Erik-Jan Van Kampen

Erik-Jan Van Kampen
Delft University of Technology | TU · Department of Control and Operations (C&O)

PhD

About

212
Publications
63,440
Reads
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2,240
Citations
Additional affiliations
September 2011 - present
Delft University of Technology
Position
  • Professor (Assistant)
Education
February 2006 - September 2010
Delft University of Technology
Field of study
  • Aerospace Engineering
January 2004 - January 2006
Delft University of Technology
Field of study
  • Aerospace Engineering
September 1999 - December 2003
Delft University of Technology
Field of study
  • Aerospace Engineering

Publications

Publications (212)
Conference Paper
Full-text available
This paper develops an intelligent optimal stabilization control approach that can be applied to general flight control systems. The self-learning controller is developed based on dual heuristic programming (DHP) in cooperation with the event-triggered scheme to save computational load. Besides, the control inputs can be handled by the combination...
Presentation
Full-text available
This presentation corresponds to the paper presented in EuroGNC 2022.
Preprint
Full-text available
Enabling robots with the capability of assessing risk and making risk-aware decisions is widely considered a key step toward ensuring robustness for robots operating under uncertainty. In this paper, we consider the specific case of a nano drone robot learning to navigate an apriori unknown environment while avoiding obstacles under partial observa...
Preprint
Fault-tolerant flight control faces challenges, as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited system complexity due to their low sample efficiency. In this research, a model-free coupled-dynamics flight controller for a jet aircraft able to withstand multiple failur...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-1394.vid Control augmentation systems based on Incremental Nonlinear Dynamic Inversion (INDI) are able to provide high-performance nonlinear control without a holistic model. Considering an angular rate control law for a fixed-wing aircraft, only a control effectiveness (CE) model and angular...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-0790.vid Safe Curriculum Learning aims at improving safety and efficiency aspects of Reinforcement Learning (RL). Curricular RL approaches divide a task into stages of increasing complexity in order to increase efficiency. This paper proposes a black box safe curriculum learning architecture a...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-1597.vid Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control strategy, which has shown robustness against model uncertainties on various aerospace platforms. The sensor-based nature of the method brings attractive properties, which has made it popular in the last decade. I...
Conference Paper
Pdf available here: http://pure.tudelft.nl/ws/portalfiles/portal/104433325/6.2022_1429.pdf
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-1395.vid Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control law design strategy that is based on the principles of feedback linearization. Contrary to its non-incremental counterpart (NDI), this design method does not rely on the availability of a high-fidelity on-board m...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-0761.vid This paper presents a sampled-data form of the recently reformulated incremental nonlinear dynamic inversion (INDI) applied for robust spacecraft attitude control. INDI is a combined model- and sensor-based approach mostly applied for attitude control that only requires an accurate co...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-0793.vid Reinforcement learning (RL) equipped with neural networks has recently led to a wide range of successes in learning policies for unmanned aerial vehicle (UAV) navigation and control problems. The success of RL relies on two human-designed heuristics: appropriate action space definitio...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-2078.vid Fault-tolerant flight control faces challenges, as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited system complexity due to their low sample efficiency. In this research, a model-free coupled-dynamics fligh...
Article
Morphing structures have acquired much attention in the aerospace community because they enable an aircraft to actively adapt its shape during flight, leading to fewer emissions and fuel consumption. Researchers have designed, manufactured, and tested a morphing wing named SmartX-Alpha, which can actively alleviate loads while achieving the optimal...
Article
Full-text available
In this paper, we establish an event-triggered intelligent control scheme with a single critic network, to cope with the optimal stabilization problem of nonlinear aeroelastic systems. The main contribution lies in the design of a novel triggering condition with input constraints, avoiding the Lipschitz assumption on the inverse hyperbolic tangent...
Conference Paper
Full-text available
Pneumatic cylinders provide an environment-friendly actuation means by minimizing the leakage of any harmful industrial fluids, as occurs for hydraulic actuators. However, pneumatic actuation has not been utilized widely for industrial servo applications due to its highly nonlinear nature. Incremental nonlinear dynamic inversion (INDI) is a form of...
Article
Full-text available
This paper develops an event-triggered optimal control method that can deal with asymmetric input constraints for nonlinear discrete-time systems. The implementation is based on an explainable global dual heuristic programming (XGDHP) technique. Different from traditional GDHP, the required derivatives of cost function in the proposed method are co...
Article
Full-text available
This paper aims to present a comparative analysis of the two most utilized graph-based and sampling-based algorithms and their variants, in view of 3D UAV path planning in complex indoor environment. The findings of this analysis outline the usability of the methods and can assist future UAV path planning designers to select the best algorithm with...
Article
Full-text available
In this paper, we provide an overview of how Safe-by-Design is conceived and applied in practice in a large number of engineering disciplines. We discuss the differences, commonalities, and possibilities for mutual learning found in those practices and identify several ways of putting those disciplinary outlooks in perspective. The considered engin...
Article
Full-text available
The scarcity of information regarding dynamics and full-state feedback increases the demand for a model-free control technique that can cope with partial observability. To deal with the absence of prior knowledge of system dynamics and perfect measurements, this paper develops a novel intelligent control scheme by combining global dual heuristic pr...
Conference Paper
Unmanned Aerial Vehicles (UAVs) are taking active roles in personal, commercial, industrial and military applications due to their efficiency, availability and low-cost. UAVs must operate safely and in real-time in both static and dynamic environments. An extensive literature review, defines the dynamic environment term, the need for dynamic path p...
Conference Paper
Full-text available
Reinforcement learning is an appealing approach for adaptive, fault-tolerant flight control, but is generally plagued by its need for accurate system models and lengthy offline training phases. The novel Incremental Dual Heuristic Programming (IDHP) method removes these dependencies by using an online-identified local system model. A recent impleme...
Conference Paper
Full-text available
Linear Approximate Dynamic Programming (LADP) and Incremental Approximate Dynamic Programming (IADP) are Reinforcement Learning methods that seek to contribute to the field of Adaptive Flight Control. This paper assesses their performance and convergence, as well as the impact of sensor noise on policy convergence, online system identification, per...
Conference Paper
Unmanned Aerial Vehicles (UAVs) are being integrated into all spheres of life varying in a wide range of applications from military to civil applications. In such applications, UAVs are expected to operate safely in the presence of uncertainties present in the dynamic environment and the UAV itself. Based on literature different uncertainty sources...
Conference Paper
Full-text available
OnlineAdaptive Flight Control is interesting in the context of growing complexity of aircraft systems and their adaptability requirements to ensure safety. An Incremental Approximate Dynamic Programming (iADP) controller combines reinforcement learning methods, optimal control and online identified incremental model to achieve optimal adaptive cont...
Conference Paper
Full-text available
Conventional discrete reinforcement learning methods fail in providing satisfactory performance for online Flight Control Systems (FCSs). The lack of efficiency of the discrete controller in exploration for finding the optimal policy, the so-called problem of ’curse of dimensionality’, results in an approach that is not suitable for online implemen...
Conference Paper
Full-text available
Reinforcement learning is used as a type of adaptive flight control. Adaptive Critic Design (ACD) is a popular approach for online reinforcement learning control due to its explicit generalization of the policy evaluation and the policy improvement elements. A variant of ACD, Incremental Dual Heuristic Programming (IDHP) has previously been develop...
Article
Full-text available
To manage air data sensor fault detection and diagnosis in the presence of atmospheric turbulence is challenging since the effects of faults and turbulence are coupled. Existing fault detection and diagnosis approaches can not decouple the faults from the turbulence. To address this challenge, this paper first proposes a novel kinematic model which...
Conference Paper
Full-text available
Sufficient information about system dynamics and inner states is often unavailable to aerospace system controllers, which requires model-free and output feedback control techniques , respectively. This paper presents a novel self-learning control algorithm to deal with these two problems by combining the advantages of heuristic dynamic programming...
Conference Paper
Full-text available
Optimal tracking is a widely researched control problem, but the unavailability of sufficient information referring to system dynamics brings challenges. In this paper, an optimal tracking control method is proposed for an unknown launch vehicle based on the global dual heuristic programming technique. The nonlinear system dynamics is identified by...
Article
Full-text available
Heuristic dynamic programming is a class of reinforcement learning, which has been introduced to aerospace engineering to solve nonlinear, optimal adaptive control problems. However, it requires an off-line learning stage to train a global system model to represent the system dynamics. This paper uses an incremental model in heuristic dynamic progr...
Article
Full-text available
Lack of trust and lack of acceptance caused by strategic mismatches in problem-solving have been identified as obstacles in the introduction of workload-alleviating automation in air traffic control. One possible way to overcome these obstacles is by creating automation capable of providing personalized advisories conformal to the individual contro...
Article
Full-text available
A novel adaptive dynamic programming method, called incremental model-based global dual heuristic programming, is proposed to generate a self-learning adaptive flight controller, in the absence of sufficient prior knowledge of system dynamics. An incremental technique is employed for online local dynamics identification, instead of the artificial n...
Article
Full-text available
This paper proposes a novel adaptive dynamic programming method, called Incremental model-based Global Dual Heuristic Programming, to generate a self-learning adaptive controller, in the absence of sufficient prior knowledge of system dynamics. An incremental technique is employed for online model identification, instead of the artificial neural ne...
Article
This paper proposes incremental nonsingular terminal sliding mode control for a class of multi-input and multi-output nonlinear systems considering model uncertainties, external disturbances, and sudden actuator faults. This method is free from singularity because it does not involve any negative fractional power. The convergence time in both reach...
Conference Paper
Full-text available
For mitigating the chattering effect in the sliding mode control (SMC), many adaption mechanisms have been proposed to reduce the switching gains. However, less attention is paid to the control structure, which influences the resulting uncertainty term and determines the minimum possible gains. This paper compares three control structures for induc...
Presentation
Full-text available
Lack of trust has been identified as an obstacle in the introduction of workload-alleviating automation in air traffic control. The work presented in this paper describes a concept to generate individual-sensitive resolution advisories for air traffic conflicts, with the aim of increasing acceptance by adapting advisories to different controller st...
Conference Paper
Full-text available
Lack of trust has been identified as an obstacle in the introduction of workload-alleviating automation in air traffic control. The work presented in this paper describes a concept to generate individual-sensitive resolution advisories for air traffic conflicts, with the aim of increasing acceptance by adapting advisories to different controller st...
Conference Paper
Full-text available
In this work interval analysis is applied to find the trimpoints of the Innovative Control Effectors aircraft model. At low speed the method is capable of finding interval enclosures of single trim points with a high accuracy. At higher speeds the found accelerations are larger. When looking for a full trim set the method finds continuous bounds on...
Article
Full-text available
This paper designs an incremental nonlinear dynamic inversion control law for free-flying flexible aircraft, which can regulate rigid-body motions, alleviate gust loads, reduce the wing root bending moment, and suppress elastic modes. By fully exploring the sensor measurements, the model dependency of the proposed control law can be reduced while m...
Article
Full-text available
As a sensor-based control method, Incremental Nonlinear Dynamic Inversion (INDI) has been applied to various aerospace systems and shown desirable robust performance against aerodynamic model uncertainties. However, its previous derivation based on the time scale separation principle has some limitations. There is also a need for stability and robu...
Article
This paper proposes an Incremental Sliding Mode Control driven by Sliding Mode Disturbance Observers (INDI-SMC/SMDO), with application to a quadrotor fault tolerant control problem. By designing the SMC/SMDO based on the control structure of the sensor-based Incremental Nonlinear Dynamic Inversion (INDI), instead of the model-based Nonlinear Dynami...
Conference Paper
Fault-tolerant flight control has the potential of improving the aircraft survivability in real life. This paper proposes an Incremental Backstepping Sliding Mode Control (IBSMC) framework for multi-input/output nonlinear strict-feedback systems considering model uncertainties, sudden faults, and external disturbances. This approach is a hybridizat...
Conference Paper
This paper discusses the design, implementation and flight testing of an incremental Backstep-ping (IBS) based manual flight control law with angular accelerometer (AA) feedback. The main advantages of incremental control laws are that they only require a partial model of the system and are of low complexity. Incremental control laws for aircraft rot...
Article
Full-text available
This paper proposes a novel control framework that combines the recently reformulated incremental nonlinear dynamic inversion with (higher-order) sliding-mode controllers/observers, for generic multi-input/multi-output nonlinear systems, named incremental sliding-mode control. As compared to the widely used approach that designs (higher-order) slid...
Article
Full-text available
Autonomous guidance and navigation problems often have high-dimensional spaces, multiple objectives, and consequently a large number of states and actions, which is known as the ‘curse of dimensionality’. Furthermore, systems often have partial observability instead of a perfect perception of their environment. Recent research has sought to deal wi...
Article
Full-text available
Approximate dynamic programming is a class of reinforcement learning, which solves adaptive, optimal control problems and tackles the curse of dimensionality with function approximators. Within this category, linear approximate dynamic programming provides a model-free control method by systematically using a quadratic cost-to-go function. Although...
Conference Paper
Full-text available
Nowadays, the complexity of high speed civil transport and highly-augmented rotorcraft, has led to an increase in the chances of encountering unwanted unstable phenomena, such as the so called Aircraft/Rotorcraft-Pilot Couplings (A/RPCs) or Pilot-Induced Oscillations (PIOs), whose unpredictability has given rise to a serious problem concerning the...
Article
Full-text available
Dual heuristic programming has gained an increasing interest in recent years because it provides an effective process for optimal adaptive control of uncertain nonlinear systems. However, it requires an off-line stage to train a global system model from a representative model, which is often infeasible to obtain in practice. This paper presents a n...
Article
Full-text available
The research presented in this paper focuses on the effects of structural failures on the safe flight envelope of an aircraft, which is the set of all the states in which safe maneuver of the aircraft can be assured. Nonlinear reachability analysis based on an optimal control formulation is performed to estimate the safe flight envelope using actua...
Conference Paper
This paper describes the design, implementation and flight testing of flight control laws based on Incremental nonlinear Dynamic Inversion (INDI). The method compares commanded and measured accelerations to compute increments on the current control deflections. This results in highly robust control solutions with respect to model uncertainties as w...