This paper investigates the adaptive tracking control problem for a class of uncertain single-input and single-output strict-feedback nonlinear systems with unknown control direction and disturbances. Dynamic surface control is utilized to handle the problem of “explosion of complexity” occurred in the conventional backstepping design. In order to escape analytic calculation, a first-order filter is used to generate the command signals and their derivatives. Moreover, Nussbaum function is employed to handle the problem of the unknown control coefficient. New controllers and adaptive laws are designed by combining the compensation tracking error and the prediction error that exist between the system state and the serial–parallel estimation model. It is proved that all the variables in the closed-loop system are bounded and the tracking error is driven to the origin with a small neighborhood. Finally, the simulation results are presented to verify the effectiveness of the proposed approach.

Adaptive Dynamic Surface Control Design for Uncertain Nonlinear Strict-Feedback Systems With Unknown Control Direction and Disturbances

This paper addresses the distributed consensus controller design approaches for one-sided Lipschitz nonlinear multiagents by employing relative state feedback. A new treatment for one-sided Lipschitz nonlinearity is rendered from the consensus control point of view. By employing the quadratic inner-boundedness and the one-sided Lipschitz constraints, a sufficient condition for asymptotic consensus of nonlinear systems under strongly connected communication topologies is provided. Further, a robust consensus protocol design scheme for the nonlinear multiagents is derived by ensuring the ${L_{2}}$ stability of the consensus error system. Furthermore, a novel robust consensus control scheme against amplitude-bounded perturbations is developed that guarantees asymptotic convergence of the consensus error into a compact set. Extensions to the proposed methodologies for the leader-following consensus for a spanning tree communication topology with the leader as the root are addressed. In contrast to the conventional consensus control methodologies, this paper is less conservative and can be applied to a broader class of nonlinear multiagent systems. Moreover, the proposed consensus control approach is less conservative for robustness against disturbances owing to its ability to handle amplitude-bounded disturbances and due to the relaxation of a balanced communication topology. A numerical simulation study is provided for the consensus control of eight mobile agents.

Distributed Consensus Control of One-Sided Lipschitz Nonlinear Multiagent Systems

Significant attention has been paid to the bipartite consensus (BC) problem of multiagent systems (MASs) with antagonistic interactions. In many practical applications, the convergence speed is very important. In this article, we focus on the finite-time BC (FTBC) problems of MASs with detail-balanced antagonistic interactions. First, two FTBC protocols are designed and expressed in a unified form. Then, by taking advantage of some recent findings on network stability, we obtain theoretical results to guarantee that the states of all agents reach agreement in finite time under our proposed protocols. Finally, the effectiveness and validity of the main theoretical results are demonstrated via two numerical examples.

Finite-Time Bipartite Consensus For Multiagent Systems Under Detail-Balanced Antagonistic Interactions

This paper investigates an adaptive consensus problem of a class of nonlinear multiagent systems in which the states are unmeasurable and the dynamics of all agents are supposed to be in strict-feedback form with unknown time-varying control coefficients. Due to the presence of uncertain nonlinearities in agents’ dynamics, radial basis function neural networks are used to approximate the unknown nonlinear functions, and a neural-network-based observer is designed to estimate the unmeasured states. The adaptive observer-based protocols are based on the relative output information of neighbors, and are constructed by adopting the dynamic surface control technique. It is proved that practical consensus of the system can be achieved with the proposed protocols. A simulation example is given to show the effectiveness of the proposed method.

Observer-Based Adaptive Consensus for a Class of Nonlinear Multiagent Systems

This paper addresses the leaderless consensus control for a network of multiagent systems with the one-sided Lipschitz and quadratic inner-boundedness nonlinear dynamics. A distributed dynamic consensus protocol as a function of relative state feedback of the neighboring agents with edge-based adaptive coupling weights is designed for an undirected communication graph to achieve asymptotic consensus among the nonlinear agents. Further, an extension of the proposed consensus protocol in the presence of external disturbance is devised to ensure the ${L_{2}}$ stability of the consensus error. This paper is less conservative and more general owing to its application to the systems with large Lipschitz constants and to a broad class of the nonlinear systems. In comparison to the previous consensus control schemes, the proposed approach can be employed to design consensus protocols for the one-sided Lipschitz systems with unknown communication topology. This feature enables the fully distributed consensus control as the communication graph information is not required for the consensus protocol design. Simulation results for a network of six mobile agents are provided to demonstrate the effectiveness of proposed consensus schemes in the absence or presence of an external disturbance.

Adaptive Distributed Consensus Control of One-Sided Lipschitz Nonlinear Multiagents

This paper addresses output-feedback-based distributed adaptive consensus control of multi-agent systems having Lipschitz nonlinear dynamics. Distributed dynamic protocols are designed based on the relative outputs of neighbouring agents and the adaptive coupling weights, under which consensus is reached between the nonlinear systems for all undirected connected communication topologies. Extension to the case of Lipschitz nonlinear multi-agent systems subjected to external disturbances is further studied, and a robust adaptive fully distributed consensus protocol is suggested. By application of a decoupling technique, necessary and sufficient conditions for the existence of these consensus protocols are provided in terms of linear matrix inequalities. Finally, numerical simulation results are demonstrated to validate the effectiveness of the theoretical results.

Distributed adaptive consensus control of Lipschitz nonlinear multi-agent systems using output feedback

Compressive sensing is a compression technique that can be effectively utilised in multimedia encryption. This paper proposes a new compressive sensing image encryption scheme using the Secure Hash Algorithm (SHA-512), Discrete Cosine Transform (DCT), orthogonal matrix and discrete Chirikov map-based random permutation. DCT is applied on a plaintext image and a block of DCT coefficients is multiplied with an orthogonal matrix. Inverse DCT and scaling are performed to restrict the values between 0 and 255. Furthermore, values are shuffled using Chirikov-based pseudo-random permutation. A strong trade-off exists between DCT block size and computational efficiency. The quality and Signal to Noise Ratio (SNR) of the decrypted image decreases when the size of the DCT matrix is reduced, increasing the speed of the encryption algorithm. An extensive security analyses of the proposed scheme are performed, which establishes the robustness, computational efficiency and security of the technique against cryptographic attacks.

Atif Jameel

Papers

Distributed Consensus Control of One-Sided Lipschitz Nonlinear Multiagent Systems

Distributed adaptive consensus control of Lipschitz nonlinear multi-agent systems using output feedback

A Novel Multi-Chaos Based Compressive Sensing Encryption Technique