Publications

1. “Security Allocation in Networked Control Systems under Stealthy Attacks”.
   A. T. Nguyen, A. M. H. Teixeira, and A. Medvedev.
   IEEE Trans. Control of Network Systems (Submitted)
   ABS ARXIV BIB

   This paper considers the problem of security allocation in a networked control system under stealthy attacks in which the system is comprised of interconnected subsystems represented by vertices. A malicious adversary selects a single vertex on which to conduct a stealthy data injection attack to maximally disrupt the local performance while remaining undetected. On the other hand, a defender selects several vertices on which to allocate defense resources against the adversary. First, the objectives of the adversary and the defender with uncertain targets are formulated in probabilistic ways, resulting in an expected worst-case impact of stealthy attacks. Next, we provide a graph-theoretic necessary and sufficient condition under which the cost for the defender and the expected worst-case impact of stealthy attacks are bounded. This condition enables the defender to restrict the admissible actions to a subset of available vertex sets. Then, we cast the problem of security allocation in a Stackelberg game-theoretic framework. Finally, the contribution of this paper is highlighted by utilizing the proposed admissible actions of the defender in the context of large-scale networks. A numerical example of a 50-vertex networked control system is presented to validate the obtained results.

   @article{Tung_TCNS2024,
     author = {Nguyen, A. T. and Teixeira, A. M. H. and Medvedev, A.},
     journal = {IEEE Trans. Control of Network Systems (Submitted)},
     number = {},
     pages = {},
     title = {Security Allocation in Networked Control Systems under Stealthy Attacks},
     volume = {},
     year = {},
     published = {0},
     tag = {10005}
   }

2023

1. “Security Allocation in Networked Control Systems”.
   A. T. Nguyen.
   Licentiate thesis, Uppsala University, Uppsala, Sweden, 2023
   PDF ABS BIB

   Sustained use of critical infrastructure, such as electrical power and water distribution networks, requires efficient management and control. Facilitated by the advancements in computational devices and non-proprietary communication technology, such as the Internet, the efficient operation of critical infrastructure relies on network decomposition into interconnected subsystems, thus forming networked control systems. However, the use of public and pervasive communication channels leaves these systems vulnerable to cyber attacks. Consequently, the critical infrastructure is put at risk of suffering operation disruption and even physical damage that would inflict financial costs as well as pose a hazard to human health. Therefore, security is crucial to the sustained efficient operation of critical infrastructure. This thesis develops a framework for evaluating and improving the security of networked control systems in the face of cyber attacks. The considered security problem involves two strategic agents, namely a malicious adversary and a defender, pursuing their specific and conflicting goals. The defender aims to efficiently allocate defense resources with the purpose of detecting malicious activities. Meanwhile, the malicious adversary simultaneously conducts cyber attacks and remains stealthy to the defender. We tackle the security problem by proposing a game-theoretic framework and characterizing its main components: the payoff function, the action space, and the available information for each agent. Especially, the payoff function is characterized based on the output-to-output gain security metric that fully explores the worst-case attack impact. Then, we investigate the properties of the game and how to efficiently compute its equilibrium. Given the combinatorial nature of the defender’s actions, one important challenge is to alleviate the computational burden. To overcome this challenge, the thesis contributes several system- and graph-theoretic conditions that enable the defender to shrink the action space, efficiently allocating the defense resources. The effectiveness of the proposed framework is validated through numerical examples.

   @phdthesis{Nguyen_Lic2023,
     author = {Nguyen, Anh Tung},
     title = {Security Allocation in Networked Control Systems},
     school = {Uppsala University},
     year = {2023},
     address = {Uppsala, Sweden},
     month = oct,
     type = {Licentiate thesis},
     tag = {10005}
   }

2. “Secure State Estimation with Asynchronous Measurements against Malicious Measurement-data and Time-stamp Manipulation”.
   Z. Li, A. T. Nguyen, A. M. H. Teixeira, Y. Mo, and K. H. Johansson.
   IEEE Conference on Decisions and Control (CDC), 2023
   PDF ABS DOI ARXIV BIB

   This paper proposes a secure state estimation scheme with non-periodic asynchronous measurements for linear continuous-time systems under false data attacks on the measurement transmit channel. After sampling the output of the system, a sensor transmits the measurement information in a triple composed of sensor index, time-stamp, and measurement value to the fusion center via vulnerable communication channels. The malicious attacker can corrupt a subset of the sensors through (i) manipulating the time-stamp and measurement value; (ii) blocking transmitted measurement triples; or (iii) injecting fake measurement triples. To deal with such attacks, we propose the design of local estimators based on observability space decomposition, where each local estimator updates the local state and sends it to the fusion center after sampling a measurement. Whenever there is a local update, the fusion center combines all the local states and generates a secure state estimate by adopting the median operator. We prove that local estimators of benign sensors are unbiased with stable covariance. Moreover, the fused central estimation error has bounded expectation and covariance against at most p corrupted sensors as long as the system is 2p-sparse observable. The efficacy of the proposed scheme is demonstrated through an application on a benchmark example of the IEEE 14-bus system.

   @inproceedings{Li_CDC2023,
     address = {},
     author = {Li, Z. and Nguyen, A. T. and Teixeira, A. M. H. and Mo, Y. and Johansson, K. H.},
     booktitle = {IEEE Conference on Decisions and Control (CDC)},
     title = {Secure State Estimation with Asynchronous Measurements against Malicious  Measurement-data and Time-stamp Manipulation},
     year = {2023},
     doi = {10.1109/CDC49753.2023.10383571},
     published = {1},
     tag = {10005}
   }

3. “Optimal Detector Placement in Networked Control Systems under Cyber-attacks with Applications to Power Networks”.
   A. T. Nguyen, S. C. Anand, A. M. H. Teixeira, and A. Medvedev.
   IFAC World Congress, 2023
   PDF ABS DOI ARXIV BIB

   This paper proposes a game-theoretic method to address the problem of optimal detector placement in a networked control system under cyber-attacks. The networked control system is composed of interconnected agents where each agent is regulated by its local controller over unprotected communication, which leaves the system vulnerable to malicious cyber-attacks. To guarantee a given local performance, the defender optimally selects a single agent on which to place a detector at its local controller with the purpose of detecting cyber-attacks. On the other hand, an adversary optimally chooses a single agent on which to conduct a cyber-attack on its input with the aim of maximally worsening the local performance while remaining stealthy to the defender. First, we present a necessary and sufficient condition to ensure that the maximal attack impact on the local performance is bounded, which restricts the possible actions of the defender to a subset of available agents. Then, by considering the maximal attack impact on the local performance as a game payoff, we cast the problem of finding optimal actions of the defender and the adversary as a zero-sum game. Finally, with the possible action sets of the defender and the adversary, an algorithm is devoted to determining the Nash equilibria of the zero-sum game that yield the optimal detector placement. The proposed method is illustrated on an IEEE benchmark for power systems.

   @inproceedings{NguyenIFAC2023,
     address = {},
     author = {Nguyen, A. T. and Anand, S. C. and Teixeira, A. M. H. and Medvedev, A.},
     booktitle = {IFAC World Congress},
     title = {Optimal Detector Placement in Networked Control Systems under Cyber-attacks with Applications to Power Networks},
     tag = {10005},
     year = {2023},
     doi = {10.1016/j.ifacol.2023.10.1896},
   }

4. “Distributed formation trajectory planning for multi-vehicle systems”.
   B. Nguyen, T. Nghiem, L. Nguyen, et al.
   2023 American Control Conference (ACC), 2023, pp. 1325–1330
   PDF ABS DOI BIB

   This paper addresses the problem of distributed formation trajectory planning for multi-vehicle systems with collision avoidance among vehicles. Unlike some previous distributed formation trajectory planning methods, our proposed approach offers great flexibility in handling computational tasks for each vehicle when the global formation of all the vehicles changes. It affords the system the ability to adapt to the computational capabilities of the vehicles. Furthermore, global formation constraints can be handled at any selected vehicles. Thus, any formation change can be effectively updated without recomputing all local formations at all the vehicles. To guarantee the above features, we first formulate a dynamic consensus-based optimization problem to achieve desired formations while guaranteeing collision avoidance among vehicles. Then, the optimization problem is effectively solved by ADMM-based or alternating projection-based algorithms, which are also presented. Theoretical analysis is provided not only to ensure the convergence of our method but also to show that the proposed algorithm can surely be implemented in a fully distributed manner. The effectiveness of the proposed method is illustrated by a numerical example of a 9-vehicle system.

   @inproceedings{nguyen2023distributed,
     title = {Distributed formation trajectory planning for multi-vehicle systems},
     author = {Nguyen, Binh and Nghiem, Truong and Nguyen, Linh and Nguyen, Tung and La, Hung and Sookhak, Mehdi and Nguyen, Thang},
     booktitle = {2023 American Control Conference (ACC)},
     pages = {1325--1330},
     year = {2023},
     organization = {IEEE},
     doi = {10.23919/ACC55779.2023.10156635}
   }

5. “Real-time distributed trajectory planning for mobile robots”.
   B. Nguyen, T. Nghiem, L. Nguyen, A. T. Nguyen, and T. Nguyen.
   IFAC-PapersOnLine, vol. 56, no. 2, pp. 2152–2157, 2023
   PDF ABS DOI BIB

   Efficiently planning trajectories for nonholonomic mobile robots in formation tracking is a fundamental yet challenging problem. Nonholonomic constraints, complexity in collision avoidance, and limited computing resources prevent the robots from being practically deployed in realistic applications. This paper addresses these difficulties by modeling each mobile platform as a nonholonomic motion and formulating trajectory planning as an optimization problem using model predictive control (MPC). That is, the optimization problem is subject to both nonholonomic motions and collision avoidance. To reduce computing costs in real time, the nonholonomic constraints are convexified by finding the closest nominal points to the nonholonomic motion, which are then incorporated into a convex optimization problem. Additionally, the predicted values from the previous MPC step are utilized to form linear avoidance conditions for the next step, preventing collisions among robots. The formulated optimization problem is solved by the alternating direction method of multiplier (ADMM) in a distributed manner, which makes the proposed trajectory planning method scalable. More importantly, the convergence of the proposed planning algorithm is theoretically proved while its effectiveness is validated in a synthetic environment.

   @article{nguyen2023real,
     title = {Real-time distributed trajectory planning for mobile robots},
     author = {Nguyen, Binh and Nghiem, Truong and Nguyen, Linh and Nguyen, Anh Tung and Nguyen, Thang},
     journal = {IFAC-PapersOnLine},
     volume = {56},
     number = {2},
     pages = {2152--2157},
     year = {2023},
     publisher = {Elsevier},
     doi = {10.1016/j.ifacol.2023.10.1120}
   }

2022

1. “A Zero-Sum Game Framework for Optimal Sensor Placement in Uncertain Networked Control Systems under Cyber-Attacks”.
   A. T. Nguyen, S. C. Anand, and A. M. H. Teixeira.
   IEEE Conference on Decision and Control (CDC), 2022
   PDF ABS DOI ARXIV BIB

   This paper proposes a game-theoretic approach to address the problem of optimal sensor placement against an adversary in uncertain networked control systems. The problem is formulated as a zero-sum game with two players, namely a malicious adversary and a detector. Given a protected performance vertex, we consider a detector, with uncertain system knowledge, that selects another vertex on which to place a sensor and monitors its output with the aim of detecting the presence of the adversary. On the other hand, the adversary, also with uncertain system knowledge, chooses a single vertex and conducts a cyber-attack on its input. The purpose of the adversary is to drive the attack vertex as to maximally disrupt the protected performance vertex while remaining undetected by the detector. As our first contribution, the game payoff of the above-defined zero-sum game is formulated in terms of the Value-at-Risk of the adversary’s impact. However, this game payoff corresponds to an intractable optimization problem. To tackle the problem, we adopt the scenario approach to approximately compute the game payoff. Then, the optimal monitor selection is determined by analyzing the equilibrium of the zero-sum game. The proposed approach is illustrated via a numerical example of a 10-vertex networked control system.

   @inproceedings{NguyenCDC2022,
     address = {},
     author = {Nguyen, A. T. and Anand, S. C. and Teixeira, A. M. H.},
     booktitle = {IEEE Conference on Decision and Control (CDC)},
     title = {A Zero-Sum Game Framework for Optimal Sensor Placement in Uncertain Networked Control Systems under Cyber-Attacks},
     year = {2022},
     doi = {10.1109/CDC51059.2022.9992468},
     tag = {10005}
   }

2. “A Single-Adversary-Single-Detector Zero-Sum Game in Networked Control Systems”.
   A. T. Nguyen, A. M. H. Teixeira, and A. Medvedev.
   IFAC Conference on Networked Systems (NecSys), 2022
   PDF ABS DOI ARXIV BIB

   This paper proposes a game-theoretic approach to address the problem of optimal sensor placement for detecting cyber-attacks in networked control systems. The problem is formulated as a zero-sum game with two players, namely a malicious adversary and a detector. Given a protected target vertex, the detector places a sensor at a single vertex to monitor the system and detect the presence of the adversary. On the other hand, the adversary selects a single vertex through which to conduct a cyber-attack that maximally disrupts the target vertex while remaining undetected by the detector. As our first contribution, for a given pair of attack and monitor vertices and a known target vertex, the game payoff function is defined as the output-to-output gain of the respective system. Then, the paper characterizes the set of feasible actions by the detector that ensures bounded values of the game payoff. Finally, an algebraic sufficient condition is proposed to examine whether a given vertex belongs to the set of feasible monitor vertices. The optimal sensor placement is then determined by computing the mixed-strategy Nash equilibrium of the zero-sum game through linear programming. The approach is illustrated via a numerical example of a 10-vertex networked control system with a given target vertex.

   @inproceedings{NguyenNecsys2022,
     address = {},
     author = {Nguyen, A. T. and Teixeira, A. M. H. and Medvedev, A.},
     booktitle = {IFAC Conference on Networked Systems (NecSys)},
     title = {A Single-Adversary-Single-Detector Zero-Sum Game in Networked Control Systems},
     year = {2022},
     doi = {10.1016/j.ifacol.2022.07.234},
     tag = {10005},
   }

2020

1. “Dynamic event-triggered time-varying formation control of second-order dynamic agents: Application to multiple quadcopters systems”.
   A. T. Nguyen, T. B. Nguyen, and S. K. Hong.
   Applied Sciences, vol. 10, no. 8, p. 2814, 2020
   PDF ABS DOI BIB

   This paper investigates the problem of the time-varying formation control of a second-order dynamic agent based on a distributed dynamic event-triggered algorithm. In this problem, each agent can exchange the information of its position and velocity with its neighbors via limited communication ability. Our approach provides a new dynamic event triggering mechanism to reduce the number of triggering times while maintaining satisfactory control performance. Further, a novel Lyapunov function is proposed to guarantee that the group of agents asymptotically tracks the desired time-varying formation trajectory. The practical applicability of the event triggering mechanism is also indicated by excluding the Zeno behavior in the proposed control algorithm. Finally, the validity and effectiveness of the proposed method are demonstrated via illustrative examples of the time-varying formation flight for six quadcopters.

   @article{nguyen2020dynamic,
     title = {Dynamic event-triggered time-varying formation control of second-order dynamic agents: Application to multiple quadcopters systems},
     author = {Nguyen, Anh Tung and Nguyen, Thanh Binh and Hong, Sung Kyung},
     journal = {Applied Sciences},
     volume = {10},
     number = {8},
     pages = {2814},
     year = {2020},
     publisher = {MDPI},
     doi = {10.3390/app10082814}
   }

2019

1. “Quadcopter adaptive trajectory tracking control: A new approach via backstepping technique”.
   A. T. Nguyen, N. Xuan-Mung, and S.-K. Hong.
   Applied Sciences, vol. 9, no. 18, p. 3873, 2019
   PDF ABS DOI BIB

   Nowadays, quadcopter unmanned aerial vehicles play important roles in several real-world applications and the improvement of their control performance has become an increasingly attractive topic of a great number of studies. In this paper, we present a new approach for the design and stability analysis of a quadcopter adaptive trajectory tracking control. Based on the quadcopter nonlinear dynamics model which is obtained by using the Euler–Lagrange approach, the tracking controller is devised via the backstepping control technique. Besides, an adaptive law is proposed to deal with the system parameterized uncertainties and to guarantee that the control input is finite. In addition, the vehicle’s vertical descending acceleration is ensured to not exceed the gravitational acceleration by making use of a barrier Lyapunov function. It is shown that the suitable parameter estimator is stable and the tracking errors are guaranteed to be asymptotically stable simultaneously. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our method to that of existing approaches. The simulation results demonstrate the effectiveness of the proposed algorithm.

   @article{nguyen2019quadcopter,
     title = {Quadcopter adaptive trajectory tracking control: A new approach via backstepping technique},
     author = {Nguyen, Anh Tung and Xuan-Mung, Nguyen and Hong, Sung-Kyung},
     journal = {Applied Sciences},
     volume = {9},
     number = {18},
     pages = {3873},
     year = {2019},
     publisher = {MDPI},
     doi = {10.3390/app9183873}
   }

2. “A machine learning-based approach for the prediction of electricity consumption”.
   D. H. Nguyen and A. T. Nguyen.
   2019 12th Asian Control Conference (ASCC), 2019, pp. 1301–1306
   PDF ABS BIB

   Balancing the power supply and demand is one of the most fundamental and important problems for the operation and control of any electric power grid. There are multiple ways to guarantee the supply-demand balance, but in this research we focus on one specific method to facilitate it namely the prediction of electricity consumption, which is widely used by utility companies or system operators. It is known that this prediction is challenging because of many reasons, for example, inexact weather forecasts, uncertain consumers’ behaviors, etc. Hence, analytical and linear models of electricity consumption might not be able to deal with such issues well. This paper therefore presents a machine learning-based approach to predict electricity consumption, in which an improved radial basis function neural network (iRBF-NN) is proposed, whose inputs are time sampling points, temperature, and humidity associated with the consumption. The parameters of this iRBF-NN are sought by solving an optimization problem where four types of cost functions are used and compared on their performances and computational costs. Afterward, the derived model is employed to predict the future electricity consumption based on the hourly forecasts of temperature and humidity. Finally, simulation results for realistic data in Tokyo are presented to illustrate the efficiency of the proposed approach.

   @inproceedings{nguyen2019machine,
     title = {A machine learning-based approach for the prediction of electricity consumption},
     author = {Nguyen, Dinh Hoa and Nguyen, Anh Tung},
     booktitle = {2019 12th Asian Control Conference (ASCC)},
     pages = {1301--1306},
     year = {2019},
     organization = {IEEE},
   }

3. “An Approach for The Electricity Consumption Prediction based on Artificial Neural Network”.
   D. H. Nguyen and A. T. Nguyen.
   2019 SICE International Symposium on Control Systems (SICE ISCS), 2019, pp. 78–83
   PDF ABS DOI BIB

   This paper studies the day-ahead prediction of electricity consumption for power supply-demand balance in electric power networks. To handle the uncertainties in weather forecast and the nonlinearity relation between the electricity consumption and the weather conditions, this paper proposes a Radial Basis Function like Artificial Neural Network (RBF-like ANN) model with temperature, humidity, and sampling times as inputs. Then the Least Absolute Deviation, i.e., the L 1 norm condition, is employed as the optimization cost which is minimized in the model training process. To solve the L 1 optimization problem, two approaches, namely least square (L 2 ) based and alternating direction method of multipliers (ADMM), are utilized and compared. The simulations on real data collected in California shows that the latter approach performs better, and the number of neurons does not affect much to the prediction performance of the latter approach while it does influence on that of the former approach. Further, the proposed RBF-like ANN model equipped with ADMM solving approach provides reasonably good prediction of the electricity consumption in spite of the imprecise weather forecast.

   @inproceedings{nguyen2019approach,
     title = {An Approach for The Electricity Consumption Prediction based on Artificial Neural Network},
     author = {Nguyen, Dinh Hoa and Nguyen, Anh Tung},
     booktitle = {2019 SICE International Symposium on Control Systems (SICE ISCS)},
     pages = {78--83},
     year = {2019},
     organization = {IEEE},
     doi = {10.23919/SICEISCS.2019.8758717}
   }

4. “An adaptive backstepping trajectory tracking control of a tractor trailer wheeled mobile robot”.
   N. T. Binh, N. A. Tung, D. P. Nam, and N. H. Quang.
   International Journal of Control, Automation and Systems, vol. 17, pp. 465–473, 2019
   PDF ABS DOI BIB

   The considered Tractor Trailer Wheeled Mobile Robot (TTWMR) is type of Mobile Robot including a master robot – Tractor and slave robots – Trailers which moves along Tractor to track a given desired trajectory. The main difficulties of the stabilization and the tracking control of TTWMR are due to nonlinear and underactuated systems subjected to nonholonomic constraints. In order to overcome these problems, firstly, we develop the model of TTWMR and transform the tracking error model to the triangular form to propose a control law and an adaptive law. Secondly, the varying time state feedback controllers are designed to generate actuator torques by using Backstepping technique and Lyapunov direct’s method, in that these are able to guarantee the stability of the whole system including kinematics and dynamics. In addition, the Babarlat’s lemma is used to prove that the proposed tracking errors converge to the origin and the proposed adaptive law is carried on to tackle unknown parameter problem. The simulations are implemented to demonstrate the effective performances of the proposed adaptive law and the proposed control law.

   @article{binh2019adaptive,
     title = {An adaptive backstepping trajectory tracking control of a tractor trailer wheeled mobile robot},
     author = {Binh, Nguyen Thanh and Tung, Nguyen Anh and Nam, Dao Phuong and Quang, Nguyen Hong},
     journal = {International Journal of Control, Automation and Systems},
     volume = {17},
     pages = {465--473},
     year = {2019},
     publisher = {Springer},
     doi = {10.1007/s12555-017-0711-0}
   }

2017

1. “An adaptive control law against time-varying delays in bilateral teleoperation systems”.
   T. H. Anh, N. A. Tung, N. T. Binh, D. P. Nam, and V. Van Tu.
   2017 International Conference on System Science and Engineering (ICSSE), 2017, pp. 520–524
   PDF ABS DOI BIB

   Bilateral teleoperation is a robotic system helping humans to work with the remote environment through a dual robot which includes a local robot and a remote robot operating with considerable time delays. In order to overcome this obstacle, beside the proposed wave variables and scattering approaches [1], [2], the conventional methods without wave variables has been pointed out in [3], [4] with constant time delay. In this paper, we propose a new adaptive control law based on Lyapunov’s direct method to address time varying delays and position synchronization between two robots. In addition, force control was considered to guarantee tracking position error which converges to zero under humans and environment disturbances. The validity of them is based on theory and the good performance of the proposed controller shown in simulation results.

   @inproceedings{anh2017adaptive,
     title = {An adaptive control law against time-varying delays in bilateral teleoperation systems},
     author = {Anh, Tran Hoang and Tung, Nguyen Anh and Binh, Nguyen Thanh and Nam, Dao Phuong and Van Tu, Vu},
     booktitle = {2017 International Conference on System Science and Engineering (ICSSE)},
     pages = {520--524},
     year = {2017},
     organization = {IEEE},
     doi = {10.1109/ICSSE.2017.8030928}
   }

2. “Synchronization control of bilateral teleoperation systems by using wave variable method under varying time delay”.
   N. A. Tung, N. T. Binh, T. H. Anh, D. P. Nam, and N. M. Dong.
   2017 International Conference on System Science and Engineering (ICSSE), 2017, pp. 499–503
   PDF ABS DOI BIB

   Teleoperation is a human control system enabling humans to interact with the remote environment through a dual robot system which includes a master robot and a slave robot operating in two different places. Wave variables and scattering approaches were proposed in [1],[2] with constant time delay, [3],[4] with varying time delays. This paper develops them based on different wave variables and new passivity control to guarantee the stability of the whole system against varying time delays without assumption that absolute derivative of time delays is smaller than one. The validity of the control law is based on passivity theory. In addition, force controller design is considered for increasing transparency of system. The simulation results demonstrate the good performance of the proposed controller for position synchronization.

   @inproceedings{tung2017synchronization,
     title = {Synchronization control of bilateral teleoperation systems by using wave variable method under varying time delay},
     author = {Tung, Nguyen Anh and Binh, Nguyen Thanh and Anh, Tran Hoang and Nam, Dao Phuong and Dong, Nguyen Minh},
     booktitle = {2017 International Conference on System Science and Engineering (ICSSE)},
     pages = {499--503},
     year = {2017},
     organization = {IEEE},
     doi = {10.1109/ICSSE.2017.8030924}
   }

3. “Robust H-infinity backstepping control design of a wheeled inverted pendulum system”.
   N. T. Binh, N. M. Hung, N. A. Tung, D. P. Nam, and N. T. Long.
   2017 International Conference on System Science and Engineering (ICSSE), 2017, pp. 444–449
   PDF ABS DOI BIB

   The issue of applying H ∞ to control wheeled inverted pendulum is a topic of much concern on account of underactuated and nonlinear model. Authors in [1] selected Lyapunov candidate function presented following HJ equation. Almost previous papers using H - infinity to control WIP must assume that desired accelerator is zero and model is linearized at origin, leading to that system does not obtain global asymptotical stability when angular error leave neighborhood of origin. In this paper, we propose a new control method applying H - infinity and Backstepping technique based on Lyapunov direct method to stabilize tracking error to converge to arbitrary ball of origin. The simulation results of WIP under bounded disturbances demonstrate the effectiveness of the proposed controller.

   @inproceedings{binh2017robust,
     title = {Robust H-infinity backstepping control design of a wheeled inverted pendulum system},
     author = {Binh, Nguyen Thanh and Hung, Nguyen Manh and Tung, Nguyen Anh and Nam, Dao Phuong and Long, Nguyen Thanh},
     booktitle = {2017 International Conference on System Science and Engineering (ICSSE)},
     pages = {444--449},
     year = {2017},
     organization = {IEEE},
     doi = {10.1109/ICSSE.2017.8030914}
   }

4. “An approach robust nonlinear model predictive control with state-dependent disturbances via linear matrix inequalities”.
   N. T. Binh, N. A. Tung, D. P. Nam, and C. T. Trung.
   2017 International Conference on System Science and Engineering (ICSSE), 2017, pp. 418–422
   PDF ABS DOI BIB

   The issue of nonlinear model predictive control has always been a topic of much concern. We will propose a new approach to robust nonlinear model predictive control to class of nonlinear model system with input constraint under state-dependent disturbances. The considered class of model is separated into linear part at current state, nonlinear part and state-dependent disturbances which are assumed to have their bound. The state-feedback control law is obtained by that solving optimization problem of upper bound of infinite horizon cost function with input constraint via LMIs. In this paper, in order to guarantee robust stability, the proposed approach must generates feasible regions which ensures the existence of a solution and stable region bounded by that. Moreover, these regions are able to contract after every sampling time to proof the robust stability of the system. The simulation results demonstrate the good performance of the proposed approach to RNMPC.

   @inproceedings{binh2017approach,
     title = {An approach robust nonlinear model predictive control with state-dependent disturbances via linear matrix inequalities},
     author = {Binh, Nguyen Thanh and Tung, Nguyen Anh and Nam, Dao Phuong and Trung, Cao Thanh},
     booktitle = {2017 International Conference on System Science and Engineering (ICSSE)},
     pages = {418--422},
     year = {2017},
     organization = {IEEE},
     doi = {10.1109/ICSSE.2017.8030909}
   }