Pinning controllability of autonomous Boolean control networks

Autonomous Boolean networks (ABNs), which are developed to model the Boolean networks (BNs) with regulatory delays, are well known for their advantages of characterizing the intrinsic evolution rules of biological systems such as the gene regulatory networks. As a special type of ABNs with binary inputs, the autonomous Boolean control networks (ABCNs) are introduced for designing and analyzing the therapeutic intervention strategies where the binary inputs represent whether a certain medicine is dominated or not. An important problem in the therapeutic intervention is to design a control sequence steering an ABCN from an undesirable location (implying a diseased state) to a desirable one (corresponding to a healthy state). Motivated by such background, this paper aims to investigate the reachability and controllability of ABCNs with pinning controllers. Several necessary and sufficient criteria are provided by resorting to the semi-tensor product techniques of matrices. Moreover, an effective pinning control algorithm is presented for steering an ABCN from any given states to the desired state in the shortest time period. Numerical examples are also presented to demonstrate the results obtained.This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61329301, 61273156), Natural Science Foundation of Jiangsu Province of China (Grant No. BK20130017), Six Talent Peaks Project for the High Level Personnel from the Jiangsu Province of China (Grant No. 2015- DZXX-003), Scientific Research Foundations of Graduate School of Southeast University (Grant No. YBJJ1560), and Innovation Program of Jiangsu Province (Grant No. KYZZ15 0050)

A Note on the Observability of Temporal Boolean Control Network

Temporal Boolean network is a generalization of the Boolean network model that takes into account the time series nature of the data and tries to incorporate into the model the possible existence of delayed regulatory interactions among genes. This paper investigates the observability problem of temporal Boolean control networks. Using the semi tensor product of matrices, the temporal Boolean networks can be converted into discrete time linear dynamic systems with time delays. Then, necessary and sufficient conditions on the observability via two kinds of inputs are obtained. An example is given to illustrate the effectiveness of the obtained results

A Note on the Observability of Temporal Boolean Control Network

Temporal Boolean network is a generalization of the Boolean network model that takes into account the time series nature of the data and tries to incorporate into the model the possible existence of delayed regulatory interactions among genes. This paper investigates the observability problem of temporal Boolean control networks. Using the semi tensor product of matrices, the temporal Boolean networks can be converted into discrete time linear dynamic systems with time delays. Then, necessary and sufficient conditions on the observability via two kinds of inputs are obtained. An example is given to illustrate the effectiveness of the obtained results

Double Deep-Q Learning-Based Output Tracking of Probabilistic Boolean Control Networks

In this article, a reinforcement learning (RL)-based scalable technique is presented to control the probabilistic Boolean control networks (PBCNs). In particular, a double deep- $Q$ network (DD $Q\text{N}$ ) approach is firstly proposed to address the output tracking problem of PBCNs, and optimal state feedback controllers are obtained such that the output of PBCNs tracks a constant as well as a time-varying reference signal. The presented method is model-free and offers scalability, thereby provides an efficient way to control large-scale PBCNs that are a natural choice to model gene regulatory networks (GRNs). Finally, three PBCN models of GRNs including a 16-gene and 28-gene networks are considered to verify the presented results

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Decentralised sliding mode control for nonlinear interconnected systems with uncertainties

With the advances in science and technology, nonlinear large-scale interconnected systems have widely appeared in the real life. Traditional centralised control methods have inevitable disadvantages when they are used to deal with complex nonlinear interconnected systems with uncertainties. In connection with this, people desire to develop the novel control strategy which can be applied to complex interconnected systems. Therefore, decentralised sliding mode control (SMC) for interconnected systems has attracted great attention in related fields due to its advantages, for instance, simple structure, low cost of calculation, fast response, reduced-order sliding mode dynamics and insensitivity to matched variation of parameters and disturbances in systems. This thesis focuses on the development of decentralised SMC for nonlinear interconnected systems with uncertainties under certain assumptions. Several methods and different techniques have been considered in design of the controller to improve the robustness. The main contributions of this thesis include: • The state feedback decentralised SMC is developed for nonlinear interconnected systems with matched uncertainty and mismatched unknown interconnections. A state feedback decentralised SMC strategy, under the assumption that all system states are accessible, is proposed to attenuate the impact of the uncertainties by using bounds on uncertainties and interconnections. The bounds used in the design are fully nonlinear which provide higher applicability for different complex interconnected systems. Especially, for this fully nonlinear system, the proposed method does not need to use the technique of linearisation, which is widely used in existing work to deal with nonlinear interconnected systems with uncertainties. • The dynamic observer is applied to complex nonlinear interconnected systems with matched and mismatched uncertainties. This dynamic observer can estimate the system states which can not be achieved during the controller design. The proposed method has great identification ability with small estimated errors for the states of nonlinear interconnected systems with matched and mismatched uncertainties. It should be pointed out that the considered uncertainties of nonlinear interconnected systems have general forms, which means that the proposed method can be effectively used in more generalised nonlinear interconnected systems. • A variable structure observer-based decentralised SMC is proposed to control a class of nonlinear interconnected systems with matched and mismatched uncertainties. Based on the designed dynamic observer, a dynamic decentralised output feedback SMC using outputs and estimated states is presented to control the interconnected systems with matched and mismatched uncertainties. The nonlinear interconnections are employed in the control design to reduce the conservatism of the developed results. The bounds of the uncertainties are relaxed which are nonlinear and take more general forms. Moreover, the limitation for the interconnected system is reduced when compared with the existing results in which the proposed strategies adopt the full-order observer. Besides that, the presented method improves the robustness of nonlinear interconnected systems to be against the effects of uncertainties. This thesis also provides several numerical and practical simulations to demonstrate the effectiveness of the proposed decentralised SMC for nonlinear interconnected systems with matched uncertainty, mismatched uncertainty and nonlinear interconnections

Hybrid modeling and control of mechatronic systems using a piecewise affine dynamics approach

This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.publishedVersio