs, MOSFETs, and diodes change modestly; therefore, the driver's MTTF and LED's luminous flux decay are not affected much by the variation of temperatures during LED's degradation process.

In this work, a physics-of-failure (PoF) reliability prediction methodology is combined with statistical models to consider the interaction between the lumen depreciation and catastrophic failures of LEDs. The current in each LED may redistribute when the catastrophic failure occurs in one of LEDs in an array, thus affecting the operation conditions of the entire LED array. A physics-of-failure based reliability prediction methodology is combined with statistical models to consider the interaction between the lumen depreciation and the catastrophic failure. Electronic-thermal simulations are utilized to obtain operation conditions, including temperature and current. Meanwhile, statistical models are applied to calculate possibilities of the catastrophic failure in different operation conditions.